BEAM clusters

combined <- list()

for (i in 1:6){
  beam_genelist <- read.table(paste('tables/tables_paper/all_tables/BEAM/heatmap_logFC0.3_ncluster6/genelist_cluster', i, '.tsv', sep=''), sep='\t', header=T)
  beam_genelist['ensembl_gene_id'] <- ids2symbols$ensembl_gene_id[match(beam_genelist$gene_short_name, ids2symbols$gene_symbol)]
  beam_genelist['cluster'] <- i
  
  #add geneinfo
  merged <- merge(beam_genelist, gene_annotations[,c('Gene stable ID', 'Gene type', 'GO term accession', 'GO term name')], by.y='Gene stable ID', by.x='ensembl_gene_id')
  
  #filter for tf's and gene type != protein coding
  filtered <- merged[c(which(c(merged$`GO term name`) %like% 'transcription factor'),
                     which(merged$`GO term definition` %like% 'transcription factor'),
                     which(merged$`Gene type` != 'protein_coding')),]
  
  #filter out duplicate genes
  filtered <- filtered[!duplicated(filtered$gene_short_name),]
  
  combined[[i]] <- filtered
}

combined <- do.call("rbind", combined)

kable(combined[c('gene_short_name', 'qval', 'avgLogFC_State2_State3', 'cluster', 'Gene type', 'GO term accession', 'GO term name')]) %>%
  kable_styling(bootstrap_options = "striped")

#write.table(combined, file='../tables/tables_paper/all_tables/BEAM/heatmap_logFC0.3_ncluster6/genelist_TFs.tsv', sep='\t', quote=F, row.names=F)
#write.table(combined, file='../tables/tables_paper/supplementary_tables/BEAM_logFC0.3_nclusters6/genelist_TFs.tsv', sep='\t', quote=F, row.names=F)

#for (gene in as.vector(combined$gene_short_name)){
#  p <- FeaturePlot(seurobj, features.plot=as.vector(combined$gene_short_name), nCol=2, cols.use=c('gray', 'blue'), no.legend=F, do.return = T)[[gene]]
#  save_plot(paste('../figures/figures_paper/supplementary_figures/tf_analysis/BEAM_logFC0.3_ncluster6_413genes/', gene, '.pdf', sep=''), p, base_width=5, base_height=4)
#}

LogFC > 0

combined_upper_branch <- combined[combined$avgLogFC_State2_State3 > 0,]
combined_lower_branch <- combined[combined$avgLogFC_State2_State3 < 0,]

plots_upper <- FeaturePlot(seurobj, features.plot=as.vector(combined_upper_branch$gene_short_name), nCol=4, cols.use=c('gray', 'blue'), no.legend=F, no.axes=T, do.return=T)

plots_upper_edited <- list()

for (p in names(plots_upper)){
  plots_upper_edited[[p]] <- plots_upper[[p]] + scale_color_gradient(name='Expr.', low='gray', high='blue', guide='colorbar') + theme(legend.title=element_text(size=9), legend.text=element_text(size=9), legend.key.height = unit(0.6, 'cm'), legend.key.width=unit(0.2, 'cm'))
}
grid_upper <- plot_grid(plotlist=plots_upper_edited, ncol=4)

grid_upper

Past versions of unnamed-chunk-9-1.png

#save_plot('figures/figures_paper/supplementary_figures/10_tf-analysis/TFs_upper_branch.pdf', grid_upper, base_height=9.14, base_width=12)
#save_plot('figures/figures_paper/supplementary_figures/10_tf-analysis/TFs_upper_branch.png', grid_upper, base_height=9.14, base_width=12)

plots_lower <- FeaturePlot(seurobj, features.plot=as.vector(combined_lower_branch$gene_short_name), nCol=3, cols.use=c('gray', 'blue'), no.legend=F, no.axes=T, do.return=T)

plots_lower_edited <- list()

for (p in names(plots_lower)){
  plots_lower_edited[[p]] <- plots_lower[[p]] + scale_color_gradient(name='Expr.', low='gray', high='blue', guide='colorbar') + theme(legend.title=element_text(size=9), legend.text=element_text(size=9), legend.key.height = unit(0.6, 'cm'), legend.key.width=unit(0.2, 'cm'))
}
grid_lower <- plot_grid(plotlist=plots_lower_edited, ncol=4)

grid_lower

Past versions of unnamed-chunk-11-1.png

#save_plot('figures/figures_paper/supplementary_figures/10_tf-analysis/TFs_lower_branch.pdf', grid_lower, base_height=16, base_width=12)
#save_plot('figures/figures_paper/supplementary_figures/10_tf-analysis/TFs_lower_branch.png', grid_lower, base_height=16, base_width=12)

Session information

sessionInfo()

R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Storage

Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblas-r0.3.3.so

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] Seurat_2.3.4      Matrix_1.2-17     cowplot_0.9.4     ggplot2_3.1.0    
[5] kableExtra_1.1.0  knitr_1.22        dplyr_0.8.0.1     readr_1.3.1      
[9] data.table_1.12.0

loaded via a namespace (and not attached):
  [1] Rtsne_0.15          colorspace_1.4-1    class_7.3-15       
  [4] modeltools_0.2-22   ggridges_0.5.1      mclust_5.4.3       
  [7] rprojroot_1.3-2     htmlTable_1.13.1    base64enc_0.1-3    
 [10] fs_1.2.7            rstudioapi_0.10     proxy_0.4-23       
 [13] npsurv_0.4-0        bit64_0.9-7         flexmix_2.3-15     
 [16] mvtnorm_1.0-10      xml2_1.2.0          codetools_0.2-16   
 [19] splines_3.5.3       R.methodsS3_1.7.1   lsei_1.2-0         
 [22] robustbase_0.93-4   jsonlite_1.6        Formula_1.2-3      
 [25] workflowr_1.2.0     ica_1.0-2           cluster_2.0.7-1    
 [28] kernlab_0.9-27      png_0.1-7           R.oo_1.22.0        
 [31] compiler_3.5.3      httr_1.4.0          backports_1.1.3    
 [34] assertthat_0.2.1    lazyeval_0.2.2      lars_1.2           
 [37] acepack_1.4.1       htmltools_0.3.6     tools_3.5.3        
 [40] igraph_1.2.4        gtable_0.3.0        glue_1.3.1         
 [43] reshape2_1.4.3      RANN_2.6.1          Rcpp_1.0.1         
 [46] trimcluster_0.1-2.1 gdata_2.18.0        ape_5.3            
 [49] nlme_3.1-137        iterators_1.0.10    fpc_2.1-11.1       
 [52] lmtest_0.9-36       gbRd_0.4-11         xfun_0.5           
 [55] stringr_1.4.0       rvest_0.3.3         irlba_2.3.3        
 [58] gtools_3.8.1        DEoptimR_1.0-8      zoo_1.8-5          
 [61] MASS_7.3-51.1       scales_1.0.0        hms_0.4.2          
 [64] doSNOW_1.0.16       parallel_3.5.3      RColorBrewer_1.1-2 
 [67] yaml_2.2.0          reticulate_1.11.1   pbapply_1.4-0      
 [70] gridExtra_2.3       segmented_0.5-3.0   rpart_4.1-13       
 [73] latticeExtra_0.6-28 stringi_1.4.3       highr_0.8          
 [76] foreach_1.4.4       checkmate_1.9.1     caTools_1.17.1.2   
 [79] bibtex_0.4.2        Rdpack_0.10-1       SDMTools_1.1-221   
 [82] rlang_0.3.2         pkgconfig_2.0.2     dtw_1.20-1         
 [85] prabclus_2.2-7      bitops_1.0-6        evaluate_0.13      
 [88] lattice_0.20-38     ROCR_1.0-7          purrr_0.3.2        
 [91] labeling_0.3        htmlwidgets_1.3     bit_1.1-14         
 [94] tidyselect_0.2.5    plyr_1.8.4          magrittr_1.5       
 [97] R6_2.4.0            snow_0.4-3          gplots_3.0.1.1     
[100] Hmisc_4.2-0         pillar_1.3.1        whisker_0.3-2      
[103] foreign_0.8-71      withr_2.1.2         mixtools_1.1.0     
[106] fitdistrplus_1.0-14 survival_2.43-3     nnet_7.3-12        
[109] tsne_0.1-3          tibble_2.1.1        crayon_1.3.4       
[112] hdf5r_1.1.1         KernSmooth_2.23-15  rmarkdown_1.12     
[115] grid_3.5.3          git2r_0.25.2        metap_1.1          
[118] digest_0.6.18       diptest_0.75-7      webshot_0.5.1      
[121] tidyr_0.8.3         R.utils_2.8.0       stats4_3.5.3       
[124] munsell_0.5.0       viridisLite_0.3.0