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	<title>生信菜鸟团 &#187; hisat2</title>
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		<title>hisat2+stringtie+ballgown</title>
		<link>http://www.bio-info-trainee.com/2073.html</link>
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		<pubDate>Fri, 25 Nov 2016 15:06:23 +0000</pubDate>
		<dc:creator><![CDATA[ulwvfje]]></dc:creator>
				<category><![CDATA[转录组软件]]></category>
		<category><![CDATA[ballgown]]></category>
		<category><![CDATA[hisat2]]></category>
		<category><![CDATA[StringTie]]></category>
		<category><![CDATA[转录组]]></category>

		<guid isPermaLink="false">http://www.bio-info-trainee.com/?p=2073</guid>
		<description><![CDATA[早在去年九月，我就写个博文说 RNA-seq流程需要进化啦！ http://ww &#8230; <a href="http://www.bio-info-trainee.com/2073.html">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
				<content:encoded><![CDATA[<p>早在去年九月，我就写个博文说 RNA-seq流程需要进化啦！<a href="http://www.bio-info-trainee.com/1022.html" target="_blank"> http://www.bio-info-trainee.com/1022.html </a> ，主要就是进化成hisat2+stringtie+ballgown的流程，但是我一直没有系统性的讲这个流程，因为我觉真心木有用。我只用了里面的hisat来做比对而已！但是群里的小伙伴问得特别多，我还是勉为其难的写一个教程吧，你们之间拷贝我的代码就可以安装这些软件的！然后自己找一个测试数据，我的脚本很容易用的！<span id="more-2073"></span></p>
<div>其实我最喜欢这样的文章了：<a href="http://www.nature.com/nprot/journal/v11/n9/full/nprot.2016.095.html">http://www.nature.com/nprot/journal/v11/n9/full/nprot.2016.095.html</a> 而且人家还提供了所有的代码，不知道大家怎么还会有疑问的<a href="http://www.nature.com/nprot/journal/v11/n9/extref/nprot.2016.095-S1.zip" target="_blank">：http://www.nature.com/nprot/journal/v11/n9/extref/nprot.2016.095-S1.zip</a></div>
<div>人家已经把流程说得清清楚楚了，我还是说一个自己的体悟吧：</div>
<div>软件安装如下：</div>
<blockquote>
<div>## Download and install HISAT</div>
<div># https://ccb.jhu.edu/software/hisat2/index.shtml</div>
<div>cd ~/biosoft</div>
<div>mkdir HISAT &amp;&amp; cd HISAT</div>
<div>#### readme: https://ccb.jhu.edu/software/hisat2/manual.shtml</div>
<div>wget ftp://ftp.ccb.jhu.edu/pub/infphilo/hisat2/downloads/hisat2-2.0.4-Linux_x86_64.zip</div>
<div>unzip hisat2-2.0.4-Linux_x86_64.zip</div>
<div>ln -s hisat2-2.0.4 current</div>
<div>## ~/biosoft/HISAT/current/hisat2-build</div>
<div>## ~/biosoft/HISAT/current/hisat2</div>
<div></div>
<div>## Download and install StringTie</div>
<div>## https://ccb.jhu.edu/software/stringtie/ ## https://ccb.jhu.edu/software/stringtie/index.shtml?t=manual</div>
<div>cd ~/biosoft</div>
<div>mkdir StringTie &amp;&amp; cd StringTie</div>
<div>wget http://ccb.jhu.edu/software/stringtie/dl/stringtie-1.2.3.Linux_x86_64.tar.gz</div>
<div>tar zxvf stringtie-1.2.3.Linux_x86_64.tar.gz</div>
<div>ln -s stringtie-1.2.3.Linux_x86_64 current</div>
<div># ~/biosoft/StringTie/current/stringtie</div>
</blockquote>
<div></div>
<div>软件使用，我比较喜欢用shell脚本，而且是简单的那种：</div>
<div>
<blockquote>
<div>while read id</div>
<div>do</div>
<div>sample=$(echo $id |cut -d" " -f 1 )</div>
<div>file1=$(echo $id |cut -d" " -f 2 )</div>
<div>file2=$(echo $id |cut -d" " -f 3 )</div>
<div>echo  $sample</div>
<div>echo $file1</div>
<div>echo $file2</div>
<div>~/biosoft/HISAT/current/hisat2  -p 4 --dta  -x  ~/reference/index/hisat/hg19/genome  -1 $file1 -2 $file2 -S $sample.hisat2.hg19.sam 2&gt;$sample.hisat2.hg19.log &amp;</div>
<div>done &lt;$1</div>
</blockquote>
<div>上面这个脚本需要一个3列的输入文件，分别是样本名，read1文件，read2文件，会产生以下的输出文件，sam文件。</div>
<div><img src="C:\Users\jimmy1314\AppData\Local\YNote\data\jmzeng1314@163.com\5262fabc557a4523a4694cb992a1a399\clipboard.png" alt="" data-media-type="image" data-attr-org-src-id="0A2D6DB986A14AC0A37C06273FEC3647" /><a href="http://www.bio-info-trainee.com/wp-content/uploads/2016/11/16.png"><img class="alignnone size-full wp-image-2074" src="http://www.bio-info-trainee.com/wp-content/uploads/2016/11/16.png" alt="1" width="298" height="63" /></a></div>
<blockquote>
<div>while read id</div>
<div>do</div>
<div>file=$(basename $id )</div>
<div>sample=${file%%.*}</div>
<div>echo $id $sample</div>
<div>nohup samtools sort -@ 4 -o ${sample}.sorted.bam $id &amp;</div>
<div>done &lt;$1</div>
</blockquote>
<div><span style="color: #ff0000;">最新版的samtools已经可以直接把sam文件变成排序好的bam文件啦~~~~</span></div>
<div><img src="C:\Users\jimmy1314\AppData\Local\YNote\data\jmzeng1314@163.com\adf062aca85f49d08d1d860f3a09443e\clipboard.png" alt="" data-media-type="image" data-attr-org-src-id="9E5C149652164763BB6DE37FE9DDCA67" /><img class="alignnone size-full wp-image-2075" src="http://www.bio-info-trainee.com/wp-content/uploads/2016/11/23.png" alt="2" width="266" height="65" /></div>
<blockquote>
<div>while read id</div>
<div>do</div>
<div>file=$(basename $id )</div>
<div>sample=${file%%.*}</div>
<div>echo $id $sample</div>
<div>nohup ~/biosoft/StringTie/current/stringtie  -p 4  -G ~/reference/gtf/gencode/gencode.v25lift37.annotation.gtf  -o $sample.hg19.stringtie.gtf -l $sample  $id  &amp;</div>
<div>done &lt;$1</div>
</blockquote>
<div>stringTie的用法就是这样咯。没什么好讲的</div>
<div><img class="alignnone size-full wp-image-2076" src="http://www.bio-info-trainee.com/wp-content/uploads/2016/11/31.png" alt="3" width="318" height="82" /></div>
<div><img src="C:\Users\jimmy1314\AppData\Local\YNote\data\jmzeng1314@163.com\c61ae9e9ad8a47c1a5f7886632cfa1fa\clipboard.png" alt="" data-media-type="image" data-attr-org-src-id="930C433F5E104A8FA07D0306E15026DD" /></div>
<div></div>
<div> ~/biosoft/StringTie/current/stringtie   --merge -p 8 -G ~/reference/gtf/gencode/gencode.v25lift37.annotation.gtf  -o stringtie_merged.gtf  mergelist.txt</div>
<div></div>
<div></div>
<div>while read id</div>
<div>do</div>
<div>file=$(basename $id )</div>
<div>sample=${file%%.*}</div>
<div>echo $id $sample</div>
<div>nohup ~/biosoft/StringTie/current/stringtie -e -B  -G  $2  -o ballgown/$sample/$sample.hg19.stringtie.gtf   $id  &amp;</div>
<div>done &lt;$1</div>
</div>
<div>我实在讲不下去了，因为真心不用这个东东，<strong><span style="color: #ff0000;">我都是拿到了sam/bam文件就直接去counts表达量矩阵了</span></strong>，而count reads数量是非常容易的事情，代码如下</div>
<div>nohup samtools view   A.sorted.bam.Nsort.bam |  ~/.local/bin/htseq-count -f sam  -s no -i gene_name  -   ~/reference/gtf/gencode/gencode.v25lift37.annotation.gtf    1&gt;A.geneCounts 2&gt;A.HTseq.log &amp;</div>
<div>下面的这些文件，导入到R里面用ballgown处理吧，不要在问我这个问题了。</div>
<div><img class="alignnone size-full wp-image-2077" src="http://www.bio-info-trainee.com/wp-content/uploads/2016/11/4.png" alt="4" width="608" height="548" /></div>
<div></div>
<div></div>
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