In githubz0r/SecretUtils: Some utils for Conos

load packages and data

library(conos)
library(tidyverse)
library(parallel)
library(Matrix)
library(data.table)
library(pagoda2)
library(cowplot)
library(abind)
library(Rtsne)
devtools::load_all('/home/larsc/SecretUtils')

con <- readRDS(file.path('/home/larsc/data/10x_preproced_graphed.rds'))
con <- Conos$new(con)
annot <- readRDS(file.path('/home/demharters/R/projects/UPF9_14_17_19_22_23_24_32_33/metadata_10x_final.rds'))
fraction_palette_eps <- c(epilepsy='hotpink', healthy='seagreen') 

The fractions across the conditions are the average of the fractions for each sample.

FractionalPlot(annot$sample, annot$subtype, annot$condition, fraction.palette = fraction_palette_eps)

Looking at patients instead

freq_df <- FractionalPlot(annot$sample, annot$subtype, annot$condition, return.plot=F) 
ggplot(na.omit(freq_df),aes(x=subtype,y=freq, col=patient))+ 
  geom_point() + theme(axis.text.x = element_text(angle = 90, hjust = 1), axis.text.y = element_text(angle = 90, hjust = 0.5)) +
    xlab("") +ylab("fraction of total cells")+ theme(legend.position="right")

Distance matrix tsne plot

annot2 <- annot %>% mutate(cellid=rownames(annot))
source('/home/larsc/SecretUtils/R/peter_code_utils.R')
sub_dist_mat <- Makesubdistmat(con, annot2$sample, annot2$subtype, annot2$cellid)

## some weird shit
#testannot <- bind_cols(list(annot2$sample, annot2$subtype, annot2$cellid))
#tf_test <- setNames(testannot[, 2], testannot[, 3]) %>% as.factor # does not work
#tf_test <- setNames(testannot[[2]], testannot[[3]]) %>% as.factor
## end weird shit
PlotDistanceMatRed(sub_dist_mat, annot2$sample, annot2$subtype, annot2$sample, 
                   annot2$cellid, annot2$condition, perplexity=2, max_iter=1e4) # add labels

check the mat

PlotDistanceMatRed(sub_dist_mat, annot2$sample, annot2$subtype, annot2$sample, 
                   annot2$cellid, annot2$condition, perplexity=2, max_iter=1e4, get.mat=TRUE)

Condition distance distribution (uses JSD in Peter's code, replace with something more suitable)

ConditionDistanceDensity(sub_dist_mat, annot$sample, annot$subtype, annot$sample, annot2$cellid, annot$condition,
                         notch=F, fraction.palette = fraction_palette_eps)

Distribution of distances per cell type (JSD again). It's possible that there are better ways to visualize this.

min_cells=0
SecretUtils::PlotCellTypeDists(sub_dist_mat, min_cells, annot$sample, annot$condition)

githubz0r/SecretUtils documentation built on May 15, 2021, 10:29 p.m.