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	<title>生信菜鸟团 &#187; GEOquery</title>
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		<title>我用rmarkdown写过的教程</title>
		<link>http://www.bio-info-trainee.com/2372.html</link>
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		<pubDate>Wed, 15 Mar 2017 09:16:05 +0000</pubDate>
		<dc:creator><![CDATA[ulwvfje]]></dc:creator>
				<category><![CDATA[R]]></category>
		<category><![CDATA[DESeq2]]></category>
		<category><![CDATA[GEOquery]]></category>
		<category><![CDATA[limma]]></category>
		<category><![CDATA[rmarkdown]]></category>

		<guid isPermaLink="false">http://www.bio-info-trainee.com/?p=2372</guid>
		<description><![CDATA[用rmarkdown写教程真心非常方便，尤其是R语言相关的，比如一些R包的应用， &#8230; <a href="http://www.bio-info-trainee.com/2372.html">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
				<content:encoded><![CDATA[<div>用rmarkdown写教程真心非常方便，尤其是R语言相关的，比如一些R包的应用，或者一些可视化，或者一些统计，下面我简单列出一些我以前写过的，图文并茂，关键是还非常省心，不需要排版，不需要上传图片，整理图片。</div>
<p>一般来说看链接最后的文件名就知道这篇文章讲的是什么了：</p>
<div>首先是几个R包的讲解：<br />
<a href="http://www.bio-info-trainee.com/bioconductor_China/software/limma.html" target="_blank">http://www.bio-info-trainee.com/ ... software/limma.html</a><br />
<a href="http://www.bio-info-trainee.com/bioconductor_China/software/DESeq2.html" target="_blank">http://www.bio-info-trainee.com/ ... oftware/DESeq2.html</a><br />
<a href="http://www.bio-info-trainee.com/bioconductor_China/software/GEOquery.html" target="_blank">http://www.bio-info-trainee.com/ ... tware/GEOquery.html</a><br />
<a href="http://www.bio-info-trainee.com/bioconductor_China/software/limma_voom.html" target="_blank">http://www.bio-info-trainee.com/ ... are/limma_voom.html</a><br />
当然，一些并不是bioconductor的包我也会写教程， 偶尔：<br />
<a href="http://www.bio-info-trainee.com/bioconductor_China/software/GOplot.html" target="_blank">http://www.bio-info-trainee.com/ ... oftware/GOplot.html</a><br />
<a href="http://www.bio-info-trainee.com/bioconductor_China/software/Rcircos.html" target="_blank">http://www.bio-info-trainee.com/ ... ftware/Rcircos.html</a></div>
<p><span id="more-2372"></span></p>
<div></div>
<div>下面是一个统计学里面的逻辑分析的讲解</div>
<div><a href="http://www.bio-info-trainee.com/tmp/tutorial_for_logical_analysis.html">http://www.bio-info-trainee.com/tmp/tutorial_for_logical_analysis.html</a></div>
<div>下面是一个表达矩阵的15个常见的可视化图形的制作：</div>
<div><a href="http://bio-info-trainee.com/tmp/basic_visualization_for_expression_matrix.html">http://bio-info-trainee.com/tmp/basic_visualization_for_expression_matrix.html</a></div>
<div></div>
<div>
<h1 class="title toc-ignore">用deconstructSigs来做cosmic的mutation signature图</h1>
</div>
<div><a href="http://biotrainee.com/jmzeng/markdown/deconstuctSigs.html" target="_blank">http://biotrainee.com/jmzeng/markdown/deconstuctSigs.html</a></div>
<div></div>
<div>这个史上最全方差分析，不是我写的，但是写的很赞，我就不多此一举了：</div>
<div><a href="http://biotrainee.com/jmzeng/markdown/ANOVA.html" target="_blank">http://biotrainee.com/jmzeng/markdown/ANOVA.html  </a>推荐大家看看</div>
<div></div>
<div>
<h1 class="title toc-ignore">标准的基因检测报告目录  <a href="http://www.biotrainee.com/jmzeng/blogMyGenome/name_introduction.html" target="_blank">http://www.biotrainee.com/jmzeng/blogMyGenome/name_introduction.html</a></h1>
</div>
<div></div>
<div></div>
<div></div>
<h1><strong><span style="color: #ff0000;">下面是一堆高通量测序分析的结题报告：</span></strong></h1>
<div></div>
<div> 简单 <span style="color: #6e8b3d;">RNA-seq</span> 项目结题报告</div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Ref_RNAseq_result/index.html" target="_blank">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Ref_RNAseq_result/index.html</a></div>
<div></div>
<div>
<div>16s rDNA 高变区测序 项目结题报告</div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/16sRNA/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/16sRNA/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/16sRNA/index.html">示范 宏基因组分析 结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/MetaGenome_result/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/MetaGenome_result/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/MetaGenome_result/index.html">示范 细菌基因组分析 结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Pacbio_Genome_result/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Pacbio_Genome_result/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Pacbio_Genome_result/index.html">示范 小RNA 项目结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/SmallRNA_result/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/SmallRNA_result/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/SmallRNA_result/index.html">示范 lncRNA 项目结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/lncRNA_result/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/lncRNA_result/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/lncRNA_result/index.html">示范ChIP-Seq结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/chip-report/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/chip-report/index.html</a></div>
<div></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/chip-report/index.html">示范 转录组测序（De novo） 项目结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Denovo_transcriptome/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Denovo_transcriptome/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/Denovo_transcriptome/index.html">示范 WGCNA分析 结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/WGCNA_Traits_result/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/WGCNA_Traits_result/index.html</a></div>
<div></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/WGCNA_Traits_result/index.html">蛋白iTRAQ定量分析 项目结题报告</a></div>
<div><a href="http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/iTRAQ_Result/index.html">http://www.biotrainee.com/jmzeng/html_report/d/e/e/p/i/n/iTRAQ_Result/index.html</a></div>
<div></div>
</div>
<div></div>
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		<title>从GEO数据库下载矩阵数据-可以直接进行下游分析</title>
		<link>http://www.bio-info-trainee.com/941.html</link>
		<comments>http://www.bio-info-trainee.com/941.html#comments</comments>
		<pubDate>Thu, 27 Aug 2015 13:26:05 +0000</pubDate>
		<dc:creator><![CDATA[ulwvfje]]></dc:creator>
				<category><![CDATA[R]]></category>
		<category><![CDATA[bioconductor]]></category>
		<category><![CDATA[GEOquery]]></category>

		<guid isPermaLink="false">http://www.bio-info-trainee.com/?p=941</guid>
		<description><![CDATA[bioconductor系列的包都是一样的安装方式： source("http: &#8230; <a href="http://www.bio-info-trainee.com/941.html">Continue reading <span class="meta-nav">&#8594;</span></a>]]></description>
				<content:encoded><![CDATA[<div>
<pre>bioconductor系列的包都是一样的安装方式：</pre>
<pre>source("http://bioconductor.org/biocLite.R")
    biocLite("GEOquery")</pre>
<p>以前GEO数据库主要是microarray的芯片数据，后来有了RNA-seq，如果同时做多个样品的RNA-seq，表达量矩阵后来也可以上传到GEO数据库里面，只有看到文献里面有提到GEO数据库，都可以通过这个R包俩进行批量下载，其实就是网页版的一个API调用而已：</p>
</div>
<div></div>
<div>GEO数据库里面有四种数据</p>
<div data-canvas-width="750.7327616000006">At the most basic level of organization of GEO, there are four basic entity types.</div>
<div data-canvas-width="750.7327616000006"> The first three (Sample, Platform, and Series) are supplied by users;</div>
<div data-canvas-width="750.7327616000006">the fourth, the dataset, is compiled and curated by GEO sta from the user-submitted data.</div>
<div data-canvas-width="750.7327616000006">GEO accession number (GPLxxx).<span class="Apple-converted-space"> </span></div>
<div data-canvas-width="750.7327616000006">GEO accession number (GSMxxx)</div>
<div data-canvas-width="750.7327616000006">GEO accession number (GSExxx).<span class="Apple-converted-space"> </span></div>
<div data-canvas-width="750.7327616000006">GEO DataSets (GDSxxx)</div>
<div data-canvas-width="750.7327616000006">记住大小关系：一个GDS可以有多个GSM，一个GSM可以有多个GSE，至于GPL，一般不接触的</div>
<div data-canvas-width="750.7327616000006">我们通常接触的都是GSE系列（一个GSE里面有多个GSM）的数据，而且这个包最重要的就是一个getGEO函数。</div>
<div data-canvas-width="750.7327616000006">只要你通过文献确定了你的检索号，就可以通过这个函数来下载啦</div>
<div data-canvas-width="750.7327616000006">
<div data-canvas-width="750.7327616000006">检索号一般是A character string representing a GEO object for download and</div>
<div data-canvas-width="750.7327616000006">          parsing.  (eg., 'GDS505','GSE2','GSM2','GPL96'</div>
<p>这个函数有很多参数，除非你需要下载的文件，那么就设置destdir到你喜欢的目录，如果只需要表达量数据就不用了。</p>
</div>
<div data-canvas-width="750.7327616000006"> getGEO(GEO = NULL, filename = NULL, destdir = tempdir(), GSElimits=NULL,</div>
<div data-canvas-width="750.7327616000006">     GSEMatrix=TRUE,AnnotGPL=FALSE)</div>
<div data-canvas-width="750.7327616000006">例如：</div>
<div data-canvas-width="750.7327616000006">gds &lt;- getGEO("GDS10") 会返回一个对象，而且下载数据一般会在tmp目录下面，当然如果你需要保存这些文件，你可以自己制定下载目录及文件名。</div>
<div data-canvas-width="750.7327616000006">gse2553 &lt;- getGEO("GSE2553")</div>
<div data-canvas-width="750.7327616000006">GDS2eSet函数可以把上面这个下载函数得到的对象(要确定是GDS而不是GSE)变成表达对象</div>
<div data-canvas-width="750.7327616000006">pData和exprs函数都可以处理上面这个表达对象，从而分别得到样品描述矩阵和样品表达量矩阵</div>
<div data-canvas-width="750.7327616000006">综合一起就是</div>
<div data-canvas-width="750.7327616000006">g4100 &lt;- GDS2eSet(getGEO("GDS4100"))<br />
g4102 &lt;- GDS2eSet(getGEO("GDS4102"))<br />
e4102&lt;-exprs(g4102)<br />
e4100&lt;-exprs(g4100)</div>
<div data-canvas-width="750.7327616000006">这样的代码，这个e4100和e4102就都是一个数值矩阵啦，可以进行下游分析，但是如果是下载的GSM数据</div>
<div data-canvas-width="750.7327616000006">就用下面这个代码，GSE26253_series_matrix.txt是通过GSEMatrix=TRUE这个参数特意下载到你的目录的</div>
<div data-canvas-width="750.7327616000006">expr_dat=read.table("GSE26253_series_matrix.txt",comment.char="!",stringsAsFactors=F)</div>
<div data-canvas-width="750.7327616000006">这样读取也是一个数值矩阵</div>
<div data-canvas-width="750.7327616000006">具体大家可以看这个包的说明书</div>
<div data-canvas-width="750.7327616000006">
<pre><code>#Download GDS file, put it in the current directory, and load it:
gds858 &lt;- getGEO('GDS858', destdir=".")
如果使用了GSEMatrix=TRUE这个参数，那么除了下载soft文件，还有表达量矩阵文件，可以直接用read.table读取那个文件。
#Or, open an existing GDS file (even if its compressed):
gds858 &lt;- getGEO(filename='GDS858.soft.gz')
下面这个下载的是GSE对象，GDS对象还有大一点</code></pre>
</div>
<div data-canvas-width="750.7327616000006"><a href="http://www.bio-info-trainee.com/wp-content/uploads/2015/08/GEOquery-下载结果gds对象.jpg"><img class="alignnone size-full wp-image-942" src="http://www.bio-info-trainee.com/wp-content/uploads/2015/08/GEOquery-下载结果gds对象.jpg" alt="GEOquery-下载结果gds对象" width="629" height="333" /></a></div>
<div data-canvas-width="750.7327616000006">参考：<a href="http://www2.warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/geo/">http://www2.warwick.ac.uk/fac/sci/moac/people/students/peter_cock/r/geo/</a></div>
<div data-canvas-width="750.7327616000006"></div>
</div>
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