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    <title>Meta-Analysis on dennogumi.org</title>
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    <description>Recent content in Meta-Analysis on dennogumi.org</description>
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    <copyright>&amp;copy; 2026 Einar under a CC-BY-SA 4.0 license. Some images are AI-generated. Header design by [Melissa Adkins](https://melissaadkins.com) with [assets from Freepik](https://freepik.com).</copyright>
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      <title>Follow up on meta-analysis</title>
      <link>https://www.dennogumi.org/2008/02/follow-up-on-meta-analysis/</link>
      <pubDate>Thu, 28 Feb 2008 19:42:15 +0000</pubDate>
      
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      <description>&lt;p&gt;Fourteen days since my last post. Quite a while, indeed. Mostly I&amp;rsquo;ve been stumbled with work and some health related issues. Anyway, I thought I&amp;rsquo;d follow up on the meta analysis matter I discussed in my last post.&lt;/p&gt;&#xA;&lt;p&gt;It turns out that it&amp;rsquo;s a fault of both limma and the data sets, because apparently the raw data found in the Stanford Microarray Database have different length, gene-wise (a result of not all spots on the array being good?) and limma itself does need equal length tables to form a single object (I stumbled upon the same problem when doing my thesis, but I used a hack to work around it), and does not perform any checking.&lt;/p&gt;</description>
      
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    <item>
      <title>Meta analysis difficulty increasing</title>
      <link>https://www.dennogumi.org/2008/02/meta-analysis-difficulty-increasing/</link>
      <pubDate>Thu, 14 Feb 2008 20:17:09 +0000</pubDate>
      
      <guid>https://www.dennogumi.org/2008/02/meta-analysis-difficulty-increasing/</guid>
      <description>&lt;p&gt;Again in the past days I&amp;rsquo;ve been banging my head thanks to the fact that doing meta-analysis with microarray data is more difficult than what it seems.&lt;/p&gt;&#xA;&lt;p&gt;The problem sometimes lies in the data, sometimes lies in the analysis  software and sometimes in a combination of factors. When doing work on a public data set (Zhao et al., 2005), I had to start analysis from raw data. Now, I tried using both the limma and marray Bioconductor packages, but both of them bail out with cryptic error messages. From what I&amp;rsquo;ve learnt by googling around, it seems that R doesn&amp;rsquo;t like batch loading of tables of different length.&lt;/p&gt;</description>
      
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