RNASEQ DATA ANALYSIS

STEP 0

确认工作目录（Confirm your working directory）
所在目录下面有raw文件夹储存原始文件（'raw' file store rawdata）

STEP 1 01fastq.sh

质量控制（Quality Control）
1.fastqc 主要查看GC% ; 接头 ; 碱基质量 （GC% ; Adaptor ; Base quality）
2.multiqc

STEP 2 02trim.sh

去接头（The raw RNAseq data is first trimmed by Trim Galore to remove adaptors）

STEP 3 03fastq.sh

STEP 4 04hisat.sh

回帖基因组（The high quality RNAseq reads were mapped to the hg38 human / mm10 mouse genome by using Hisat2 ）
nohup sh 04hisat.sh > mapped_ratio.out &
index download : https://daehwankimlab.github.io/hisat2/download/

STEP 5 05bam.sh

从bam文件中提取出来未比对上的序列 ：samtools view x.bam | awk '$3=="*" {print ">"$1"\n"$10}' >x_no_mapped_reads.txt

STEP 6 06featurecounts.sh

'The number of reads mapped to each gene was counted using featureCounts software'
featureCounts software was used to map the number of reads to each gene.
gtf download : https://www.gencodegenes.org/
gtf download Chinese help description : https://blog.csdn.net/u011262253/article/details/89363809

STEP 7 Deseq2.r

差异基因分析（Differentially expressed genes (DEGs) analysis）

补充1：featurecounts 结果批量读取 merge.r

补充2：GSEA analysis GSEA.r

补充3：人鼠基因转换 human_mouse_gene_transition.r