---
author: einar
categories:
- Science
comments: true
date: "2007-10-09T20:00:23Z"
header:
  image_fullwidth: banner_other.jpg
slug: soft-file-woes
tags:
- bioinformatics
- python
- R
- Science
- software
title: SOFT file woes
omit_header_text: true
disable_share: true
wordpress_id: 298
---

Today I started working on a data set published on [GEO](http://www.ncbi.nlm.nih.gov/geo/). As the sample data were somehow inconsistent (they mentioned 23 controls when I found 28), I decided to parse the [SOFT](http://www.ncbi.nlm.nih.gov/projects/geo/info/soft2.html#SOFTformat) file from GEO in order to get the exact sample information.

I did a grave mistake. First of all, [Biopython](http://www.biopython.org)'s SOFT parser is horribly broken (doesn't work at all) and quite undocumented: I could work around the lack of documentation (API docs) but not with the fact that it wouldn't work. So I turned to [R](http://www.r-project.org), which offers a GEO query module through [Bioconductor](http://www.bioconductor.org).

Again that proved to be a terrible mistake. For a file containing 183 samples, the analysis is going on since **four hours** and with no sign of completing anytime soon (not to mention a  possible memory leak). After this, I gave up. I'm going to get the reduced data sheet and write a small parser in Python myself.

What is frustrating is the lack of quality: I could concentrate on my own work rather than reinventing the wheel for the nth time if the existing implementations worked. What's the point in releasing non-working software? I could understand bugs, but this is one step further.
