This repository will guide you complete the analysis of RNA-seq offline using the following software:hisat2, samtools, and stringtie. Double-terminal sequencing data has been filtered by FastQC, and the specific filtering process is not involved in this paper. The sample data is for reference only. For the guided in Chinese version, you can visit my CSDN: https://blog.csdn.net/m0_64240043/article/details/122450444?spm=1001.2014.3001.5501
Let's look at the data to be processed as a whole
@biocloud:~/1223/NGS2022$ tree
.
├── gene_data.csv # final result!!
├── genome
│ ├── yeast.fa# reference genome
│ ├── yeast.gff# genome annotation for reference
│ └── yeast_transcriptome.fa # The transcriptome index file required by Kallisto, which is used to achieve transcription quantification based on pseudo Alignment, is not covered in this article
├── reads
│ ├── s1_y_1.fq.gz
│ ├── s1_y_2.fq.gz
│ ├── s2_y_1.fq.gz
│ └── s2_y_2.fq.gz
├── script # Script file. If necessary, add an absolute path to reference the script.
│ ├── edgeR.R
│ ├── prepDE.py
│ ├── prepDE.py3
│ └── run.sh
└── src # A software installation package that may be used. If the software has been installed on the server, you do not need to install it again.
├── fastqc_v0.11.9.zip
├── kallisto_linux-v0.46.1.tar.gz
├── samtools-1.14.tar.bz2
├── stringtie-2.2.0.Linux_x86_64.tar.gz$ cd ./genome
$ hisat2-build yeast.fa genome.fa $ cd ..
$ mkdir alignment
$ cd alignment
$ hisat2 -p 6 -x ../genome/genome.fa -1 ../reads/s1_y_1.fq.gz -2 ../reads/s1_y_2.fq.gz -S ./s1.sam$ samtools view -bS s1.sam -o s1.bam
$ samtools sort s1.bam s1.sorted
$ samtools index s1.sorted.bam 4.stringtie estimates transcript expression based on GTF annotation and bam alignment after sequencing
$ stringtie ./s1.sorted.bam -G ../genome/yeast.gff -e -p 2 -o ./s1_out.gtf -A ./s1_genes.list The comparison results of s2_out. GTF and S2_genes. List were obtained by the same method. The steps are exactly the same as above and will not be repeated here. A pair of double-ended sequencing results under each process produces an S1_out.gtf file. After following the steps above to process another pair of double-endsequencing, you should have two GTF files: s1_out.gtf and s2_out.gtf.
$ cd ..
$ mkdir differential_expression
$ cd differential_expression
$ vim sample_list.txt prepDE.py3 could be download from github（https://github.com/gpertea/stringtie）
$ python prepDE.py3 -i sample_list.txt -g gene_count.csv -t transcript.csvThe gene_count.csv obtained after the above steps is the list of differentially expressed genes.