Differential expression analysis of Arcuate Nucleus/Median Eminence astrocytes dataset from Lutomska LM et al 2022

Author

Evgenii O. Tretiakov

Published

July 26, 2023

Load data and setup parameters

Code 
# Load tidyverse infrastructure packages
suppressPackageStartupMessages({
  library(future)
  library(here)
  library(tidyverse)
  library(magrittr)
  library(stringr)
  library(skimr)
  library(RColorBrewer)
  library(viridis)
})


# Load packages for scRNA-seq analysis and visualisation
suppressPackageStartupMessages({
  library(ggplot2)
  library(cowplot)
  library(patchwork)
  library(ggstatsplot)
  library(dabestr)
  library(sceasy)
  library(anndata)
  library(Seurat)
  library(SeuratDisk)
  library(SeuratWrappers)
  library(schex)
  library(scCustomize)
})

sc <- import("scanpy", convert = FALSE)

Set paths

Code 
src_dir <- here("code")
data_dir <- here("data")
output_dir <- here("output")
plots_dir <- here(output_dir, "figures/")
tables_dir <- here(output_dir, "tables/")

Load helper functions and gene-sets

Code 
source(here(src_dir, "genes.R"))
source(here(src_dir, "functions.R"))

Set fixed variables

Code 
# set seed
reseed <- 42
set.seed(seed = reseed)

# Parameters for parallel execution
n_cores <- 32
plan("multisession", workers = n_cores)
options(
  future.globals.maxSize = 100000 * 1024^2,
  future.rng.onMisuse = "ignore"
)
plan()
multisession:
- args: function (..., workers = 32, envir = parent.frame())
- tweaked: TRUE
- call: plan("multisession", workers = n_cores)
Code 
# ggplot2 theme
theme_set(ggmin::theme_powerpoint())
Code 
bioproject <- "PRJNA847050"
project <- "lutomska2022-Arc"
cb_fpr <- 0.001
low_cutoff_gene <- 500
high_cutoff_gene <- NULL
high_cutoff_gene <- 10000
low_cutoff_umis <- NULL
low_cutoff_umis <- -Inf
high_cutoff_umis <- 45000
high_cutoff_pc_mt <- 25
high_cutoff_pc_ribo <- 20
high_cutoff_pc_hb <- 0.1
high_cutoff_doublet_score <- 0.33
high_cutoff_complexity <- 0.8

Load selected astrocytes data from Lutomska LM et al (2022)

Code 
anndata <- sc$read(here(
  data_dir,
  sprintf("class_cello/%s-whole_dataset-%s-cello_annotation.h5ad", bioproject, cb_fpr)
))

Convert adata object to R AnnDataR6 object.

Code 
adata <- py_to_r(anndata)
class(adata)
[1] "AnnDataR6" "R6"
Code 
class(adata$X)
[1] "dgCMatrix"
attr(,"package")
[1] "Matrix"
Code 
adata
AnnData object with n_obs × n_vars = 14594 × 24746
    obs: 'nCount_RAW', 'nFeature_RAW', 'nCount_RNA', 'nFeature_RNA', 'orig.ident', 'nFeature_Diff', 'nCount_Diff', 'percent_mito', 'percent_ribo', 'percent_mito_ribo', 'percent_hb', 'log10GenesPerUMI', 'cell_name', 'barcode', 'latent_RT_efficiency', 'latent_cell_probability', 'latent_scale', 'doublet_score', 'predicted_doublets', 'QC', 'var_regex', 'RNA_snn_res.0.5', 'RNA_snn_res.0.71728703859461', 'RNA_snn_res.1.18939286532015', 'RNA_snn_res.3.00000100000001', 'seurat_clusters', 'k_tree', 'comb_clstr1', 'S.Score', 'G2M.Score', 'Phase', 'nCount_SCT', 'nFeature_SCT', 'SCT_snn_res.1', 'SCT_snn_res.1.10031502002514', 'SCT_snn_res.1.2198400795032', 'SCT_snn_res.1.36467746508232', 'SCT_snn_res.1.54382016547197', 'SCT_snn_res.1.77109349840298', 'SCT_snn_res.2.0689045782524', 'SCT_snn_res.2.47612417203789', 'SCT_snn_res.3.06661007679595', 'SCT_snn_res.4.00000100000002', 'bioproject', 'project', 'model', 'tech', 'region', 'sex', 'stage', 'libname', 'expbtch', 'condit', 'ora_celltype'
    var: 'vst.mean', 'vst.variance', 'vst.variance.expected', 'vst.variance.standardized', 'vst.variable'
    uns: 'k_tree_colors', 'name', 'ora_celltype_colors'
    obsm: 'X_pacmap', 'X_pca', 'X_umap', 'ora_estimate', 'ora_pvals'
Code 
srt_path <- here(
  data_dir,
  sprintf("%s-whole_dataset-%s-cello_annotation.h5ad", bioproject, cb_fpr)
)

expr_mtx <- t(as.matrix(adata$raw$X))
colnames(expr_mtx) <- rownames(adata$X)
rownames(expr_mtx) <- adata$var_names
srt <- CreateSeuratObject(
  expr_mtx,
  assay = "RNA",
  project = "individual_hypothalamic_nuclei_astrocytes_evaluation_dataset",
  meta.data = as.data.frame(adata$obs),
  row.names = colnames(adata$X)
)

Idents(srt) <- "ora_celltype"
srt <- subset(srt, idents = c("Astrocytes"))

Idents(srt) <- "expbtch"
scarc <- subset(srt, idents = c("control", "hfd_15"))
srt <- subset(srt, idents = c("control", "hfd_05"))

print(srt)
An object of class Seurat 
24746 features across 2747 samples within 1 assay 
Active assay: RNA (24746 features, 0 variable features)
Code 
rm(adata, anndata, expr_mtx)
invisible(gc())
Code 
markers_region <-
  readr::read_csv(
    here(
      "data",
      "individual_hypothalamic_nuclei_astrocytes_evaluation_dataset-all-marker-genes-astrotrap.csv"
    ),
    col_types = cols(
      p_val = col_double(),
      avg_log2FC = col_double(),
      pct.1 = col_double(),
      pct.2 = col_double(),
      p_val_adj = col_double(),
      cluster = col_character(),
      gene = col_character(),
      pct_diff = col_double()
    )
  )
Code 
markers_region <- markers_region %>%
  filter(pct.2 < 0.3, pct_diff > 0.1) %>%
  group_by(cluster)

at_top_50 <- Extract_Top_Markers(marker_dataframe = markers_region, num_genes = 50, group_by = "cluster", gene_column = "gene", rank_by = "avg_log2FC", make_unique = TRUE, named_vector = FALSE)

markers_region2 <- markers_region %>%
  filter(gene %in% c(nmr, npr, transcription_factors, mitochondrial)) %>%
  group_by(cluster)

at_top_50s <- Extract_Top_Markers(marker_dataframe = markers_region2, num_genes = 50, group_by = "cluster", gene_column = "gene", rank_by = "avg_log2FC", make_unique = TRUE, named_vector = FALSE)


selected_genes <- c(
  "Insr", "Meis1", "Igf1r", "Nrf1", "Prlr", "Camk1d", "Lars2", "Cacna2d3", # 0 ARC
  "Dcn", "Ptgds", "Nupr1", "Igfbp2", "Nrarp", "Ctnna2", "Ldlr", "Mmp14", # 1 LHA
  "Nkx6-2", "Cirbp", "Selenop", # 2 MnPO
  "Foxg1", "Crym", "Sema3c", "Meis2", "Dbp", # 3 POA
  "Egr1", "Ttr", "Btg2", "Mbnl3", "Pgf", "Irs4", "Gpr101", "Nr3c2", "Agtr1", # 4 PVN
  "Rfx4", "Dbx2", "Prokr2", "Cebpb", "Zic1", "Zic2", "Zic5", "Ccn1", "Gata4", "Klf4", "Klf10", # 5 SCN
  "Tbx3", "Fis1", "Ndn", "Psmc5", "Drap1", "Pcsk1n", "Rtn1", # 6 VMH
  "Emx2", "Sgip1", "Myoc", "Hivep3", "Dcc", "Ralyl", "Ltbp1", "Egfem1", # 7 VPH
  "Klf4", "Atf3", "Nrg1", "Cdk8", "Grpr", "Qrfpr", "Hcrtr1", "Hcrtr2", "Tacr1", "Trhr", "Tshr",
  "Gfap", "Fgf1", "Fgfr3", "Hepacam", "Hif1", "Htra1", "Lxn", "Ndrg2", "Ntn1", "Nfia", "Slit2", "Aqp4", "S100a1", "S100a6", "S100b", "Slc1a2", "Slc1a3", "Slc38a1", "Vegfa", "Fos", "Fosb", "Jun", "Junb", "Jund", "Ier2", "Socs3", "Pde10a", "Fbln5", "Otp", "Nr4a1", "Six6", "Emx2", "Myt1l", "Adcyap1r1", "Ghr", "Ntrk2", "Npy1r", "Gria1", "Gria2", "Grin2b", "Grin3a", "Grm3", "Grm7", "Gabrb1", "Gabbr1", "Gabbr2", "Rfx3", "Nr5a1", "Nkx2-1", "Otx2", "Bclaf1", "Foxo3", "Dlx1", "Lrrc6", "Peg3", "Elavl2", "Isl1", "Zfp36", "Otx1", "Pitx2",
  "2610507B11Rik",
  "5430405H02Rik",
  "9630014M24Rik",
  "Abi2",
  "Adam22",
  "AI480526",
  "Ank3",
  "Ap3m1",
  "Aplp1",
  "App",
  "Araf",
  "Arhgap12",
  "Arhgef10l",
  "Arhgef28",
  "Arpp21",
  "Arrb1",
  "Arsb",
  "Asic2",
  "Atg10",
  "Atp11b",
  "Atp1b1",
  "Atp1b3",
  "Atp6v1b2",
  "Azin1",
  "B3galt2",
  "Basp1",
  "Bicd1",
  "Bmt2",
  "Btg2",
  "Cacna1a",
  "Camta1",
  "Car10",
  "Ccser1",
  "Cd38",
  "Cdc26",
  "Cdc42",
  "Chd6",
  "Clstn1",
  "Coro2b",
  "Cry2",
  "Csmd2",
  "Csnk1g3",
  "Cyb5b",
  "Dcc",
  "Ddrgk1",
  "Ddx6",
  "Dennd5a",
  "Dlat",
  "Dlg2",
  "Dlg5",
  "Dnm2",
  "Dock9",
  "Dpp10",
  "Dscam",
  "Dync1i1",
  "Dzank1",
  "Dzip1",
  "Eef2",
  "Efr3b",
  "Egfem1",
  "Epas1",
  "Epha5",
  "Esco1",
  "Fam107a",
  "Fam155a",
  "Fam171a1",
  "Fam193a",
  "Fam219a",
  "Fbxw2",
  "Fer",
  "Fnbp1l",
  "Fos",
  "Gaa",
  "Gabrb2",
  "Gabrb3",
  "Gfap",
  "Gm1604a",
  "Gnas",
  "Gnl3l",
  "Gpr158",
  "Gprasp1",
  "Gria4",
  "Grik4",
  "Hk1",
  "Hmbox1",
  "Hsd17b12",
  "Id4",
  "Ipo9",
  "Jun",
  "Kcnip4",
  "Kif5a",
  "Klc1",
  "Klhl7",
  "Lcor",
  "Lhfpl3",
  "Lix1",
  "Lrrc8a",
  "Luzp1",
  "Ly6h",
  "Map2k1",
  "Map4k5",
  "Map7d2",
  "Mapk8",
  "Marcksl1",
  "Marf1",
  "Megf9",
  "Mia2",
  "Mindy2",
  "Mmp16",
  "mt-Cytb",
  "mt-Nd1",
  "mt-Nd2",
  "mt-Nd4",
  "Mthfd2l",
  "Mtss2",
  "Ncan",
  "Ncl",
  "Ndufc2",
  "Nfasc",
  "Nfix",
  "Nfs1",
  "Nhs",
  "Nkx6-2",
  "Nmnat2",
  "Nsf",
  "Nsg2",
  "Nxph1",
  "Ocrl",
  "Pam",
  "Paqr6",
  "Parp6",
  "Pcbp2",
  "Pcsk1n",
  "Pdgfd",
  "Pdss1",
  "Pdxdc1",
  "Pdzph1",
  "Pea15a",
  "Peg3",
  "Pet100",
  "Pi4ka",
  "Pkia",
  "Podxl2",
  "Prr14",
  "Psd2",
  "Rab11fip4",
  "Rab2a",
  "Rab6b",
  "Rac1",
  "Rad23b",
  "Ralyl",
  "Rbfox1",
  "Rbms3",
  "Rftn2",
  "Rgs7bp",
  "Rpl22",
  "Rpl30",
  "Rpl37a",
  "Rps14",
  "Rps6",
  "Rpsa",
  "Rtn1",
  "Samd12",
  "Scarb2",
  "Scd1",
  "Selenot",
  "Sfi1",
  "Shisa6",
  "Ski",
  "Slc12a6",
  "Slc25a3",
  "Smarcc1",
  "Snhg14",
  "Snrk",
  "Snrpn",
  "Sntg1",
  "Snx21",
  "Spcs2",
  "Spop",
  "Spred2",
  "Stk3",
  "Stxbp5l",
  "Taf1",
  "Tafa1",
  "Tbc1d5",
  "Tbc1d9b",
  "Tef",
  "Tenm2",
  "Tenm4",
  "Thra",
  "Thrsp",
  "Timp2",
  "Tmem106b",
  "Tmem245",
  "Tmsb4x",
  "Tmx4",
  "Tnr",
  "Tom1",
  "Tsix",
  "Tspan13",
  "Ttc3",
  "Ube2l3",
  "Ube2r2",
  "Vps13d",
  "Vps35l",
  "Vwa8",
  "Wasf3",
  "Wdr26",
  "Ywhae",
  "Zfp644",
  "Zwint"
)

selected_genes <- unique(c(selected_genes, at_top_50, at_top_50s, mitochondrial))

selected_genes <- selected_genes[selected_genes %in% rownames(GetAssayData(object = srt, slot = "data"))]

5 days of HFD

Code 
srt <- NormalizeData(srt)
srt <- FindVariableFeatures(srt, selection.method = "vst", nfeatures = 5000)
all.genes <- rownames(srt)
srt <- ScaleData(srt, features = selected_genes)
Code 
invisible(gc())
plan("sequential")
invisible(gc())
plan("multisession", workers = n_cores)
all_markers_genes <-
  FindAllMarkers(object = srt, verbose = T, test.use = "LR", latent.vars = c("nFeature_RNA"), only.pos = F, min.pct = 0, logfc.threshold = 0, random.seed = reseed, min.cells.feature = 1, return.thresh = 1, features = selected_genes)
all_markers_genes <-
  all_markers_genes %>%
  Add_Pct_Diff()

write_csv(all_markers_genes, here(data_dir, sprintf("%s-all-marker-genes-condition05-goi.csv", bioproject)))
all_markers_genes

Dotplots 5 days of HFD

Code 
all_markers_genes2 <- all_markers_genes %>%
  filter(
    gene %in% c(npr, nmr, transcription_factors),
    pct_diff >= 0.1,
    pct.1 >= 0.333
  ) %>%
  arrange(desc(avg_log2FC))

at_top_5 <- Extract_Top_Markers(marker_dataframe = all_markers_genes, num_genes = 5, group_by = "cluster", gene_column = "gene", rank_by = "avg_log2FC", make_unique = TRUE, named_vector = FALSE)
at_top_30 <- Extract_Top_Markers(marker_dataframe = all_markers_genes, num_genes = 30, group_by = "cluster", gene_column = "gene", rank_by = "avg_log2FC")
at_top_10s <- Extract_Top_Markers(marker_dataframe = all_markers_genes2, num_genes = 10, group_by = "cluster", gene_column = "gene", rank_by = "avg_log2FC", make_unique = TRUE, named_vector = FALSE)
at_top_30s <- Extract_Top_Markers(marker_dataframe = all_markers_genes2, num_genes = 30, group_by = "cluster", gene_column = "gene", rank_by = "avg_log2FC")

unselected markers 5 days of HFD

Code 
DotPlot_scCustom(seurat_object = srt, colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"), features = at_top_5, flip_axes = T, x_lab_rotate = TRUE)

selected markers 5 days of HFD

Code 
DotPlot_scCustom(seurat_object = srt, colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"), features = at_top_10s, flip_axes = T, x_lab_rotate = TRUE)

Receptors of neuropeptides markers 5 days of HFD

Code 
DotPlot_scCustom(seurat_object = srt, colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"), features = npr[npr %in% rownames(GetAssayData(object = srt, slot = "scale.data"))], flip_axes = T, x_lab_rotate = TRUE)

Receptors of neuromediators markers 5 days of HFD

Code 
DotPlot_scCustom(seurat_object = srt, colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"), features = nmr[nmr %in% rownames(GetAssayData(object = srt, slot = "scale.data"))], flip_axes = T, x_lab_rotate = TRUE)

Other markers 5 days of HFD

Code 
DotPlot_scCustom(seurat_object = srt, colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"), features = genes.embed[genes.embed %in% rownames(GetAssayData(object = srt, slot = "scale.data"))], flip_axes = T, x_lab_rotate = TRUE)

Mitochondrial markers 5 days of HFD

Code 
DotPlot_scCustom(seurat_object = srt, colors_use = viridis(n = 30, alpha = .75, direction = -1, option = "E"), features = mitochondrial[mitochondrial %in% rownames(GetAssayData(object = srt, slot = "scale.data"))], flip_axes = T, x_lab_rotate = TRUE)

Code 
Stacked_VlnPlot(seurat_object = srt, features = mitochondrial[mitochondrial %in% rownames(GetAssayData(object = srt, slot = "scale.data"))], x_lab_rotate = TRUE)

Heatmap selected markers 5 days of HFD

Code 
DoHeatmap(srt, group.by = "expbtch", group.colors = c("0" = "black", "1" = "purple", "2" = "blue", "3" = "darkgreen", "4" = "green", "5" = "yellow", "6" = "red", "7" = "grey"), features = at_top_10s, size = 4, angle = 0) + NoLegend()

Gardner-Altman plot for selected genes of 5 days of HFD

Code 
df.test <-
  GetAssayData(object = srt, slot = "data") %>%
  as.data.frame() %>%
  t() %>%
  bind_cols(srt@meta.data) %>%
  select(c("cell_name", "expbtch", selected_genes))

glimpse(df.test)
Rows: 2,747
Columns: 551
$ cell_name       <chr> "SRR19578590_AAACCCATCTGACGCG-1", "SRR19578590_AAACGCT…
$ expbtch         <fct> hfd_05, hfd_05, hfd_05, hfd_05, hfd_05, hfd_05, hfd_05…
$ Insr            <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Meis1           <dbl> 0.9917400, 0.0000000, 1.3144143, 0.9183356, 2.3123177,…
$ Igf1r           <dbl> 0.6140827, 1.8422426, 1.3144143, 1.9488301, 0.0000000,…
$ Nrf1            <dbl> 0.6140827, 0.0000000, 2.4757213, 0.5610768, 1.7135998,…
$ Prlr            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Camk1d          <dbl> 1.8062808, 2.4528438, 3.1259076, 1.3888498, 1.9551815,…
$ Lars2           <dbl> 0.9917400, 2.8292067, 1.3144143, 0.5610768, 0.0000000,…
$ Cacna2d3        <dbl> 1.6562840, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Dcn             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Ptgds           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Nupr1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Igfbp2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Nrarp           <dbl> 0.0000000, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Ctnna2          <dbl> 0.000000, 0.000000, 0.000000, 2.143072, 0.000000, 0.00…
$ Ldlr            <dbl> 0.0000000, 0.0000000, 1.8633264, 0.0000000, 0.0000000,…
$ Mmp14           <dbl> 1.4797489, 0.0000000, 1.3144143, 0.5610768, 1.3944114,…
$ `Nkx6-2`        <dbl> 0.9917400, 0.0000000, 0.0000000, 1.3888498, 0.0000000,…
$ Cirbp           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Selenop         <dbl> 0.9917400, 0.0000000, 0.0000000, 1.9488301, 1.3944114,…
$ Foxg1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Crym            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Sema3c          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Meis2           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Dbp             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Egr1            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Ttr             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Btg2            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Mbnl3           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Pgf             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Irs4            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gpr101          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Nr3c2           <dbl> 2.5550116, 0.0000000, 0.0000000, 1.7075355, 2.1496089,…
$ Rfx4            <dbl> 1.4797489, 3.1020138, 2.2156876, 1.5608344, 1.3944114,…
$ Dbx2            <dbl> 0.9917400, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Prokr2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Cebpb           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Zic1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Zic2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Zic5            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Ccn1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Gata4           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Klf4            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Klf10           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Tbx3            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Fis1            <dbl> 1.2652227, 2.4528438, 0.0000000, 0.0000000, 0.0000000,…
$ Ndn             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Psmc5           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Drap1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pcsk1n          <dbl> 0.0000000, 1.8422426, 0.0000000, 0.5610768, 0.9227897,…
$ Rtn1            <dbl> 1.4797489, 2.4528438, 0.0000000, 0.9183356, 0.9227897,…
$ Emx2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Sgip1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Myoc            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Hivep3          <dbl> 0.0000000, 0.0000000, 0.0000000, 1.3888498, 0.0000000,…
$ Dcc             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Ralyl           <dbl> 0.00000, 0.00000, 0.00000, 0.00000, 0.00000, 0.00000, …
$ Ltbp1           <dbl> 1.265223, 1.842243, 0.000000, 0.000000, 0.000000, 0.95…
$ Egfem1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Atf3            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Nrg1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Cdk8            <dbl> 0.6140827, 1.8422426, 1.8633264, 0.0000000, 1.3944114,…
$ Grpr            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Qrfpr           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Hcrtr1          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Hcrtr2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Tacr1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Trhr            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Tshr            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gfap            <dbl> 0.6140827, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Fgf1            <dbl> 1.4797489, 0.0000000, 0.0000000, 1.5608344, 0.9227897,…
$ Fgfr3           <dbl> 2.413726, 0.000000, 1.863326, 2.143072, 1.955181, 1.75…
$ Hepacam         <dbl> 2.2491428, 0.0000000, 1.8633264, 1.1810141, 0.9227897,…
$ Htra1           <dbl> 1.936686, 1.842243, 1.863326, 2.624197, 1.955181, 1.75…
$ Lxn             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Ndrg2           <dbl> 2.678784, 0.000000, 1.863326, 2.624197, 2.149609, 2.73…
$ Ntn1            <dbl> 1.806281, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Nfia            <dbl> 2.618812, 0.000000, 2.998628, 3.127821, 2.452220, 1.75…
$ Slit2           <dbl> 1.656284, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Aqp4            <dbl> 1.479749, 2.452844, 1.863326, 2.143072, 1.955181, 2.19…
$ S100a1          <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ S100a6          <dbl> 0.0000000, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ S100b           <dbl> 0.0000000, 0.0000000, 0.0000000, 1.7075355, 0.9227897,…
$ Slc1a2          <dbl> 4.168169, 2.829207, 4.015507, 4.173887, 4.145803, 3.95…
$ Slc1a3          <dbl> 3.100048, 2.452844, 3.125908, 3.572843, 3.342629, 3.39…
$ Slc38a1         <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Vegfa           <dbl> 0.0000000, 0.0000000, 1.3144143, 1.7075355, 0.9227897,…
$ Fos             <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.95…
$ Fosb            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Jun             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Junb            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Jund            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Ier2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Socs3           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Pde10a          <dbl> 0.0000000, 1.8422426, 0.0000000, 0.0000000, 0.0000000,…
$ Fbln5           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Otp             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Nr4a1           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Six6            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Myt1l           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Adcyap1r1       <dbl> 1.4797489, 0.0000000, 2.2156876, 1.9488301, 1.3944114,…
$ Ghr             <dbl> 1.4797489, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Ntrk2           <dbl> 3.395537, 3.102014, 3.856165, 3.551488, 2.684215, 2.62…
$ Npy1r           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gria1           <dbl> 3.770414, 1.842243, 3.594388, 3.572843, 2.954681, 2.83…
$ Gria2           <dbl> 0.9917400, 0.0000000, 2.2156876, 2.0506598, 1.9551815,…
$ Grin2b          <dbl> 0.0000000, 1.8422426, 1.3144143, 2.0506598, 0.9227897,…
$ Grin3a          <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Grm3            <dbl> 1.9366855, 1.8422426, 0.0000000, 1.9488301, 0.9227897,…
$ Grm7            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gabrb1          <dbl> 3.137535, 2.452844, 2.852752, 2.050660, 3.661187, 3.54…
$ Gabbr1          <dbl> 0.9917400, 0.0000000, 0.0000000, 1.1810141, 1.7135998,…
$ Gabbr2          <dbl> 2.052030, 1.842243, 2.475721, 1.388850, 2.574930, 0.00…
$ Rfx3            <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 1.3944114,…
$ Nr5a1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ `Nkx2-1`        <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Otx2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Bclaf1          <dbl> 0.9917400, 0.0000000, 1.8633264, 0.0000000, 0.9227897,…
$ Foxo3           <dbl> 0.6140827, 0.0000000, 1.3144143, 1.1810141, 0.9227897,…
$ Dlx1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Lrrc6           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Peg3            <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 1.9551815,…
$ Elavl2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Isl1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Zfp36           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Otx1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Pitx2           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ `2610507B11Rik` <dbl> 0.9917400, 1.8422426, 0.0000000, 0.5610768, 0.9227897,…
$ `5430405H02Rik` <dbl> 1.2652227, 0.0000000, 0.0000000, 0.0000000, 1.3944114,…
$ `9630014M24Rik` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.95…
$ Abi2            <dbl> 1.4797489, 0.0000000, 0.0000000, 0.5610768, 1.7135998,…
$ Adam22          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ AI480526        <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 0.0000000,…
$ Ank3            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Ap3m1           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Aplp1           <dbl> 0.6140827, 0.0000000, 1.8633264, 1.1810141, 0.0000000,…
$ App             <dbl> 0.9917400, 1.8422426, 0.0000000, 1.1810141, 0.0000000,…
$ Araf            <dbl> 1.2652227, 0.0000000, 1.3144143, 0.5610768, 1.7135998,…
$ Arhgap12        <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Arhgef10l       <dbl> 0.9917400, 0.0000000, 0.0000000, 1.5608344, 0.9227897,…
$ Arhgef28        <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Arpp21          <dbl> 0.6140827, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Arrb1           <dbl> 0.0000000, 0.0000000, 0.0000000, 1.1810141, 0.9227897,…
$ Arsb            <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 1.3944114,…
$ Asic2           <dbl> 2.0520299, 0.0000000, 1.3144143, 1.8354431, 0.9227897,…
$ Atg10           <dbl> 0.0000000, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Atp11b          <dbl> 0.6140827, 0.0000000, 1.8633264, 0.5610768, 0.0000000,…
$ Atp1b1          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Atp1b3          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Atp6v1b2        <dbl> 1.4797489, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Azin1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ B3galt2         <dbl> 0.9917400, 0.0000000, 1.3144143, 1.3888498, 0.9227897,…
$ Basp1           <dbl> 0.6140827, 2.4528438, 0.0000000, 0.5610768, 0.9227897,…
$ Bicd1           <dbl> 1.2652227, 0.0000000, 0.0000000, 0.9183356, 1.7135998,…
$ Bmt2            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Cacna1a         <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Camta1          <dbl> 1.2652227, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Car10           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Ccser1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.3944114,…
$ Cd38            <dbl> 1.9366855, 0.0000000, 0.0000000, 1.8354431, 1.7135998,…
$ Cdc26           <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Cdc42           <dbl> 0.0000000, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Chd6            <dbl> 1.2652227, 1.8422426, 0.0000000, 1.7075355, 1.9551815,…
$ Clstn1          <dbl> 1.2652227, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Coro2b          <dbl> 0.9917400, 0.0000000, 1.3144143, 0.9183356, 1.7135998,…
$ Cry2            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Csmd2           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Csnk1g3         <dbl> 0.9917400, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Cyb5b           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Ddrgk1          <dbl> 0.9917400, 0.0000000, 0.0000000, 1.3888498, 0.0000000,…
$ Ddx6            <dbl> 0.9917400, 0.0000000, 0.0000000, 1.3888498, 1.3944114,…
$ Dennd5a         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Dlat            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Dlg2            <dbl> 1.9366855, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Dlg5            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Dnm2            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Dock9           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Dpp10           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Dscam           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Dync1i1         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Dzank1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Dzip1           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Eef2            <dbl> 0.0000000, 0.0000000, 0.0000000, 1.3888498, 0.0000000,…
$ Efr3b           <dbl> 0.9917400, 0.0000000, 0.0000000, 1.9488301, 0.9227897,…
$ Epas1           <dbl> 0.6140827, 1.8422426, 1.3144143, 1.3888498, 0.0000000,…
$ Epha5           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Esco1           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Fam107a         <dbl> 0.0000000, 1.8422426, 0.0000000, 1.8354431, 0.9227897,…
$ Fam155a         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 1.3944114,…
$ Fam171a1        <dbl> 1.4797489, 0.0000000, 1.3144143, 0.5610768, 1.3944114,…
$ Fam193a         <dbl> 0.9917400, 0.0000000, 1.3144143, 0.9183356, 0.0000000,…
$ Fam219a         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Fbxw2           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Fer             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Fnbp1l          <dbl> 0.6140827, 0.0000000, 1.8633264, 1.1810141, 0.9227897,…
$ Gaa             <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Gabrb2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gabrb3          <dbl> 1.4797489, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Gm1604a         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Gnas            <dbl> 1.2652227, 0.0000000, 1.3144143, 1.3888498, 2.1496089,…
$ Gnl3l           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Gpr158          <dbl> 0.0000000, 0.0000000, 2.4757213, 0.0000000, 0.0000000,…
$ Gprasp1         <dbl> 0.9917400, 1.8422426, 2.6819013, 0.5610768, 0.9227897,…
$ Gria4           <dbl> 1.479749, 0.000000, 0.000000, 0.000000, 0.000000, 0.95…
$ Grik4           <dbl> 0.6140827, 0.0000000, 1.3144143, 1.1810141, 0.0000000,…
$ Hk1             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Hmbox1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Hsd17b12        <dbl> 0.0000000, 0.0000000, 1.3144143, 0.9183356, 0.0000000,…
$ Id4             <dbl> 0.0000000, 0.0000000, 1.3144143, 2.0506598, 1.3944114,…
$ Ipo9            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Kcnip4          <dbl> 0.0000000, 2.8292067, 1.8633264, 1.8354431, 1.7135998,…
$ Kif5a           <dbl> 0.0000000, 1.8422426, 0.0000000, 0.5610768, 0.9227897,…
$ Klc1            <dbl> 0.9917400, 1.8422426, 1.3144143, 0.9183356, 0.9227897,…
$ Klhl7           <dbl> 0.6140827, 2.4528438, 0.0000000, 1.1810141, 0.0000000,…
$ Lcor            <dbl> 0.6140827, 2.4528438, 0.0000000, 0.5610768, 0.0000000,…
$ Lhfpl3          <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Lix1            <dbl> 0.6140827, 0.0000000, 1.3144143, 0.9183356, 0.0000000,…
$ Lrrc8a          <dbl> 0.0000000, 0.0000000, 0.0000000, 1.9488301, 1.3944114,…
$ Luzp1           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Ly6h            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Map2k1          <dbl> 0.6140827, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Map4k5          <dbl> 0.6140827, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Map7d2          <dbl> 0.0000000, 0.0000000, 0.0000000, 1.1810141, 0.9227897,…
$ Mapk8           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Marcksl1        <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Marf1           <dbl> 0.0000000, 0.0000000, 0.0000000, 1.1810141, 0.9227897,…
$ Megf9           <dbl> 0.9917400, 0.0000000, 1.3144143, 1.5608344, 1.3944114,…
$ Mia2            <dbl> 0.9917400, 0.0000000, 1.8633264, 0.0000000, 0.0000000,…
$ Mindy2          <dbl> 0.0000000, 0.0000000, 2.2156876, 0.5610768, 0.9227897,…
$ Mmp16           <dbl> 0.000000, 0.000000, 0.000000, 1.835443, 0.000000, 0.00…
$ `mt-Cytb`       <dbl> 3.450831, 4.249049, 4.648782, 3.160262, 3.101362, 3.07…
$ `mt-Nd1`        <dbl> 3.137535, 4.084587, 3.666531, 3.308335, 2.872395, 3.33…
$ `mt-Nd2`        <dbl> 3.208539, 3.887650, 4.194818, 3.412790, 2.954681, 3.27…
$ `mt-Nd4`        <dbl> 2.888103, 4.454008, 4.538682, 2.727762, 2.954681, 2.92…
$ Mthfd2l         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Mtss2           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Ncan            <dbl> 0.9917400, 0.0000000, 1.3144143, 1.7075355, 1.7135998,…
$ Ncl             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.9551815,…
$ Ndufc2          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Nfasc           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Nfix            <dbl> 0.9917400, 0.0000000, 1.3144143, 1.5608344, 1.7135998,…
$ Nfs1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Nhs             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Nmnat2          <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Nsf             <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Nsg2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Nxph1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Ocrl            <dbl> 1.2652227, 0.0000000, 1.3144143, 1.1810141, 1.7135998,…
$ Pam             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Paqr6           <dbl> 0.6140827, 0.0000000, 1.3144143, 1.7075355, 1.9551815,…
$ Parp6           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Pcbp2           <dbl> 1.6562840, 0.0000000, 0.0000000, 0.9183356, 1.9551815,…
$ Pdgfd           <dbl> 2.7889105, 1.8422426, 1.3144143, 1.1810141, 2.1496089,…
$ Pdss1           <dbl> 1.2652227, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pdxdc1          <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Pdzph1          <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pea15a          <dbl> 0.9917400, 1.8422426, 0.0000000, 1.1810141, 0.9227897,…
$ Pet100          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pi4ka           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pkia            <dbl> 0.6140827, 0.0000000, 1.3144143, 0.0000000, 0.9227897,…
$ Podxl2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Prr14           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Psd2            <dbl> 0.6140827, 0.0000000, 1.8633264, 1.9488301, 2.3123177,…
$ Rab11fip4       <dbl> 0.0000000, 0.0000000, 1.3144143, 1.1810141, 0.0000000,…
$ Rab2a           <dbl> 1.2652227, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Rab6b           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Rac1            <dbl> 1.2652227, 0.0000000, 1.3144143, 0.9183356, 0.0000000,…
$ Rad23b          <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Rbfox1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Rbms3           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Rftn2           <dbl> 1.9366855, 0.0000000, 1.3144143, 1.9488301, 1.3944114,…
$ Rgs7bp          <dbl> 0.6140827, 0.0000000, 0.0000000, 1.1810141, 1.3944114,…
$ Rpl22           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Rpl30           <dbl> 0.0000000, 1.8422426, 0.0000000, 0.0000000, 0.0000000,…
$ Rpl37a          <dbl> 0.0000000, 3.7724251, 0.0000000, 0.0000000, 0.9227897,…
$ Rps14           <dbl> 0.6140827, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Rps6            <dbl> 0.0000000, 2.4528438, 0.0000000, 0.5610768, 0.0000000,…
$ Rpsa            <dbl> 0.0000000, 3.4923793, 0.0000000, 0.0000000, 0.0000000,…
$ Samd12          <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Scarb2          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Scd1            <dbl> 0.6140827, 0.0000000, 0.0000000, 1.1810141, 1.3944114,…
$ Selenot         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 1.3944114,…
$ Sfi1            <dbl> 0.000000, 0.000000, 0.000000, 1.388850, 0.000000, 0.00…
$ Shisa6          <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Ski             <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Slc12a6         <dbl> 0.6140827, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Slc25a3         <dbl> 1.4797489, 1.8422426, 0.0000000, 0.0000000, 1.3944114,…
$ Smarcc1         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Snhg14          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Snrk            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Snrpn           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Sntg1           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Snx21           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Spcs2           <dbl> 1.2652227, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Spop            <dbl> 0.0000000, 0.0000000, 0.0000000, 1.7075355, 1.3944114,…
$ Spred2          <dbl> 0.6140827, 1.8422426, 0.0000000, 0.0000000, 0.0000000,…
$ Stk3            <dbl> 1.8062808, 1.8422426, 0.0000000, 0.0000000, 0.0000000,…
$ Stxbp5l         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Taf1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Tafa1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Tbc1d5          <dbl> 1.2652227, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Tbc1d9b         <dbl> 0.6140827, 1.8422426, 1.8633264, 0.5610768, 1.3944114,…
$ Tef             <dbl> 0.0000000, 0.0000000, 0.0000000, 1.7075355, 0.9227897,…
$ Tenm2           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Tenm4           <dbl> 2.052030, 1.842243, 2.215688, 2.050660, 2.954681, 0.95…
$ Thra            <dbl> 1.2652227, 0.0000000, 0.0000000, 1.1810141, 1.9551815,…
$ Thrsp           <dbl> 0.9917400, 0.0000000, 1.3144143, 1.8354431, 0.0000000,…
$ Timp2           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Tmem106b        <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Tmem245         <dbl> 0.6140827, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Tmsb4x          <dbl> 0.0000000, 3.1020138, 0.0000000, 2.3779952, 0.9227897,…
$ Tmx4            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Tnr             <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Tom1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Tsix            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Tspan13         <dbl> 0.00000, 0.00000, 0.00000, 0.00000, 0.00000, 0.00000, …
$ Ttc3            <dbl> 0.9917400, 1.8422426, 1.3144143, 1.3888498, 0.9227897,…
$ Ube2l3          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 1.3944114,…
$ Ube2r2          <dbl> 0.0000000, 1.8422426, 1.3144143, 0.0000000, 0.9227897,…
$ Vps13d          <dbl> 1.2652227, 0.0000000, 0.0000000, 1.1810141, 1.7135998,…
$ Vps35l          <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Vwa8            <dbl> 0.9917400, 1.8422426, 1.3144143, 1.5608344, 0.9227897,…
$ Wasf3           <dbl> 0.9917400, 1.8422426, 1.8633264, 1.1810141, 1.7135998,…
$ Wdr26           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Ywhae           <dbl> 1.4797489, 1.8422426, 0.0000000, 0.9183356, 0.9227897,…
$ Zfp644          <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 0.0000000,…
$ Zwint           <dbl> 0.0000000, 2.4528438, 0.0000000, 0.0000000, 0.9227897,…
$ Nap1l5          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Ahi1            <dbl> 0.6140827, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Nrgn            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Kcnq3           <dbl> 0.6140827, 0.0000000, 2.4757213, 2.0506598, 0.0000000,…
$ Hap1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Calm2           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Slc24a3         <dbl> 1.6562840, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Ncald           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Map1b           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ `6330403K07Rik` <dbl> 0.000000, 2.829207, 0.000000, 0.000000, 0.000000, 0.00…
$ Vsnl1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ `4930447C04Rik` <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Slc8a1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Prkce           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Prkacb          <dbl> 1.4797489, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Gabrg3          <dbl> 1.8062808, 0.0000000, 1.8633264, 1.1810141, 0.0000000,…
$ Efna5           <dbl> 1.2652227, 1.8422426, 0.0000000, 0.9183356, 0.0000000,…
$ Npas2           <dbl> 1.4797489, 1.8422426, 1.3144143, 0.0000000, 1.7135998,…
$ Agbl4           <dbl> 2.1554352, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Myo16           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Zfhx4           <dbl> 1.2652227, 0.0000000, 0.0000000, 2.1430719, 1.9551815,…
$ Antxr1          <dbl> 1.2652227, 0.0000000, 1.3144143, 1.3888498, 0.0000000,…
$ Cacna1d         <dbl> 1.2652227, 0.0000000, 0.0000000, 1.3888498, 0.9227897,…
$ Atp2b2          <dbl> 1.4797489, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Adamts20        <dbl> 0.9917400, 0.0000000, 0.0000000, 1.1810141, 1.7135998,…
$ Med12l          <dbl> 1.4797489, 0.0000000, 1.3144143, 1.7075355, 0.9227897,…
$ Lrrc7           <dbl> 0.6140827, 2.4528438, 1.3144143, 0.5610768, 0.9227897,…
$ Kcnq1ot1        <dbl> 0.6140827, 0.0000000, 1.3144143, 1.1810141, 1.9551815,…
$ `6030443J06Rik` <dbl> 0.6140827, 0.0000000, 1.3144143, 0.9183356, 0.0000000,…
$ Rbfox2          <dbl> 0.0000000, 2.4528438, 0.0000000, 0.0000000, 1.3944114,…
$ Gm33680         <dbl> 1.2652227, 1.8422426, 0.0000000, 1.1810141, 0.9227897,…
$ Fgf12           <dbl> 1.2652227, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Eif2s3y         <dbl> 0.9917400, 0.0000000, 1.3144143, 0.5610768, 0.0000000,…
$ A230057D06Rik   <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 1.7135998,…
$ Mbp             <dbl> 0.000000, 5.733403, 1.863326, 0.000000, 2.149609, 0.00…
$ Snhg11          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Nrg3            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Lrrtm4          <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Lingo2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Cntn5           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Sgcz            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Cntnap2         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Syt1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Opcml           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Meg3            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ March1          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Spock1          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Tenm1           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Cdh18           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Cntnap5a        <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Unc5d           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Lrfn5           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Anks1b          <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Rims1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Grm5            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Usp29           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Xkr4            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ A230006K03Rik   <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gm26871         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Cacna2d1        <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Prkg1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Brinp1          <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.95…
$ Rian            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Grin1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Celf4           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Atp1a3          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Ppfia2          <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Galntl6         <dbl> 0.00000, 0.00000, 0.00000, 0.00000, 0.00000, 0.00000, …
$ Scg2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Unc5c           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Tmem59l         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Hmgcs1          <dbl> 1.4797489, 0.0000000, 0.0000000, 1.3888498, 0.9227897,…
$ Zswim6          <dbl> 0.0000000, 2.4528438, 0.0000000, 0.0000000, 0.9227897,…
$ Sept4           <dbl> 0.6140827, 2.4528438, 0.0000000, 0.0000000, 0.0000000,…
$ Irak2           <dbl> 0.9917400, 1.8422426, 1.3144143, 0.5610768, 0.9227897,…
$ Ddit4           <dbl> 0.0000000, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Arhgap31        <dbl> 0.0000000, 1.8422426, 0.0000000, 0.0000000, 0.0000000,…
$ Zbtb16          <dbl> 0.9917400, 0.0000000, 1.3144143, 2.0506598, 0.0000000,…
$ Anln            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Dab1            <dbl> 1.6562840, 0.0000000, 1.8633264, 1.9488301, 0.0000000,…
$ Tmem100         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ B2m             <dbl> 0.9917400, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Glmp            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Avp             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Resp18          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Oxt             <dbl> 0.000000, 4.322137, 0.000000, 0.000000, 0.000000, 0.00…
$ Stmn1           <dbl> 0.000000, 2.452844, 0.000000, 0.000000, 0.000000, 0.00…
$ Stmn3           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Bc1             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Bex2            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Tmsb10          <dbl> 0.000000, 1.842243, 0.000000, 0.000000, 0.000000, 0.00…
$ Ywhah           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gm35188         <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Gm26917         <dbl> 0.9917400, 2.8292067, 1.8633264, 0.9183356, 0.9227897,…
$ Pcp4            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Uchl1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Bex3            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Pgrmc1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Atpif1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Hsp90aa1        <dbl> 0.0000000, 0.0000000, 0.0000000, 1.7075355, 0.0000000,…
$ `1700030F04Rik` <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Rpl22l1         <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ `5330438D12Rik` <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Fkbp3           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Plp1            <dbl> 0.0000000, 1.8422426, 0.0000000, 0.0000000, 0.9227897,…
$ Sgcd            <dbl> 0.0000000, 0.0000000, 0.0000000, 1.8354431, 0.0000000,…
$ Gm47283         <dbl> 0.0000000, 1.8422426, 1.3144143, 0.0000000, 0.0000000,…
$ Snap47          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Rtl8a           <dbl> 0.6140827, 2.4528438, 0.0000000, 0.5610768, 0.0000000,…
$ Ssbp4           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Gm15738         <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Mtch1           <dbl> 0.0000000, 0.0000000, 1.8633264, 0.5610768, 0.0000000,…
$ Mrfap1          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Syn3            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Aldh1a1         <dbl> 1.4797489, 0.0000000, 1.3144143, 0.5610768, 0.9227897,…
$ Nrp1            <dbl> 1.6562840, 0.0000000, 0.0000000, 1.1810141, 1.3944114,…
$ Tmem229a        <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 1.3944114,…
$ Pou3f3          <dbl> 1.2652227, 0.0000000, 1.8633264, 0.9183356, 0.9227897,…
$ Setbp1          <dbl> 0.9917400, 0.0000000, 1.8633264, 1.1810141, 0.0000000,…
$ Kmt2a           <dbl> 1.4797489, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Aff3            <dbl> 0.9917400, 0.0000000, 0.0000000, 1.8354431, 1.7135998,…
$ Hdac9           <dbl> 0.0000000, 1.8422426, 0.0000000, 1.1810141, 0.9227897,…
$ Ncoa2           <dbl> 0.0000000, 0.0000000, 0.0000000, 1.8354431, 0.9227897,…
$ Gli2            <dbl> 0.9917400, 0.0000000, 2.2156876, 1.3888498, 0.9227897,…
$ Herc1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Arid1b          <dbl> 1.6562840, 1.8422426, 1.8633264, 1.3888498, 1.3944114,…
$ Prdm16          <dbl> 1.4797489, 0.0000000, 0.0000000, 1.3888498, 1.3944114,…
$ Ldb2            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 1.3944114,…
$ Nfkb1           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Ssbp3           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Zfp148          <dbl> 1.2652227, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Mdm4            <dbl> 0.0000000, 0.0000000, 0.0000000, 1.7075355, 0.9227897,…
$ Bptf            <dbl> 0.9917400, 0.0000000, 1.3144143, 1.7075355, 0.0000000,…
$ Bach2           <dbl> 0.9917400, 0.0000000, 1.3144143, 1.3888498, 1.7135998,…
$ Rb1             <dbl> 0.6140827, 0.0000000, 1.3144143, 0.0000000, 1.9551815,…
$ Rreb1           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 1.3944114,…
$ Ppp1r12b        <dbl> 0.6140827, 0.0000000, 0.0000000, 1.3888498, 0.0000000,…
$ Dnmt3a          <dbl> 0.0000000, 0.0000000, 2.4757213, 0.5610768, 1.3944114,…
$ Gria3           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gabra1          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Maged1          <dbl> 0.6140827, 0.0000000, 0.0000000, 0.9183356, 0.9227897,…
$ Purb            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Chgb            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Dnm1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Bin1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Npm1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Nr2f2           <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Mfn1            <dbl> 1.2652227, 0.0000000, 1.3144143, 0.0000000, 0.9227897,…
$ Mfn2            <dbl> 0.0000000, 1.8422426, 0.0000000, 0.0000000, 0.0000000,…
$ Opa1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Dnm1l           <dbl> 1.2652227, 0.0000000, 1.8633264, 0.0000000, 1.3944114,…
$ Mff             <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Ppargc1a        <dbl> 0.9917400, 0.0000000, 0.0000000, 0.9183356, 0.0000000,…
$ Ppargc1b        <dbl> 0.0000000, 0.0000000, 1.3144143, 0.5610768, 0.0000000,…
$ Tfam            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Sod2            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Prdx3           <dbl> 0.0000000, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Slc25a1         <dbl> 0.6140827, 0.0000000, 1.3144143, 0.5610768, 0.0000000,…
$ Slc25a4         <dbl> 0.6140827, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Slc25a5         <dbl> 0.6140827, 0.0000000, 1.3144143, 1.3888498, 1.3944114,…
$ Uqcrc1          <dbl> 0.6140827, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Uqcrc2          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.9183356, 1.3944114,…
$ Cox4i1          <dbl> 0.000000, 1.842243, 1.314414, 1.560834, 1.955181, 0.95…
$ Cox4i2          <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Atp5a1          <dbl> 0.6140827, 0.0000000, 1.3144143, 1.1810141, 0.9227897,…
$ Atp5b           <dbl> 0.9917400, 0.0000000, 0.0000000, 1.3888498, 0.9227897,…
$ Bak1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Bax             <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Bcl2            <dbl> 2.2491428, 2.4528438, 0.0000000, 1.7075355, 2.1496089,…
$ Bcl2l1          <dbl> 0.6140827, 0.0000000, 0.0000000, 1.5608344, 0.0000000,…
$ Bnip3           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Bnip3l          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.9227897,…
$ Casp9           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Cybb            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Gpx1            <dbl> 0.0000000, 1.8422426, 0.0000000, 1.1810141, 0.0000000,…
$ Gpx4            <dbl> 0.9917400, 2.4528438, 0.0000000, 0.0000000, 1.7135998,…
$ Mapk14          <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Nfe2l2          <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Nox4            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Polg            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Polg2           <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Pink1           <dbl> 0.0000000, 1.8422426, 0.0000000, 0.5610768, 0.9227897,…
$ Aifm1           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Ogg1            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Mutyh           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Sod1            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Sod3            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Ucp1            <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Ucp2            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Ucp3            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Klb             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Bdh1            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Bdh2            <dbl> 1.4797489, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Hmgcs2          <dbl> 0.000000, 0.000000, 0.000000, 1.388850, 0.000000, 1.99…
$ Slc16a1         <dbl> 0.9917400, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Slc16a7         <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Slc2a1          <dbl> 0.0000000, 0.0000000, 0.0000000, 1.1810141, 0.0000000,…
$ Slc2a3          <dbl> 0.000000, 0.000000, 1.314414, 0.000000, 0.000000, 0.00…
$ Gck             <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Pfkp            <dbl> 1.4797489, 1.8422426, 1.3144143, 0.0000000, 1.7135998,…
$ Pkm             <dbl> 0.0000000, 0.0000000, 1.3144143, 0.9183356, 0.0000000,…
$ Pdha1           <dbl> 0.0000000, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Pdk1            <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Pdk2            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Pdk3            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pdk4            <dbl> 0.000000, 0.000000, 0.000000, 0.000000, 0.000000, 0.00…
$ Acox1           <dbl> 0.6140827, 1.8422426, 0.0000000, 0.5610768, 0.0000000,…
$ Cpt1a           <dbl> 0.9917400, 1.8422426, 1.3144143, 0.5610768, 0.9227897,…
$ Cpt1b           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Cpt1c           <dbl> 0.6140827, 0.0000000, 1.3144143, 0.9183356, 0.9227897,…
$ Cpt2            <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Acsl1           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Acsl3           <dbl> 2.978339, 0.000000, 2.475721, 2.508654, 2.782725, 2.83…
$ Acsl4           <dbl> 0.9917400, 0.0000000, 0.0000000, 0.5610768, 0.0000000,…
$ Acsl5           <dbl> 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, …
$ Acsl6           <dbl> 2.1554352, 1.8422426, 0.0000000, 2.3056508, 1.9551815,…
$ Acly            <dbl> 1.2652227, 1.8422426, 0.0000000, 0.5610768, 0.9227897,…
$ Fasn            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 0.9227897,…
$ Scd2            <dbl> 3.306402, 1.842243, 2.681901, 3.507358, 3.229254, 3.44…
$ Acaa2           <dbl> 0.0000000, 0.0000000, 1.3144143, 0.0000000, 0.0000000,…
$ Eno1            <dbl> 0.6140827, 0.0000000, 0.0000000, 0.5610768, 1.3944114,…
$ Hadhb           <dbl> 0.0000000, 0.0000000, 0.0000000, 0.0000000, 0.0000000,…
$ Pygb            <dbl> 1.936686, 0.000000, 1.863326, 2.143072, 1.394411, 0.95…
Code 
# for (x in selected_genes) {
#   df.two.group.unpaired <-
#       df.test %>%
#       select(
#           x,
#           expbtch,
#           cell_name
#           )

#   two.group.unpaired <-
#       df.two.group.unpaired |>
#       dabest(
#           x = expbtch,
#           y = x,
#           idx = c(
#               "control",
#               "hfd_05"
#               ),
#           paired = FALSE,
#           id.column = cell_name
#           )

#   two.group.unpaired.meandiff <- mean_diff(two.group.unpaired)
#   two.group.unpaired.meandiff
#   plot(two.group.unpaired.meandiff)
# }

MA-plot 5 days of HFD

Code 
target <- "control"
geneLogAverage <- rowMeans(GetAssayData(subset(srt, idents = target), "data", "RNA"))
all_markers_genes$logA <- geneLogAverage[all_markers_genes$gene]


plt_genes <- all_markers_genes %>%
  filter(cluster == target) %>%
  mutate(gene = if_else(condition = (avg_log2FC >= 0.2 | avg_log2FC <= -0.2) & (pct_diff >= 0.015 | pct_diff <= -0.015),
    gene, ""
  ))

subselected_genes <- c(
  "Insr", "Meis1", "Igf1r", "Nrf1", "Prlr", "Camk1d", "Lars2", "Cacna2d3", # 0 ARC
  "Dcn", "Ptgds", "Nupr1", "Igfbp2", "Nrarp", "Ctnna2", "Ldlr", "Mmp14", # 1 LHA
  "Nkx6-2", "Cirbp", "Selenop", # 2 MnPO
  "Foxg1", "Crym", "Sema3c", "Meis2", "Dbp", # 3 POA
  "Egr1", "Ttr", "Btg2", "Mbnl3", "Pgf", "Irs4", "Gpr101", "Nr3c2", "Agtr1", # 4 PVN
  "Rfx4", "Dbx2", "Prokr2", "Cebpb", "Zic1", "Zic2", "Zic5", "Ccn1", "Gata4", "Klf4", "Klf10", # 5 SCN
  "Tbx3", "Fis1", "Ndn", "Psmc5", "Drap1", "Pcsk1n", "Rtn1", # 6 VMH
  "Emx2", "Sgip1", "Myoc", "Hivep3", "Dcc", "Ralyl", "Ltbp1", "Egfem1", # 7 VPH
  "Klf4", "Atf3", "Nrg1", "Cdk8", "Grpr", "Qrfpr", "Hcrtr1", "Hcrtr2", "Tacr1", "Trhr", "Tshr",
  "Gfap", "Fgf1", "Fgfr3", "Hepacam", "Hif1", "Htra1", "Lxn", "Ndrg2", "Ntn1", "Nfia", "Slit2", "Aqp4", "S100a1", "S100a6", "S100b", "Slc1a2", "Slc1a3", "Slc38a1", "Vegfa", "Fos", "Fosb", "Jun", "Junb", "Jund", "Ier2", "Socs3", "Pde10a", "Fbln5", "Otp", "Nr4a1", "Six6", "Emx2", "Myt1l", "Adcyap1r1", "Ghr", "Ntrk2", "Npy1r", "Gria1", "Gria2", "Grin2b", "Grin3a", "Grm3", "Grm7", "Gabrb1", "Gabbr1", "Gabbr2", "Rfx3", "Nr5a1", "Nkx2-1", "Otx2", "Bclaf1", "Foxo3", "Dlx1", "Lrrc6", "Peg3", "Elavl2", "Isl1", "Zfp36", "Otx1", "Pitx2"
)

plt_genes_const <- all_markers_genes %>%
  filter(cluster == target) %>%
  mutate(gene = if_else(condition = gene %in% subselected_genes & (avg_log2FC < 0.2 & avg_log2FC > -0.2) & (pct_diff < 0.015 & pct_diff > -0.015),
    gene, ""
  ))

my_pal <- function(range = c(1, 6)) {
  force(range)
  function(x) scales::rescale(x, to = range, from = c(0, 1))
}

plt_genes %>%
  ggplot(
    .,
    aes(
      x = logA,
      y = avg_log2FC,
      label = gene,
      size = pct.1
    )
  ) +
  geom_point(alpha = 0.7, colour = if_else(condition = (plt_genes$avg_log2FC >= 0.2 | plt_genes$avg_log2FC <= -0.2) & (plt_genes$pct_diff >= 0.015 | plt_genes$pct_diff <= -0.015), "orangered", "grey50")) +
  continuous_scale(
    aesthetics = c("size", "point.size"), scale_name = "size",
    palette = my_pal(c(2, 9)),
    guide = guide_legend(override.aes = list(label = "")) # hide "a" in legend
  ) +
  ggrepel::geom_text_repel(
    aes(point.size = pct.1), # data point size
    size = 6, # font size in the text labels
    point.padding = 0, # additional padding around each point
    min.segment.length = 0, # draw all line segments
    max.time = 2, max.iter = 1e6, # stop after 1 second, or after 100,000 iterations
    seed = reseed,
    max.overlaps = Inf,
    box.padding = 0.5
  ) +
  theme_light()

Volcano-plot 5 days of HFD

Code 
plt_genes %>%
  ggplot(
    .,
    aes(
      x = avg_log2FC,
      y = 1 / p_val_adj,
      col = logA,
      label = gene,
      size = pct.1
    )
  ) +
  scale_y_log10() +
  geom_point(alpha = 0.7, colour = if_else(condition = plt_genes$avg_log2FC < 0.2 & plt_genes$avg_log2FC > -0.2, "grey50", "orangered")) +
  continuous_scale(
    aesthetics = c("size", "point.size"), scale_name = "size",
    palette = my_pal(c(2, 9)),
    guide = guide_legend(override.aes = list(label = "")) # hide "a" in legend
  ) +
  ggrepel::geom_text_repel(
    aes(point.size = pct.1), # data point size
    size = 6, # font size in the text labels
    point.padding = 0, # additional padding around each point
    min.segment.length = 0, # draw all line segments
    max.time = 2, max.iter = 1e6, # stop after 1 second, or after 100,000 iterations
    seed = reseed,
    max.overlaps = Inf,
    box.padding = 0.5
  ) +
  theme_light()

Plot effect size to sample size delta 5 days of HFD

Code 
plt_genes %>%
  ggplot(
    .,
    aes(
      x = avg_log2FC,
      y = pct_diff,
      col = -log10(p_val_adj),
      label = gene,
      size = pct.1
    )
  ) +
  xlim(c(-1.5, 1.5)) +
  ylim(c(-0.2, 0.2)) +
  geom_vline(
    xintercept = c(-0.2, 0.2),
    linetype = "dashed",
    colour = "grey80",
    size = 0.3
  ) +
  geom_hline(
    yintercept = c(-0.015, 0.015),
    linetype = "dashed",
    colour = "grey80",
    size = 0.3
  ) +
  geom_vline(
    xintercept = 0,
    linetype = "solid",
    colour = "black",
    size = 0.5
  ) +
  geom_hline(
    yintercept = 0,
    linetype = "solid",
    colour = "black",
    size = 0.5
  ) +
  geom_point(alpha = 0.7, colour = if_else(condition = (plt_genes$avg_log2FC >= 0.2 | plt_genes$avg_log2FC <= -0.2) & (plt_genes$pct_diff >= 0.015 | plt_genes$pct_diff <= -0.015), "orangered", "grey50")) +
  continuous_scale(
    aesthetics = c("size", "point.size"), scale_name = "size",
    palette = my_pal(c(2, 9)),
    guide = guide_legend(override.aes = list(label = "")) # hide "a" in legend
  ) +
  ggrepel::geom_text_repel(
    aes(point.size = pct.1), # data point size
    size = 6, # font size in the text labels
    point.padding = 0, # additional padding around each point
    min.segment.length = 0, # draw all line segments
    max.time = 2, max.iter = 1e6, # stop after 1 second, or after 100,000 iterations
    seed = reseed,
    max.overlaps = Inf,
    box.padding = 0.5
  ) +
  theme_classic()

Code 
plt_genes_const %>%
  ggplot(
    .,
    aes(
      x = avg_log2FC,
      y = pct_diff,
      col = -log10(p_val_adj),
      label = gene,
      size = pct.1
    )
  ) +
  xlim(c(-0.25, 0.25)) +
  ylim(c(-0.02, 0.02)) +
  geom_vline(
    xintercept = c(-0.2, 0.2),
    linetype = "dashed",
    colour = "grey80",
    size = 0.3
  ) +
  geom_hline(
    yintercept = c(-0.015, 0.015),
    linetype = "dashed",
    colour = "grey80",
    size = 0.3
  ) +
  geom_vline(
    xintercept = 0,
    linetype = "solid",
    colour = "black",
    size = 0.5
  ) +
  geom_hline(
    yintercept = 0,
    linetype = "solid",
    colour = "black",
    size = 0.5
  ) +
  geom_point(alpha = 0.7, colour = if_else(condition = (plt_genes$avg_log2FC < 0.2 & plt_genes$avg_log2FC > -0.2) &
    (plt_genes$pct_diff < 0.015 & plt_genes$pct_diff > -0.015), "navy", "grey50")) +
  continuous_scale(
    aesthetics = c("size", "point.size"), scale_name = "size",
    palette = my_pal(c(2, 9)),
    guide = guide_legend(override.aes = list(label = "")) # hide "a" in legend
  ) +
  ggrepel::geom_text_repel(
    aes(point.size = pct.1), # data point size
    size = 6, # font size in the text labels
    point.padding = 0, # additional padding around each point
    min.segment.length = 0, # draw all line segments
    max.time = 2, max.iter = 1e6, # stop after 1 second, or after 100,000 iterations
    seed = reseed,
    max.overlaps = Inf,
    box.padding = 0.5
  ) +
  theme_classic()

Code 
plt_genes_const %>%
  ggplot(
    .,
    aes(
      x = pct.1,
      y = pct_diff,
      col = -log10(p_val_adj),
      label = gene,
      size = avg_log2FC
    )
  ) +
  geom_vline(
    xintercept = 0,
    linetype = "solid",
    colour = "black",
    size = 0.5
  ) +
  geom_hline(
    yintercept = 0,
    linetype = "solid",
    colour = "black",
    size = 0.5
  ) +
  geom_point(alpha = 0.7, colour = if_else(condition = (plt_genes$avg_log2FC < 0.2 & plt_genes$avg_log2FC > -0.2) &
    (plt_genes$pct_diff < 0.015 & plt_genes$pct_diff > -0.015), "darkgreen", "grey50")) +
  continuous_scale(
    aesthetics = c("size", "point.size"), scale_name = "size",
    palette = my_pal(c(2, 9)),
    guide = guide_legend(override.aes = list(label = "")) # hide "a" in legend
  ) +
  ggrepel::geom_text_repel(
    aes(point.size = avg_log2FC), # data point size
    size = 6, # font size in the text labels
    point.padding = 0, # additional padding around each point
    min.segment.length = 0, # draw all line segments
    max.time = 2, max.iter = 1e6, # stop after 1 second, or after 100,000 iterations
    seed = reseed,
    max.overlaps = Inf,
    box.padding = 0.5
  ) +
  theme_light()

Session information

Code 
sI <- sessioninfo::session_info()
sI$loadedOnly <- NULL
print(sI, locale = FALSE)
─ Session info ───────────────────────────────────────────────────────────────
 setting  value
 version  R version 4.2.2 (2022-10-31)
 os       Ubuntu 22.04.2 LTS
 system   x86_64, linux-gnu
 ui       X11
 language en_US:en
 collate  en_US.UTF-8
 ctype    en_US.UTF-8
 tz       Etc/UTC
 date     2023-07-26
 pandoc   2.19.2 @ /opt/python/3.8.8/bin/ (via rmarkdown)

─ Packages ───────────────────────────────────────────────────────────────────
 package              * version     date (UTC) lib source
 abind                  1.4-5       2016-07-21 [1] RSPM (R 4.2.0)
 anndata              * 0.7.5.6     2023-03-17 [1] RSPM (R 4.2.0)
 assertthat             0.2.1       2019-03-21 [1] RSPM (R 4.2.0)
 base64enc              0.1-3       2015-07-28 [1] RSPM (R 4.2.0)
 bayestestR             0.13.1      2023-04-30 [1] https://easystats.r-universe.dev (R 4.2.2)
 beeswarm               0.4.0       2021-06-01 [1] RSPM (R 4.2.0)
 Biobase              * 2.58.0      2022-11-01 [1] RSPM (R 4.2.2)
 BiocGenerics         * 0.44.0      2022-11-01 [1] RSPM (R 4.2.2)
 BiocManager            1.30.20     2023-02-24 [1] RSPM (R 4.2.0)
 bit                    4.0.5       2022-11-15 [1] RSPM (R 4.2.0)
 bit64                  4.0.5       2020-08-30 [1] RSPM (R 4.2.0)
 bitops                 1.0-7       2021-04-24 [1] RSPM (R 4.2.0)
 boot                   1.3-28.1    2022-11-22 [1] RSPM (R 4.2.0)
 circlize               0.4.15      2022-05-10 [1] RSPM (R 4.2.0)
 cli                    3.6.1       2023-03-23 [1] RSPM (R 4.2.0)
 cluster                2.1.4       2022-08-22 [1] RSPM (R 4.2.0)
 coda                   0.19-4      2020-09-30 [1] RSPM (R 4.2.0)
 codetools              0.2-19      2023-02-01 [1] RSPM (R 4.2.0)
 colorspace             2.1-0       2023-01-23 [1] RSPM (R 4.2.0)
 concaveman             1.1.0       2020-05-11 [1] RSPM (R 4.2.0)
 correlation            0.8.4       2023-04-30 [1] Github (easystats/correlation@3d5cd1e)
 cowplot              * 1.1.1       2020-12-30 [1] RSPM (R 4.2.0)
 crayon                 1.5.2       2022-09-29 [1] RSPM (R 4.2.0)
 dabestr              * 0.3.0       2023-04-30 [1] Github (ACCLAB/dabestr@8775899)
 data.table             1.14.8      2023-02-17 [1] RSPM (R 4.2.0)
 datawizard             0.7.1       2023-04-03 [1] RSPM (R 4.2.0)
 DelayedArray           0.24.0      2022-11-01 [1] RSPM (R 4.2.2)
 deldir                 1.0-6       2021-10-23 [1] RSPM (R 4.2.0)
 digest                 0.6.31      2022-12-11 [1] RSPM (R 4.2.0)
 dplyr                * 1.1.2       2023-04-20 [1] RSPM (R 4.2.2)
 ellipsis               0.3.2       2021-04-29 [1] RSPM (R 4.2.0)
 emmeans                1.8.5       2023-03-08 [1] RSPM (R 4.2.0)
 entropy                1.3.1       2021-10-02 [1] RSPM (R 4.2.0)
 estimability           1.4.1       2022-08-05 [1] RSPM (R 4.2.0)
 evaluate               0.20        2023-01-17 [1] RSPM (R 4.2.0)
 fansi                  1.0.4       2023-01-22 [1] RSPM (R 4.2.0)
 farver                 2.1.1       2022-07-06 [1] RSPM (R 4.2.0)
 fastmap                1.1.1       2023-02-24 [1] RSPM (R 4.2.0)
 fitdistrplus           1.1-11      2023-04-25 [1] RSPM (R 4.2.2)
 forcats              * 1.0.0       2023-01-29 [1] RSPM (R 4.2.0)
 future               * 1.32.0      2023-03-07 [1] RSPM (R 4.2.0)
 future.apply           1.10.0      2022-11-05 [1] RSPM (R 4.2.0)
 generics               0.1.3       2022-07-05 [1] RSPM (R 4.2.0)
 GenomeInfoDb         * 1.34.9      2023-02-02 [1] RSPM (R 4.2.2)
 GenomeInfoDbData       1.2.9       2023-04-30 [1] RSPM (R 4.2.2)
 GenomicRanges        * 1.50.2      2022-12-16 [1] RSPM (R 4.2.2)
 ggbeeswarm             0.7.2       2023-04-30 [1] Github (eclarke/ggbeeswarm@3cf58a9)
 ggforce                0.4.1.9000  2023-04-30 [1] Github (thomasp85/ggforce@9be635c)
 ggmin                  0.0.0.9000  2023-04-30 [1] Github (sjessa/ggmin@8ada274)
 ggplot2              * 3.4.2       2023-04-03 [1] RSPM (R 4.2.0)
 ggprism                1.0.4       2023-04-30 [1] Github (csdaw/ggprism@0e411f4)
 ggrastr                1.0.1       2023-04-30 [1] Github (VPetukhov/ggrastr@7aed9af)
 ggrepel                0.9.2.9999  2023-04-30 [1] Github (slowkow/ggrepel@fe3b5c3)
 ggridges               0.5.4       2022-09-26 [1] RSPM (R 4.2.0)
 ggstatsplot          * 0.11.1.9000 2023-04-30 [1] Github (IndrajeetPatil/ggstatsplot@befe812)
 GlobalOptions          0.1.2       2020-06-10 [1] RSPM (R 4.2.0)
 globals                0.16.2      2022-11-21 [1] RSPM (R 4.2.0)
 glue                   1.6.2       2022-02-24 [1] RSPM (R 4.2.0)
 goftest                1.2-3       2021-10-07 [1] RSPM (R 4.2.0)
 gridExtra              2.3         2017-09-09 [1] RSPM (R 4.2.0)
 gtable                 0.3.3       2023-03-21 [1] RSPM (R 4.2.0)
 hdf5r                  1.3.8       2023-01-21 [1] RSPM (R 4.2.2)
 here                 * 1.0.1       2020-12-13 [1] RSPM (R 4.2.0)
 hexbin                 1.28.3      2023-03-21 [1] RSPM (R 4.2.0)
 hms                    1.1.3       2023-03-21 [1] RSPM (R 4.2.0)
 htmltools              0.5.5       2023-03-23 [1] RSPM (R 4.2.0)
 htmlwidgets            1.6.2       2023-03-17 [1] RSPM (R 4.2.0)
 httpuv                 1.6.9       2023-02-14 [1] RSPM (R 4.2.0)
 httr                   1.4.5       2023-02-24 [1] RSPM (R 4.2.0)
 ica                    1.0-3       2022-07-08 [1] RSPM (R 4.2.0)
 igraph                 1.4.1       2023-02-24 [1] RSPM (R 4.2.0)
 insight                0.19.1      2023-03-18 [1] RSPM (R 4.2.0)
 IRanges              * 2.32.0      2022-11-01 [1] RSPM (R 4.2.2)
 irlba                  2.3.5.1     2022-10-03 [1] RSPM (R 4.2.0)
 janitor                2.2.0.9000  2023-04-30 [1] Github (sfirke/janitor@d64c8bb)
 jsonlite               1.8.4       2022-12-06 [1] RSPM (R 4.2.0)
 KernSmooth             2.23-20     2021-05-03 [1] RSPM (R 4.2.0)
 knitr                  1.42        2023-01-25 [1] RSPM (R 4.2.0)
 labeling               0.4.2       2020-10-20 [1] RSPM (R 4.2.0)
 later                  1.3.0       2021-08-18 [1] RSPM (R 4.2.0)
 lattice                0.21-8      2023-04-05 [1] RSPM (R 4.2.0)
 lazyeval               0.2.2       2019-03-15 [1] RSPM (R 4.2.0)
 leiden                 0.4.3       2022-09-10 [1] RSPM (R 4.2.0)
 lifecycle              1.0.3       2022-10-07 [1] RSPM (R 4.2.0)
 listenv                0.9.0       2022-12-16 [1] RSPM (R 4.2.0)
 lmtest                 0.9-40      2022-03-21 [1] RSPM (R 4.2.0)
 lubridate            * 1.9.2       2023-02-10 [1] RSPM (R 4.2.0)
 magrittr             * 2.0.3       2022-03-30 [1] RSPM (R 4.2.0)
 MASS                   7.3-58.1    2022-08-03 [1] CRAN (R 4.2.2)
 Matrix                 1.5-4       2023-04-04 [1] RSPM (R 4.2.0)
 MatrixGenerics       * 1.10.0      2022-11-01 [1] RSPM (R 4.2.2)
 matrixStats          * 0.63.0      2022-11-18 [1] RSPM (R 4.2.0)
 mime                   0.12        2021-09-28 [1] RSPM (R 4.2.0)
 miniUI                 0.1.1.1     2018-05-18 [1] RSPM (R 4.2.0)
 multcomp               1.4-23      2023-03-09 [1] RSPM (R 4.2.0)
 munsell                0.5.0       2018-06-12 [1] RSPM (R 4.2.0)
 mvtnorm                1.1-3       2021-10-08 [1] RSPM (R 4.2.0)
 nlme                   3.1-162     2023-01-31 [1] RSPM (R 4.2.0)
 paletteer              1.5.0       2022-10-19 [1] RSPM (R 4.2.0)
 parallelly             1.35.0      2023-03-23 [1] RSPM (R 4.2.0)
 parameters             0.20.3      2023-04-05 [1] RSPM (R 4.2.0)
 patchwork            * 1.1.2.9000  2023-04-30 [1] Github (thomasp85/patchwork@c14c960)
 pbapply                1.7-0       2023-01-13 [1] RSPM (R 4.2.0)
 pillar                 1.9.0       2023-03-22 [1] RSPM (R 4.2.0)
 pkgconfig              2.0.3       2019-09-22 [1] RSPM (R 4.2.0)
 plotly                 4.10.1      2022-11-07 [1] RSPM (R 4.2.0)
 plyr                   1.8.8       2022-11-11 [1] RSPM (R 4.2.0)
 png                    0.1-8       2022-11-29 [1] RSPM (R 4.2.0)
 polyclip               1.10-4      2022-10-20 [1] RSPM (R 4.2.0)
 progressr              0.13.0      2023-01-10 [1] RSPM (R 4.2.0)
 promises               1.2.0.1     2021-02-11 [1] RSPM (R 4.2.0)
 purrr                * 1.0.1       2023-01-10 [1] RSPM (R 4.2.0)
 R.methodsS3            1.8.2       2022-06-13 [1] RSPM (R 4.2.0)
 R.oo                   1.25.0      2022-06-12 [1] RSPM (R 4.2.0)
 R.utils                2.12.2      2022-11-11 [1] RSPM (R 4.2.0)
 R6                     2.5.1       2021-08-19 [1] RSPM (R 4.2.0)
 RANN                   2.6.1       2019-01-08 [1] RSPM (R 4.2.0)
 RColorBrewer         * 1.1-3       2022-04-03 [1] RSPM (R 4.2.0)
 Rcpp                   1.0.10      2023-01-22 [1] RSPM (R 4.2.0)
 RcppAnnoy              0.0.20      2022-10-27 [1] RSPM (R 4.2.0)
 RCurl                  1.98-1.12   2023-03-27 [1] RSPM (R 4.2.0)
 readr                * 2.1.4       2023-02-10 [1] RSPM (R 4.2.0)
 rematch2               2.1.2       2020-05-01 [1] RSPM (R 4.2.0)
 remotes                2.4.2       2021-11-30 [1] RSPM (R 4.2.0)
 repr                   1.1.6       2023-01-26 [1] RSPM (R 4.2.0)
 reshape2               1.4.4       2020-04-09 [1] RSPM (R 4.2.0)
 reticulate           * 1.28-9000   2023-04-30 [1] Github (rstudio/reticulate@442c49f)
 rlang                  1.1.0       2023-03-14 [1] RSPM (R 4.2.0)
 rmarkdown              2.21        2023-03-26 [1] RSPM (R 4.2.0)
 ROCR                   1.0-11      2020-05-02 [1] RSPM (R 4.2.0)
 rprojroot              2.0.3       2022-04-02 [1] RSPM (R 4.2.0)
 rsvd                   1.0.5       2021-04-16 [1] RSPM (R 4.2.0)
 Rtsne                  0.16        2022-04-17 [1] RSPM (R 4.2.0)
 S4Vectors            * 0.36.2      2023-02-26 [1] RSPM (R 4.2.2)
 sandwich               3.0-2       2022-06-15 [1] RSPM (R 4.2.0)
 scales                 1.2.1       2022-08-20 [1] RSPM (R 4.2.0)
 scattermore            0.8         2022-02-14 [1] RSPM (R 4.2.0)
 scCustomize          * 1.1.1       2023-04-30 [1] Github (samuel-marsh/scCustomize@d08268d)
 sceasy               * 0.0.7       2023-04-30 [1] Github (cellgeni/sceasy@0cfc0e3)
 schex                * 1.12.0      2022-11-01 [1] RSPM (R 4.2.2)
 sctransform            0.3.5       2022-09-21 [1] RSPM (R 4.2.0)
 sessioninfo            1.2.2       2021-12-06 [1] RSPM (R 4.2.0)
 Seurat               * 4.3.0       2022-11-18 [1] RSPM (R 4.2.2)
 SeuratDisk           * 0.0.0.9020  2023-04-30 [1] Github (mojaveazure/seurat-disk@9b89970)
 SeuratObject         * 4.1.3       2022-11-07 [1] RSPM (R 4.2.0)
 SeuratWrappers       * 0.3.1       2023-04-30 [1] Github (satijalab/seurat-wrappers@d28512f)
 shape                  1.4.6       2021-05-19 [1] RSPM (R 4.2.0)
 shiny                * 1.7.4       2022-12-15 [1] RSPM (R 4.2.0)
 SingleCellExperiment * 1.20.1      2023-03-17 [1] RSPM (R 4.2.2)
 skimr                * 2.1.5       2023-04-30 [1] Github (ropensci/skimr@d5126aa)
 snakecase              0.11.0      2019-05-25 [1] RSPM (R 4.2.0)
 sp                     1.6-0       2023-01-19 [1] RSPM (R 4.2.0)
 spatstat.data          3.0-1       2023-03-12 [1] RSPM (R 4.2.0)
 spatstat.explore       3.1-0       2023-03-14 [1] RSPM (R 4.2.0)
 spatstat.geom          3.1-0       2023-03-12 [1] RSPM (R 4.2.0)
 spatstat.random        3.1-4       2023-03-13 [1] RSPM (R 4.2.0)
 spatstat.sparse        3.0-1       2023-03-12 [1] RSPM (R 4.2.0)
 spatstat.utils         3.0-2       2023-03-11 [1] RSPM (R 4.2.0)
 statsExpressions       1.5.0       2023-02-19 [1] RSPM (R 4.2.0)
 stringi                1.7.12      2023-01-11 [1] RSPM (R 4.2.0)
 stringr              * 1.5.0       2022-12-02 [1] RSPM (R 4.2.0)
 SummarizedExperiment * 1.28.0      2022-11-01 [1] RSPM (R 4.2.2)
 survival               3.5-5       2023-03-12 [1] RSPM (R 4.2.0)
 tensor                 1.5         2012-05-05 [1] RSPM (R 4.2.0)
 TH.data                1.1-1       2022-04-26 [1] RSPM (R 4.2.0)
 tibble               * 3.2.1       2023-03-20 [1] RSPM (R 4.2.0)
 tidyr                * 1.3.0       2023-01-24 [1] RSPM (R 4.2.0)
 tidyselect             1.2.0       2022-10-10 [1] RSPM (R 4.2.0)
 tidyverse            * 2.0.0.9000  2023-04-30 [1] Github (tidyverse/tidyverse@8ec2e1f)
 timechange             0.2.0       2023-01-11 [1] RSPM (R 4.2.0)
 tweenr                 2.0.2       2022-09-06 [1] RSPM (R 4.2.0)
 tzdb                   0.3.0       2022-03-28 [1] RSPM (R 4.2.0)
 utf8                   1.2.3       2023-01-31 [1] RSPM (R 4.2.0)
 uwot                   0.1.14      2022-08-22 [1] RSPM (R 4.2.0)
 vctrs                  0.6.2       2023-04-19 [1] RSPM (R 4.2.2)
 vipor                  0.4.5       2017-03-22 [1] RSPM (R 4.2.0)
 viridis              * 0.6.2       2021-10-13 [1] RSPM (R 4.2.0)
 viridisLite          * 0.4.1       2022-08-22 [1] RSPM (R 4.2.0)
 vroom                  1.6.1       2023-01-22 [1] RSPM (R 4.2.0)
 withr                  2.5.0       2022-03-03 [1] RSPM (R 4.2.0)
 xfun                   0.39        2023-04-20 [1] RSPM (R 4.2.2)
 xtable                 1.8-4       2019-04-21 [1] RSPM (R 4.2.0)
 XVector                0.38.0      2022-11-01 [1] RSPM (R 4.2.2)
 yaml                   2.3.7       2023-01-23 [1] RSPM (R 4.2.0)
 zeallot                0.1.0       2018-01-28 [1] RSPM (R 4.2.0)
 zlibbioc               1.44.0      2022-11-01 [1] RSPM (R 4.2.2)
 zoo                    1.8-12      2023-04-13 [1] RSPM (R 4.2.2)

 [1] /opt/R/4.2.2/lib/R/library

─ Python configuration ───────────────────────────────────────────────────────
 python:         /opt/python/3.8.8/bin/python
 libpython:      /opt/python/3.8.8/lib/libpython3.8.so
 pythonhome:     /opt/python/3.8.8:/opt/python/3.8.8
 version:        3.8.8 | packaged by conda-forge | (default, Feb 20 2021, 16:22:27)  [GCC 9.3.0]
 numpy:          /opt/python/3.8.8/lib/python3.8/site-packages/numpy
 numpy_version:  1.23.5
 scanpy:         /opt/python/3.8.8/lib/python3.8/site-packages/scanpy
 
 NOTE: Python version was forced by RETICULATE_PYTHON

──────────────────────────────────────────────────────────────────────────────