Variance Partition on Pseudobulk data
Last updated: 2021-07-05
Checks: 5 2
Knit directory: Embryoid_Body_Pilot_Workflowr/analysis/
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| absolute | relative |
|---|---|
| /project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/Pseudobulk_VarPart.ByCluster.Res0.1.rds | ../output/Pseudobulk_VarPart.ByCluster.Res0.1.rds |
| /project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/pdfs/VarPart_PseudobulkByCluster_res0.1.pdf | ../output/pdfs/VarPart_PseudobulkByCluster_res0.1.pdf |
| /project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/figs/VarPart_PseudobulkByCluster_res0.1.png | ../output/figs/VarPart_PseudobulkByCluster_res0.1.png |
| /project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/figs/VarPart_Pseudobulk_res0.1_MedianExplainedBarPlot.png | ../output/figs/VarPart_Pseudobulk_res0.1_MedianExplainedBarPlot.png |
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library(dplyr)
Attaching package: 'dplyr'The following objects are masked from 'package:stats':
filter, lagThe following objects are masked from 'package:base':
intersect, setdiff, setequal, unionlibrary(limma)
library(edgeR)
library(variancePartition)Loading required package: ggplot2Loading required package: foreachLoading required package: scalesLoading required package: BiobaseLoading required package: BiocGenericsLoading required package: parallel
Attaching package: 'BiocGenerics'The following objects are masked from 'package:parallel':
clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
clusterExport, clusterMap, parApply, parCapply, parLapply,
parLapplyLB, parRapply, parSapply, parSapplyLBThe following object is masked from 'package:limma':
plotMAThe following objects are masked from 'package:dplyr':
combine, intersect, setdiff, unionThe following objects are masked from 'package:stats':
IQR, mad, sd, var, xtabsThe following objects are masked from 'package:base':
Filter, Find, Map, Position, Reduce, anyDuplicated, append,
as.data.frame, basename, cbind, colnames, dirname, do.call,
duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
tapply, union, unique, unsplit, which, which.max, which.minWelcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'variancePartition'The following object is masked from 'package:limma':
classifyTestsFlibrary(ggplot2)choose parameters (integration type, clustering res, min pct threshold)
f<- 'Harmony.Batchindividual'
pct<-0.2
res<- 'SCT_snn_res.0.1'path<- here::here("output/DGELists/")
submerged<- readRDS(paste0(path,"Pseudobulk_dge_",f, "_", res,"_minPCT",pct,".rds"))clusters<- as.vector(sort(unique(submerged$samples[,"cluster"])))
varpart.list<- NULL
voom.plots<- NULL
for(i in 1:length(clusters)){
cluster<- clusters[i]
sub<- submerged[, submerged$samples[,"cluster"] == cluster]
#remove ribosomal genes
genes.ribo <- grep('^RP',rownames(sub),value=T)
genes.no.ribo <- rownames(sub)[which(!(rownames(sub) %in% genes.ribo))]
sub$counts <- sub$counts[which(rownames(sub$counts) %in% genes.no.ribo),]
#filter to expressed genes
genes.keep<- rownames(sub)[rowSums(sub$counts)>0]
sub<- sub[rownames(sub$counts) %in% genes.keep,]
#CalcNormFactors
sub<- calcNormFactors(sub, method="TMM")
#specify design matrix
design<- model.matrix(~sub$samples$batch+sub$samples$ind)
#voom
v<- voom(sub, design, plot=T)
voom.plots[[cluster]]<- v
#form
form<- ~ (1|batch) + (1|ind)
#run variance partition
varpart<- suppressWarnings(fitExtractVarPartModel(v, form, sub$samples, useWeights=TRUE, quiet=TRUE, showWarnings = FALSE))
#store varpart results
varpart.list[[cluster]]<- varpart
}
voom.plotssaveRDS(varpart.list, "/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/Pseudobulk_VarPart.ByCluster.Res0.1.rds")varpart.list<- readRDS("/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/Pseudobulk_VarPart.ByCluster.Res0.1.rds")vp.bar.list<- NULL
for (i in 1:length(varpart.list)){
v<- varpart.list[[i]]
colnames(v)<- c("Replicate", "Individual", "Residuals")
#vp<- sortCols(v)
vp.bar.list[[i]]<-plotVarPart(v, main= paste0("Cluster ", (i-1)))
}
vp.bar.list[[1]]
[[2]]
[[3]]
[[4]]
[[5]]
[[6]]
[[7]]
pdf(file = "/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/pdfs/VarPart_PseudobulkByCluster_res0.1.pdf")
vp.bar.list
dev.off()png(file= "/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/figs/VarPart_PseudobulkByCluster_res0.1.png", width= 7.5, height=7.5, units= "in", res= 1080)
vp.bar.list
dev.off()med.batch<- NULL
med.ind<- NULL
for (i in 1:7){
v<- varpart.list[[i]]
mb<-median(v$batch)
mi<- median(v$ind)
med.batch[i]<- mb
med.ind[i]<- mi
}
cluster<- c(0:6)
med.batch<- cbind(cluster, med.batch)
med.ind<- cbind(cluster, med.ind)
meds<- c(rep("replicate", 7), rep("individual", 7))
med.df<- rbind(med.batch, med.ind)
med.df<- as.data.frame(cbind(meds, med.df))
colnames(med.df)<- c("meds","cluster", "value")g<- ggplot(med.df, aes(x=cluster, y=(as.numeric(as.character(value))*100), fill=meds)) +geom_col(position="dodge") +ylim(0,100) +xlab("cluster (resolution 0.1)")+ylab("Median % variance explained")+theme(legend.title = element_blank())
g
png(file= "/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/figs/VarPart_Pseudobulk_res0.1_MedianExplainedBarPlot.png", width= 4, height=3, units= "in", res= 1080)
g
dev.off()sessionInfo()R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] variancePartition_1.16.1 Biobase_2.46.0 BiocGenerics_0.32.0
[4] scales_1.1.1 foreach_1.5.0 ggplot2_3.3.3
[7] edgeR_3.28.1 limma_3.42.2 dplyr_1.0.2
[10] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.6 locfit_1.5-9.4 here_0.1-11
[4] lattice_0.20-38 prettyunits_1.1.1 gtools_3.8.2
[7] rprojroot_2.0.2 digest_0.6.27 plyr_1.8.6
[10] R6_2.5.0 evaluate_0.14 highr_0.8
[13] pillar_1.4.7 gplots_3.0.4 rlang_0.4.10
[16] progress_1.2.2 minqa_1.2.4 gdata_2.18.0
[19] nloptr_1.2.2.2 Matrix_1.2-18 rmarkdown_2.3
[22] labeling_0.4.2 splines_3.6.1 BiocParallel_1.20.1
[25] lme4_1.1-23 statmod_1.4.34 stringr_1.4.0
[28] munsell_0.5.0 compiler_3.6.1 httpuv_1.5.4
[31] xfun_0.16 pkgconfig_2.0.3 htmltools_0.5.0
[34] tidyselect_1.1.0 tibble_3.0.4 codetools_0.2-16
[37] crayon_1.3.4 withr_2.4.2 later_1.1.0.1
[40] MASS_7.3-51.4 bitops_1.0-6 grid_3.6.1
[43] nlme_3.1-140 gtable_0.3.0 lifecycle_0.2.0
[46] git2r_0.26.1 magrittr_2.0.1 KernSmooth_2.23-15
[49] stringi_1.5.3 farver_2.0.3 reshape2_1.4.4
[52] fs_1.4.2 promises_1.1.1 doParallel_1.0.15
[55] colorRamps_2.3 ellipsis_0.3.1 generics_0.1.0
[58] vctrs_0.3.6 boot_1.3-23 iterators_1.0.12
[61] tools_3.6.1 glue_1.4.2 purrr_0.3.4
[64] hms_0.5.3 pbkrtest_0.4-8.6 yaml_2.2.1
[67] colorspace_2.0-0 caTools_1.18.0 knitr_1.29
sessionInfo()R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.4 (Nitrogen)
Matrix products: default
BLAS/LAPACK: /software/openblas-0.2.19-el7-x86_64/lib/libopenblas_haswellp-r0.2.19.so
locale:
[1] C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] variancePartition_1.16.1 Biobase_2.46.0 BiocGenerics_0.32.0
[4] scales_1.1.1 foreach_1.5.0 ggplot2_3.3.3
[7] edgeR_3.28.1 limma_3.42.2 dplyr_1.0.2
[10] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] Rcpp_1.0.6 locfit_1.5-9.4 here_0.1-11
[4] lattice_0.20-38 prettyunits_1.1.1 gtools_3.8.2
[7] rprojroot_2.0.2 digest_0.6.27 plyr_1.8.6
[10] R6_2.5.0 evaluate_0.14 highr_0.8
[13] pillar_1.4.7 gplots_3.0.4 rlang_0.4.10
[16] progress_1.2.2 minqa_1.2.4 gdata_2.18.0
[19] nloptr_1.2.2.2 Matrix_1.2-18 rmarkdown_2.3
[22] labeling_0.4.2 splines_3.6.1 BiocParallel_1.20.1
[25] lme4_1.1-23 statmod_1.4.34 stringr_1.4.0
[28] munsell_0.5.0 compiler_3.6.1 httpuv_1.5.4
[31] xfun_0.16 pkgconfig_2.0.3 htmltools_0.5.0
[34] tidyselect_1.1.0 tibble_3.0.4 codetools_0.2-16
[37] crayon_1.3.4 withr_2.4.2 later_1.1.0.1
[40] MASS_7.3-51.4 bitops_1.0-6 grid_3.6.1
[43] nlme_3.1-140 gtable_0.3.0 lifecycle_0.2.0
[46] git2r_0.26.1 magrittr_2.0.1 KernSmooth_2.23-15
[49] stringi_1.5.3 farver_2.0.3 reshape2_1.4.4
[52] fs_1.4.2 promises_1.1.1 doParallel_1.0.15
[55] colorRamps_2.3 ellipsis_0.3.1 generics_0.1.0
[58] vctrs_0.3.6 boot_1.3-23 iterators_1.0.12
[61] tools_3.6.1 glue_1.4.2 purrr_0.3.4
[64] hms_0.5.3 pbkrtest_0.4-8.6 yaml_2.2.1
[67] colorspace_2.0-0 caTools_1.18.0 knitr_1.29