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Knit directory: Embryoid_Body_Pilot_Workflowr/analysis/

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/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/Pseudobulk_VarPart.ByCluster.Res0.1.rds ../output/Pseudobulk_VarPart.ByCluster.Res0.1.rds
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/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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There are no past versions. Publish this analysis with wflow_publish() to start tracking its development.


library(dplyr)

Attaching package: 'dplyr'
The following objects are masked from 'package:stats':

    filter, lag
The following objects are masked from 'package:base':

    intersect, setdiff, setequal, union
library(limma)
library(edgeR)
library(variancePartition)
Loading required package: ggplot2
Loading required package: foreach
Loading required package: scales
Loading required package: Biobase
Loading required package: BiocGenerics
Loading 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, parSapplyLB
The following object is masked from 'package:limma':

    plotMA
The following objects are masked from 'package:dplyr':

    combine, intersect, setdiff, union
The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs
The 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.min
Welcome 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':

    classifyTestsF
library(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.plots
saveRDS(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