CompiledFits_BatchvInd

Last updated: 2021-07-04

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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/figs/Supp_TopicLoadingHeat_JUSTLEGEND.png	../output/figs/Supp_TopicLoadingHeat_JUSTLEGEND.png

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Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.

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File	Version	Author	Date	Message
Rmd	068f5cb	KLRhodes	2021-07-04	wflow_publish(c("analysis/CompiledFits_BatchvInd.Rmd", "analysis/DownSamp_NoiseRatio.Rmd",

library(fastTopics)
library(stringr)
library(ggplot2)
library(cowplot)
library(tidyr)
library(ComplexHeatmap)

Loading required package: grid

========================================
ComplexHeatmap version 2.7.4
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite:
Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
  genomic data. Bioinformatics 2016.

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

library(circlize)

========================================
circlize version 0.4.11
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

library(patchwork)


Attaching package: 'patchwork'

The following object is masked from 'package:cowplot':

    align_plots

library(ggplotify)
library(ggplot2)

load("/project2/gilad/katie/Pilot_HumanEBs/fastTopics/fits.RData")

load("/project2/gilad/katie/Pilot_HumanEBs/fastTopics/prepared_data_YorubaOnly_genesExpressedInMoreThan10Cells.RData")

scd<- grep("scd", names(fits))
scd<- names(fits)[scd]

#loadings plot for Batch 

lps<- NULL
for ( i in 1:length(scd)){
  
lps[[i]]<- loadings_plot(poisson2multinom(fits[[scd[i]]]$fit), as.factor(samples$Batch))
}
lps

[[1]]


[[2]]


[[3]]


[[4]]


[[5]]

#loadings plot for individual 

lps<- NULL
for ( i in 1:length(scd)){
  
lps[[i]]<- loadings_plot(poisson2multinom(fits[[scd[i]]]$fit), as.factor(samples$individual))
}
lps

[[1]]


[[2]]


[[3]]


[[4]]


[[5]]

#add clean names to samples df
replicate<- samples$Batch
replicate[replicate == "Batch1"]<- "Rep1"
replicate[replicate == "Batch2"]<- "Rep2"
replicate[replicate == "Batch3"]<- "Rep3"

samples<- cbind(samples, replicate)


samples$individual[samples$individual == "SNG-NA18511"]<- "18511"
samples$individual[samples$individual == "SNG-NA19160"]<- "19160"
samples$individual[samples$individual == "SNG-NA18858"]<- "18858"

samples<- samples %>% unite(rep_individual, c("replicate", "individual"))

#loadings plot for Batch_individual groups 

lps<- NULL
for ( i in 1:length(scd)){
  
lps[[i]]<- loadings_plot(poisson2multinom(fits[[scd[i]]]$fit), as.factor(samples$rep_individual))
}
lps

[[1]]


[[2]]


[[3]]


[[4]]


[[5]]

col_fun<- colorRamp2(c(0,0.3, 1), c("white", '#332288', "black"))
hp<- list()
for(i in 1:length(scd)){

#split Loadings by batch_individual groups
l<- poisson2multinom(fits[[scd[i]]]$fit)$L
l<- split.data.frame(l, samples$rep_individual)

#compute average loading for each batch_ind in each topic
m<- lapply(l, colMeans)

#to matrix
m<- as.matrix(as.data.frame(m))

#generate correlation heatmap
#heatmap(m, cexCol = 0.8, cexRow = 0.5, margins= c(8,3), main= paste0(ncol(l$`Batch1_SNG-NA18511`), " Topics"))

hp[[i]]<-Heatmap(m, col= col_fun, show_heatmap_legend = FALSE, column_title = paste0(ncol(l$Rep1_18511), " topics"), row_names_gp = gpar(fontsize = 8), cluster_rows=FALSE)
}

hp

[[1]]


[[2]]


[[3]]


[[4]]


[[5]]

all<-(as.ggplot(hp[[1]]) + as.ggplot(hp[[2]])+ as.ggplot(hp[[3]]) + as.ggplot(hp[[4]]) + as.ggplot(hp[[5]]))

png(file= "/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/figs/Supp_TopicLoadingHeat.png", width=7.5, height=8.5, units= "in", res=1080)

all

dev.off()

lgd<- Legend(col_fun = col_fun, title= "average \nloading")

png(file= "/project2/gilad/katie/Pilot_HumanEBs/Embryoid_Body_Pilot_Workflowr/output/figs/Supp_TopicLoadingHeat_JUSTLEGEND.png", width=1, height=2, units= "in", res=1080)

draw(lgd)

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] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] ggplotify_0.0.5      patchwork_1.1.1      circlize_0.4.11     
 [4] ComplexHeatmap_2.7.4 tidyr_1.1.0          cowplot_1.1.1       
 [7] ggplot2_3.3.3        stringr_1.4.0        fastTopics_0.3-145  
[10] workflowr_1.6.2     

loaded via a namespace (and not attached):
 [1] mcmc_0.9-7          matrixStats_0.57.0  fs_1.4.2           
 [4] RColorBrewer_1.1-2  progress_1.2.2      httr_1.4.2         
 [7] rprojroot_2.0.2     tools_3.6.1         R6_2.5.0           
[10] irlba_2.3.3         lazyeval_0.2.2      BiocGenerics_0.32.0
[13] colorspace_2.0-0    GetoptLong_1.0.5    withr_2.4.2        
[16] tidyselect_1.1.0    prettyunits_1.1.1   compiler_3.6.1     
[19] git2r_0.26.1        quantreg_5.61       Cairo_1.5-12.2     
[22] SparseM_1.78        plotly_4.9.2.1      labeling_0.4.2     
[25] scales_1.1.1        quadprog_1.5-8      digest_0.6.27      
[28] rmarkdown_2.3       MCMCpack_1.4-8      pkgconfig_2.0.3    
[31] htmltools_0.5.0     highr_0.8           htmlwidgets_1.5.1  
[34] rlang_0.4.10        GlobalOptions_0.1.2 farver_2.0.3       
[37] shape_1.4.5         gridGraphics_0.5-0  generics_0.1.0     
[40] jsonlite_1.7.2      dplyr_1.0.2         magrittr_2.0.1     
[43] Matrix_1.2-18       Rcpp_1.0.6          munsell_0.5.0      
[46] S4Vectors_0.24.4    lifecycle_0.2.0     stringi_1.5.3      
[49] whisker_0.4         yaml_2.2.1          MASS_7.3-51.4      
[52] Rtsne_0.15          parallel_3.6.1      promises_1.1.1     
[55] ggrepel_0.9.0       crayon_1.3.4        lattice_0.20-38    
[58] hms_0.5.3           magick_2.4.0        knitr_1.29         
[61] pillar_1.4.7        rjson_0.2.20        stats4_3.6.1       
[64] glue_1.4.2          evaluate_0.14       data.table_1.13.4  
[67] BiocManager_1.30.10 RcppParallel_5.0.2  png_0.1-7          
[70] vctrs_0.3.6         httpuv_1.5.4        MatrixModels_0.4-1 
[73] gtable_0.3.0        purrr_0.3.4         clue_0.3-58        
[76] xfun_0.16           coda_0.19-3         later_1.1.0.1      
[79] viridisLite_0.3.0   tibble_3.0.4        conquer_1.0.1      
[82] rvcheck_0.1.8       IRanges_2.20.2      cluster_2.1.0      
[85] ellipsis_0.3.1

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] grid      stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] ggplotify_0.0.5      patchwork_1.1.1      circlize_0.4.11     
 [4] ComplexHeatmap_2.7.4 tidyr_1.1.0          cowplot_1.1.1       
 [7] ggplot2_3.3.3        stringr_1.4.0        fastTopics_0.3-145  
[10] workflowr_1.6.2     

loaded via a namespace (and not attached):
 [1] mcmc_0.9-7          matrixStats_0.57.0  fs_1.4.2           
 [4] RColorBrewer_1.1-2  progress_1.2.2      httr_1.4.2         
 [7] rprojroot_2.0.2     tools_3.6.1         R6_2.5.0           
[10] irlba_2.3.3         lazyeval_0.2.2      BiocGenerics_0.32.0
[13] colorspace_2.0-0    GetoptLong_1.0.5    withr_2.4.2        
[16] tidyselect_1.1.0    prettyunits_1.1.1   compiler_3.6.1     
[19] git2r_0.26.1        quantreg_5.61       Cairo_1.5-12.2     
[22] SparseM_1.78        plotly_4.9.2.1      labeling_0.4.2     
[25] scales_1.1.1        quadprog_1.5-8      digest_0.6.27      
[28] rmarkdown_2.3       MCMCpack_1.4-8      pkgconfig_2.0.3    
[31] htmltools_0.5.0     highr_0.8           htmlwidgets_1.5.1  
[34] rlang_0.4.10        GlobalOptions_0.1.2 farver_2.0.3       
[37] shape_1.4.5         gridGraphics_0.5-0  generics_0.1.0     
[40] jsonlite_1.7.2      dplyr_1.0.2         magrittr_2.0.1     
[43] Matrix_1.2-18       Rcpp_1.0.6          munsell_0.5.0      
[46] S4Vectors_0.24.4    lifecycle_0.2.0     stringi_1.5.3      
[49] whisker_0.4         yaml_2.2.1          MASS_7.3-51.4      
[52] Rtsne_0.15          parallel_3.6.1      promises_1.1.1     
[55] ggrepel_0.9.0       crayon_1.3.4        lattice_0.20-38    
[58] hms_0.5.3           magick_2.4.0        knitr_1.29         
[61] pillar_1.4.7        rjson_0.2.20        stats4_3.6.1       
[64] glue_1.4.2          evaluate_0.14       data.table_1.13.4  
[67] BiocManager_1.30.10 RcppParallel_5.0.2  png_0.1-7          
[70] vctrs_0.3.6         httpuv_1.5.4        MatrixModels_0.4-1 
[73] gtable_0.3.0        purrr_0.3.4         clue_0.3-58        
[76] xfun_0.16           coda_0.19-3         later_1.1.0.1      
[79] viridisLite_0.3.0   tibble_3.0.4        conquer_1.0.1      
[82] rvcheck_0.1.8       IRanges_2.20.2      cluster_2.1.0      
[85] ellipsis_0.3.1