傳送門(mén)：

RNAseq005 轉(zhuǎn)錄組入門(mén)(5)：序列比對(duì)
RNAseq004 轉(zhuǎn)錄組入門(mén)(4)：參考基因組下載
 RNAseq003 轉(zhuǎn)錄組入門(mén)(3)：了解fastq測(cè)序數(shù)據(jù)
RNAseq002 轉(zhuǎn)錄組入門(mén)(2)：數(shù)據(jù)下載
 RNAseq001 轉(zhuǎn)錄組入門(mén)(1)：資源準(zhǔn)備

前面的五章我們分析的是人類(lèi)mRNA-Seq測(cè)序的結(jié)果，一般而言RNA-Seq數(shù)據(jù)分析都要有重復(fù)，而文章中有一個(gè)樣本缺少配對(duì)數(shù)據(jù)，所以還是選用小鼠的數(shù)據(jù)把流程再來(lái)一遍

1.數(shù)據(jù)下載及質(zhì)控見(jiàn)前文

2.比對(duì)

# HISAT2比對(duì)
for i in {59..62};do hisat2 -t -x /mnt/e/Work/bioinfo/public/index/mouse/hisat2/grcm38/genome -1 /mnt/e/Work/bioinfo/project/202009_RNAseq/data/SRR35899${i}_1.fastq.gz  -2 /mnt/e/Work/bioinfo/project/202009_RNAseq/data/SRR35899${i}_2.fastq.gz -S /mnt/e/Work/bioinfo/project/202009_RNAseq/result/align/20200910mouse/SRR35899${i}.sam;done

3.SAM2BAM

# SAM文件轉(zhuǎn)換為BAM
for i in `seq 59 62`
do
samtools view -S SRR35899${i}.sam -b > SRR35899${i}.bam
done

4.bam flag統(tǒng)計(jì)

# 對(duì)排序后的bam統(tǒng)計(jì)flagstat
# basename命令用于獲取路徑中的文件名或路徑名，可以對(duì)末尾的擴(kuò)展名進(jìn)行刪除

ls *.bam |while read id ;do (samtools flagstat -@ 1 $id > $(basename ${id} ".bam").flagstat );done
mkdir flagstat && mv *.flagstat flagstat && cd flagstat
multiqc ./

4.1 用一個(gè)小腳本把統(tǒng)計(jì)信息轉(zhuǎn)換為csv文件

# 創(chuàng)建腳本
cat > stat.sh
### 將以下內(nèi)容寫(xiě)入stat.sh
#!/bin/bash
cat *.flagstat | awk '{print $1}' | paste - - - - - - - - - - - - - > file1
# 77607517        16671207        0       0       75387881        60936310        30468155        30468155        56502696       57494864        1221810 832364  530657
# 134310379       28365145        0       0       130964009       105945234       52972617        52972617        98979648       100621038       1977826 1398380 907493
# 94264829        20737377        0       0       91921243        73527452        36763726        36763726        68525830       69723750        1460116 1023854 644490
# 111681106       24075844        0       0       109169544       87605262        43802631        43802631        82145504       83390620        1703080 1013088 643888
# 取行名
cut -d"+" -f 2 SRR3589959.flagstat | cut -d" " -f 3-90 > file2
# in total (QC-passed reads
# secondary
# supplementary
# duplicates
# mapped (97.14% : N/A)
# paired in sequencing
# read1
# read2
# properly paired (92.72% : N/A)
# with itself and mate mapped
# singletons (2.01% : N/A)
# with mate mapped to a different chr
# with mate mapped to a different chr (mapQ>=5)
# 取列名
ls *.flagstat | while read id ;do echo $(basename ${id} ".flagstat") ;done > file3
# SRR3589959
# SRR3589960
# SRR3589961
# SRR3589962
paste file3 file1 > file4
# 將file4行列轉(zhuǎn)置
awk '{
    for (i=1;i<=NF;i++){
        if (NR==1){
            res[i]=$i
        }
        else{
            res[i]=res[i]" "$i
        }
    }
}END{
    for(j=1;j<=NF;j++){
        print res[j]
    }
}' file4 > file5
# 在file2首行加入內(nèi)容
sed '1i Index' file2 > file6
paste  file6 file5 > stat.txt
cat stat.txt > stat.csv
rm file*
# 腳本內(nèi)容截止
# ==========================================================================
# 退出腳本編輯Enter，ctrl+c
# 運(yùn)行腳本
bash stat.sh

4.2 csv文件處理

image.png

csv文件打開(kāi)后是這個(gè)樣子：

image.png
選中第一列→數(shù)據(jù)→分列→分隔符→選擇tab分隔

image.png
選中第二列→數(shù)據(jù)→分列→分隔符→選擇空格分隔

image.png
轉(zhuǎn)換完成

image.png

5.bam排序，索引

# 排序，索引
for i in `seq 59 62`
do
samtools sort SRR35899${i}.bam -o SRR35899${i}_sorted.bam
samtools index SRR35899${i}_sorted.bam
done

# 將SAM轉(zhuǎn)換為BAM，并排序構(gòu)建索引，隨后刪除SAM文件
# for i in `seq 59 62`
# do
# samtools view -S SRR35899${i}.sam -b > SRR35899${i}.bam
# samtools sort SRR35899${i}.bam -o SRR35899${i}_sorted.bam
# samtools index SRR35899${i}_sorted.bam
# done
# rm *.sam

6 注釋

# 注釋
for i in {59..62}
do 
htseq-count -s no -f bam -r pos /mnt/e/Work/bioinfo/project/202009_RNAseq/result/align/20200910mouse/SRR35899${i}_sorted.bam /mnt/e/Work/bioinfo/public/Annotation/mouse/gencode/gencode.vM25.annotation.gff3 > /mnt/e/Work/bioinfo/project/202009_RNAseq/result/annotation/SRR35899${i}.count
done

# 代碼運(yùn)行報(bào)錯(cuò)
# Please Install PySam to use the BAM_Reader Class (http://code.google.com/p/pysam/)Error occured when reading beginning of BAM file.
# No module named pysam
# [Exception type: ImportError, raised in __init__.py:1086]
 
# 解決辦法
# 下載pysam源代碼
# 下載地址：https://pypi.org/project/pysam/#files
# 復(fù)制下載鏈接放入迅雷：https://files.pythonhosted.org/packages/99/5a/fc440eb5fffb5346e61a38b49991aa552e4b8b31e8493a101d2833ed1e19/pysam-0.16.0.1.tar.gz
cd ~/biosoft
mkdir pysam &&  cd pysam
wget https://files.pythonhosted.org/packages/99/5a/fc440eb5fffb5346e61a38b49991aa552e4b8b31e8493a101d2833ed1e19/pysam-0.16.0.1.tar.gz
tar zxvf pysam-0.16.0.1.tar.gz
cd pysam-0.16.0.1
python setup.py install
# 報(bào)錯(cuò)
# Traceback (most recent call last):
# File "setup.py", line 24, in <module>
# from setuptools import setup, find_packages
# ImportError: No module named setuptools
# python2環(huán)境下安裝setuptools
sudo apt-get install python-setuptools
# python3環(huán)境下安裝setuptools
sudo apt-get install python3-setuptools
# 再次執(zhí)行安裝
sudo python setup.py install

# 再次運(yùn)行注釋
# 構(gòu)建腳本
cat > annotation.sh
#### 輸入以下內(nèi)容
#!/bin/bash
for i in {59..62}
do 
# .sorted.bam地址
input="/mnt/e/Work/bioinfo/project/202009_RNAseq/result/align/20200910mouse/SRR35899${i}_sorted.bam"
# .gtf地址
annotation="/mnt/e/Work/bioinfo/public/Annotation/mouse/gencode/gencode.vM25.annotation.gff3"
# 輸出文件地址
output="/mnt/e/Work/bioinfo/project/202009_RNAseq/result/annotation"
htseq-count -s no -f bam -r pos ${input} ${annotation} > ${output}/SRR35899${i}.count
done 
# ===============================

# 運(yùn)行
bash annotation.sh

7 featureCounts統(tǒng)計(jì)

# featureCounts計(jì)數(shù)
featureCounts -p -t exon -g gene_id -a /mnt/e/Work/bioinfo/public/Annotation/mouse/gencode/gencode.vM25.annotation.gff3 -o /mnt/e/Work/bioinfo/project/202009_RNAseq/result/count/all.id.txt /mnt/e/Work/bioinfo/project/202009_RNAseq/result/align/20200910mouse/SRR35899{59..62}_sorted.bam

# 運(yùn)行后報(bào)錯(cuò)
# featurecounts segmentation fault (core dumped)
# 解決辦法
# 下載二進(jìn)制版本subread
rm -rf ~/biosoft/subread
mkdir -p ~/biosoft/subread && cd ~/biosoft/subread
wget https://nchc.dl.sourceforge.net/project/subread/subread-2.0.1/subread-2.0.1-Linux-x86_64.tar.gz
tar zxvf subread-2.0.1-Linux-x86_64.tar.gz
cd subread-2.0.1-Linux-x86_64
cd ~/biosoft/subread/subread-2.0.1-Linux-x86_64/bin
./featureCounts
echo "export PATH=\$PATH:/home/cqs/biosoft/subread/subread-2.0.1-Linux-x86_64/bin" >> ~/.bashrc
source ~/.bashrc
featureCounts

# 再次運(yùn)行代碼
featureCounts -p -t exon -g gene_id -a /mnt/e/Work/bioinfo/public/Annotation/mouse/gencode/gencode.vM25.annotation.gff3 -o /mnt/e/Work/bioinfo/project/202009_RNAseq/result/count/all.id.txt /mnt/e/Work/bioinfo/project/202009_RNAseq/result/align/20200910mouse/SRR35899{59..62}_sorted.bam

# 對(duì)all.id.txt.summary進(jìn)行multiqc，查看Counts質(zhì)控
multiqc ./all.id.txt.summary
# [INFO   ]         multiqc : This is MultiQC v1.9
# [INFO   ]         multiqc : Template    : default
# [INFO   ]         multiqc : Searching   : /mnt/e/Work/bioinfo/project/202009_RNAseq/result/count/all.id.txt.summary
# Searching 1 files..  [####################################]  100%
# [INFO   ]  feature_counts : Found 4 reports
# [INFO   ]         multiqc : Compressing plot data
# [INFO   ]         multiqc : Report      : multiqc_report.html
# [INFO   ]         multiqc : Data        : multiqc_data
# [INFO   ]         multiqc : MultiQC complete

image.png

8.htseq-count統(tǒng)計(jì)

cat > htseq-count.sh
### 輸入以下內(nèi)容
#!/bin/bash
for i in {59..62}
do
# .sorted.bam地址
input="/mnt/e/Work/bioinfo/project/202009_RNAseq/result/align/20200910mouse/SRR35899${i}_sorted.bam"
# .gtf地址
annotation="/mnt/e/Work/bioinfo/public/Annotation/mouse/gencode/gencode.vM25.annotation.gff3"
# 輸出文件地址
output="/mnt/e/Work/bioinfo/project/202009_RNAseq/result/annotation"
htseq-count -s no -f bam -r pos ${input} ${annotation} > ${output}/SRR35899${i}.count
echo "SRR35899${i}.count is completed"
done
#==========================

# 運(yùn)行腳本
bash htseq-count.sh

htseq-count.sh運(yùn)行結(jié)果

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RNAseq006 轉(zhuǎn)錄組入門(mén)(6)：reads計(jì)數(shù)

RNAseq006 轉(zhuǎn)錄組入門(mén)(6)：reads計(jì)數(shù)

傳送門(mén)：

1.數(shù)據(jù)下載及質(zhì)控見(jiàn)前文

2.比對(duì)

3.SAM2BAM

4.bam flag統(tǒng)計(jì)

4.1 用一個(gè)小腳本把統(tǒng)計(jì)信息轉(zhuǎn)換為csv文件

4.2 csv文件處理

5.bam排序，索引

6 注釋

7 featureCounts統(tǒng)計(jì)

8.htseq-count統(tǒng)計(jì)

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RNAseq006 轉(zhuǎn)錄組入門(mén)(6)：reads計(jì)數(shù)

傳送門(mén)：

1.數(shù)據(jù)下載及質(zhì)控見(jiàn)前文

2.比對(duì)

3.SAM2BAM

4.bam flag統(tǒng)計(jì)

4.1 用一個(gè)小腳本把統(tǒng)計(jì)信息轉(zhuǎn)換為csv文件

4.2 csv文件處理

5.bam排序，索引

6 注釋

7 featureCounts統(tǒng)計(jì)

8.htseq-count統(tǒng)計(jì)

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5.bam排序，索引