source("R/Posterior.R")
source("R/Stats.R")
source("R/Util.R")
require(Biostrings)
require(Peptides)
require(rstan)
rstan_options(auto_write = TRUE)
require(ggplot2)
d <- read.csv(file = "cells.data.tsv", header = T,
as.is = T, sep = "\t")
d <- d[, c("sample", "condition", "cdr3.aa")]
d$cdr3.sequence <- d$cdr3.aa
d$cdr3.aa <- NULL
cdr3.data <- d
table(cdr3.data$sample, cdr3.data$condition)
cdr3.data <- cdr3.data[cdr3.data$sample %in% c("11B_S3", "12B_S7",
"11E_S6", "12E_S8",
"1N_S15", "3N_S17"), ]
stats <- computeCdr3Stats(cdr3.data = cdr3.data,
hdi.level = 0.95,
cores = 2)
ggplot(data = stats$length$stats$summary.sample)+
geom_point(aes(x = condition, y = mean, group = sample, col = condition),
position = position_dodge(width = 0.65))+
geom_errorbar(aes(x = condition, y = mean, group = sample,
col = condition, ymin = mean_L, ymax = mean_H),
position = position_dodge(width = 0.65), width = 0.3)+
theme_bw()+
theme(legend.position = "top")
ggplot(data = stats$length$stats$summary.condition)+
geom_point(aes(x = condition, y = mean, col = condition))+
geom_errorbar(aes(x = condition, y = mean, col = condition,
ymin = mean_L, ymax = mean_H), width = 0.2)+
theme_bw()+
theme(legend.position = "top")
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