RNASeq 数据分析

R 函数学习 - ComBat_seq

2020-08-11  本文已影响0人  Thinkando
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ComBat-seq:使用经验贝叶斯框架调整批处理效果
输入raw_count 文件,输出也是count 文件
安装(我在windows 没有安装成功,在linux 安装成功了)

# install.packages("devtools")
devtools::install_github("zhangyuqing/sva-devel")

Basic usage (users need to input at least two parameters - a raw count matrix from RNA-Seq studies, without any normalization or transformation, and a vector for batch separation):

count_matrix <- matrix(rnbinom(400, size=10, prob=0.1), nrow=50, ncol=8)
batch <- c(rep(1, 4), rep(2, 4))

adjusted <- ComBat_seq(count_matrix, batch=batch, group=NULL)
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In ComBat-Seq, user may specify biological covariates, whose signals will be preserved in the adjusted data. If the user would like to specify one biological variable, they may use the group parameter:

group <- rep(c(0,1), 4)
adjusted_counts <- ComBat_seq(count_matrix, batch=batch, group=group)

If users wish to specify multiple biological variables, they may pass them as a matrix or data frame to the covar_mod parameter:

cov1 <- rep(c(0,1), 4)
cov2 <- c(0,0,1,1,0,0,1,1)
covar_mat <- cbind(cov1, cov2)
adjusted_counts <- ComBat_seq(count_matrix, batch=batch, group=NULL, covar_mod=covar_mat)
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