---
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
omit_header_text: true
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...).
