library(DT) motifEnrichment_wLogo <- readRDS("../data/motifs/TFenrichment_V2.rds") GO_data <- readRDS("../data/GO_enrichment.rds") library(testisAtlas) load2("../data/cache") load_component_orderings()
print_tsne(22, point_size = 0.5) print_loadings_scores(22) print_gene_list(22) go_volcano_plot(component = "V22N") head(GO_data[["V22N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V22N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(6, point_size = 0.5) print_loadings_scores(6) print_gene_list(6) go_volcano_plot(component = "V6P") head(GO_data[["V6P"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V6P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
Loading appears in a subset of leydig cells, but alot of the top (positive) genes are pseudogenes, and most almost all high cell scores are in Hormad1 KO so maybe a batch / KO specific effect / messed up.
print_tsne(24, point_size = 0.5) print_loadings_scores(24) print_gene_list(24) go_volcano_plot(component = "V24N") head(GO_data[["V24N"]][c(2,7,8,10)], 20) head(GO_data[["V24P"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V24N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
Spermatogonial location, but ribosomal negative genes, and top genes all non-protein coding or mitochondrial:
print_tsne(29, point_size = 0.5) print_loadings_scores(29) print_gene_list(29) go_volcano_plot(component = "V29P") head(GO_data[["V29P"]][c(2,7,8,10)], 20) head(GO_data[["V29N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V25N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
Odd tSNE pattern, cells on outside + blob in center. One set of Hormad1 KO cells have opposite cell loadings to the others so seems unlikely due to the KO of Hormad1 and more due to a batch? - but also high scores in SPG FACS. Highest gene (Gm42418) is lincRNA, mt-Rnr1 & mt-Rnr2 also high.
print_tsne(12, point_size = 0.5) print_loadings_scores(12) print_gene_list(12) go_volcano_plot(component = "V12N") head(GO_data[["V12N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V12N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
Overlaps V30, potentially batch effect as top 15 positive genes only 2 are protein coding, the rest are either lincRNA, antisenseRNA or processes_pseudogene.
print_tsne(28, point_size = 0.5) print_loadings_scores(28) print_gene_list(28) head(GO_data[["V28P"]][c(2,7,8,10)], 20) head(GO_data[["V28N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V28N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
Small number of cells on the outside, cells at spermatogenesis stage in tsne, but negative gene loadings (matching negative cell scores) have no enrichment & a few lincRNAs
print_tsne(36, point_size = 0.5) print_loadings_scores(36) print_gene_list(36) go_volcano_plot(component = "V36P") head(GO_data[["V36P"]][c(2,7,8,10)], 20) head(GO_data[["V36N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V36P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
looks clumpy in tsne, potentially WT batch effect
print_tsne(41, point_size = 0.5) print_loadings_scores(41) print_gene_list(41) go_volcano_plot(component = "V41P") head(GO_data[["V41P"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V41P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(9, point_size = 0.5) print_loadings_scores(9) print_gene_list(9) go_volcano_plot(component = "V9N") head(GO_data[["V9N"]][c(2,7,8,10)], 20) head(GO_data[["V9P"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V9N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(49, point_size = 0.5) print_loadings_scores(49) print_gene_list(49) go_volcano_plot(component = "V49P") head(GO_data[["V49P"]][c(2,7,8,10)], 20) go_volcano_plot(component = "V49N") head(GO_data[["V49N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V49P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(43, point_size = 0.5) print_loadings_scores(43) print_gene_list(43) go_volcano_plot(component = "V43N") head(GO_data[["V43N"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V43N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
Highest in Mlh3? Odd location on tsne.
print_tsne(48, point_size = 0.5) print_loadings_scores(48) print_gene_list(48) go_volcano_plot(component = "V48P") head(GO_data[["V48P"]][c(2,7,8,10)], 20) datatable(motifEnrichment_wLogo[geneSet=="V48P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
A single blood cell? / bad component
print_tsne(1, point_size = 1) print_loadings_scores(1) #print_gene_list(1) #go_volcano_plot(component = "V1P") head(GO_data[["V1P"]][c(2,7,8,10)], 20) #datatable(motifEnrichment_wLogo[geneSet=="V1P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(46, point_size = 1) print_loadings_scores(46) #print_gene_list(46) #go_volcano_plot(component = "V46N") head(GO_data[["V46N"]][c(2,7,8,10)], 20) #datatable(motifEnrichment_wLogo[geneSet=="V46N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(4, point_size = 1) print_loadings_scores(4) #print_gene_list(4) #go_volcano_plot(component = "V4N") head(GO_data[["V4N"]][c(2,7,8,10)], 20) #datatable(motifEnrichment_wLogo[geneSet=="V4N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(8, point_size = 1) print_loadings_scores(8) #print_gene_list(8) #go_volcano_plot(component = "V8N") head(GO_data[["V8N"]][c(2,7,8,10)], 20) #datatable(motifEnrichment_wLogo[geneSet=="V8N",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
print_tsne(14, point_size = 1) print_loadings_scores(14) #print_gene_list(14) #go_volcano_plot(component = "V14P") head(GO_data[["V14P"]][c(2,7,8,10)], 20) #datatable(motifEnrichment_wLogo[geneSet=="V14P",-c("enrichedGenes","geneSet"), with=FALSE][1:40,], escape = FALSE, filter="top", options=list(pageLength=5))
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