Understanding the hierarchy of your GO Terms subset

By |2023-11-08T09:54:32+00:00April 7th, 2011|Categories: BioinfoTips|Tags: , , , , |

The other day I downloaded the cancer-affected Gene Ontology (GO) terms from IntOGen for up- and down-regulation via it's Biomart interface for a few tissues. Since was only interested in the GO Cell Compartment terms, so I directly added a filter file containing all the GO CC Terms as a filter for the Biomart export. So then... what do you do when you have a list of GO terms? Already if it is only 100 GO terms, it is quite hard to get an idea which are the affected compartments. To understand better you have to identify the more general terms that are affected. Here I explain quickly how I solved this problem and share it with you.

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Basic and intuitive analysis of microarray datasets using Gitools (Part 1)

By |2023-11-08T09:54:32+00:00March 16th, 2011|Categories: BioinfoTips|Tags: , , , , , , |

After preparing some tutorials for our software, I thought it would be useful to show how basic analyses on microarray data can be carried out using Gitools. [...]

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Visualized ChIP & ChIPseq protocol

By |2023-11-08T09:54:32+00:00January 25th, 2011|Categories: BioinfoTips|Tags: , , |

[hana-flv-player video=”http://bg.upf.edu/blog/videos/JoVE_2101_Benevolenskaya.flv” width=”400″ height=”330″ description=”” player=”4″ autoload=”true” autoplay=”false” loop=”false” autorewind=”true” /] ChIP-seq (Chromatin Immunoprecipitation-and-Sequencing) has become a popular technique to find de novo and genome-wide binding sites [...]

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