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content/post/2008-02-14-meta-analysis-difficulty-increasing.markdown

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+---
+author: einar
+categories:
+- Science
+comments: true
+date: "2008-02-14T20:17:09Z"
+header:
+  image_fullwidth: banner_other.jpg
+slug: meta-analysis-difficulty-increasing
+tags:
+- meta-analysis
+- microarray
+- Science
+title: Meta analysis difficulty increasing
+disable_share: true
+wordpress_id: 377
+---
+
+Again in the past days I've been banging my head thanks to the fact that doing meta-analysis with microarray data is more difficult than what it seems.
+
+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've learnt by googling around, it seems that R doesn't like batch loading of tables of different length.
+
+I have 177 samples and I **have** to normalize them all together. Apparently this is a quirk of marray and limma (or worse, R itself) which is preventing me to work properly. And this is not the first time it happens, either: in the past year I've lost a lot of time dealing with software issues rather than performing real analsis. The problem has been posted already on some R mailing lists (and on BioC, too), but judging from the responses I doubt I'll see a solution.
+
+I guess I'll have to work around this somehow (and of course, this doesn't improve the idea I have of R...).