歡迎關(guān)注Bioinfor 生信云 微信公眾號(hào)！
差異表達(dá)分析用于比較兩個(gè)樣本中同一個(gè)基因的的表達(dá)量是否存在差異击吱。用到的統(tǒng)計(jì)方法是假設(shè)檢驗(yàn)篮条，所以樣本需要重復(fù)。常用的軟件包括DESeq2缴渊、edgeR，這里推薦使用trinity軟件包的一個(gè)程序run_DE_analysis.pl鱼炒，安裝方法：conda install trinity
run_DE_analysis.pl
#!/usr/bin/env perl
use strict;
use warnings;
use Carp;
use Getopt::Long qw(:config no_ignore_case bundling pass_through);
use Cwd;
use FindBin;
use File::Basename;
use lib ("$FindBin::RealBin/../../PerlLib");
use Fasta_reader;
use Data::Dumper;
my $ROTS_B = 500;
my $ROTS_K = 5000;
my $usage = <<__EOUSAGE__;
#################################################################################################
#
# Required:
#
# --matrix|m <string> matrix of raw read counts (not normalized!)
#
# --method <string> edgeR|DESeq2|voom|ROTS
# note: you should have biological replicates.
# edgeR will support having no bio replicates with
# a fixed dispersion setting.
#
# Optional:
#
# --samples_file|s <string> tab-delimited text file indicating biological replicate relationships.
# ex.
# cond_A cond_A_rep1
# cond_A cond_A_rep2
# cond_B cond_B_rep1
# cond_B cond_B_rep2
#
#
# General options:
#
# --min_rowSum_counts <int> default: 2 (only those rows of matrix meeting requirement will be tested)
#
# --output|o name of directory to place outputs (default: \$method.\$pid.dir)
#
# --reference_sample <string> name of a sample to which all other samples should be compared.
# (default is doing all pairwise-comparisons among samples)
#
# --contrasts <string> file (tab-delimited) containing the pairs of sample comparisons to perform.
# ex.
# cond_A cond_B
# cond_Y cond_Z
#
#
###############################################################################################
#
# ## EdgeR-related parameters
# ## (no biological replicates)
#
# --dispersion <float> edgeR dispersion value (Read edgeR manual to guide your value choice)
# http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
# ## ROTS parameters
# --ROTS_B <int> : number of bootstraps and permutation resampling (default: $ROTS_B)
# --ROTS_K <int> : largest top genes size (default: $ROTS_K)
#
#
###############################################################################################
#
# Documentation and manuals for various DE methods. Please read for more advanced and more
# fine-tuned DE analysis than provided by this helper script.
#
# edgeR: http://www.bioconductor.org/packages/release/bioc/html/edgeR.html
# DESeq2: http://bioconductor.org/packages/release/bioc/html/DESeq2.html
# voom/limma: http://bioconductor.org/packages/release/bioc/html/limma.html
# ROTS: http://www.btk.fi/research/research-groups/elo/software/rots/
#
###############################################################################################
腳本用法
perl anaconda3/opt/trinity-2.1.1/Analysis/DifferentialExpression/run_DE_analysis.pl \ #你的路徑
--matrix genes.counts.matrix \ #原始count矩陣
--method DESeq2 \ #差異分析的軟件
--samples_file sample.txt \ #分組的樣本信息表
輸入：read count矩陣
輸出：差異分析結(jié)果
