In VPetukhov/dropEstAnalysis: Analysis to produce figures from dropEst paper

knitr::read_chunk("../../analysis/chunks.R")

library(ggplot2)
library(ggrastr)
library(ggpubr)
library(dplyr)
library(Matrix)
library(parallel)
library(dropestr)
library(dropEstAnalysis)

theme_set(theme_base)

set.seed(42)
kOutputFolder <- '../../output/'
kDataPath <- '../../data/'
kEstDataPath <- paste0(kDataPath, 'dropest/SCG71/runtimes/est_2018_03_15_real/')

tag_stats <- kEstDataPath %>% 
  paste0('../tag_2018_03_15/SCG_71_C2_S2_R1_001.fastq.gz.tagged.rds') %>% readRDS()

holder <- readRDS(paste0(kEstDataPath, 'cell.counts.rds'))

UMI collisions

times_coll <- sapply(1:10, function(i) TimeCollisions(holder))
mean(times_coll, trim=0.2)

Error corrections directional

times_directional <- sapply(1:10, function(i) TimeUmiErrors(holder$reads_per_umi_per_cell, 
                                                            'directional', mc.cores=10))
print(times_directional)
mean(times_directional, trim=0.1)

Error corrections Bayesian

times_bayesian <- sapply(1:5, function(i) TimeUmiErrors(holder$reads_per_umi_per_cell, 
                                                        mc.cores=10))
print(times_bayesian)
mean(times_bayesian, trim=0.1)

Quality scoring

times_quality <- sapply(1:10, function(i) TimeQuality(holder, mit.chromosome.name='chrM', 
                                                      tags.data=tag_stats))
print(times_quality)
mean(times_quality, trim=0.1)