Skip to main navigation Skip to search Skip to main content

The PinkThing for analysing ChIP profiling data in their genomic context

  • Fiona G. Nielsen
  • , Maarten Kooyman
  • , Philip Kensche
  • , Hendrik Marks
  • , Henk Stunnenberg
  • , Martijn Huynen

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

Background: Current epigenetic research makes frequent use of whole-genome ChIP profiling for determining the in vivo binding of proteins, e.g. transcription factors and histones, to DNA. Two important and recurrent questions for these large scale analyses are: 1) What is the genomic distribution of a set of binding sites? and 2) Does this genomic distribution differ significantly from another set of sites?. Findings. We exemplify the functionality of the PinkThing by analysing a ChIP profiling dataset of cohesin binding sites. We show the subset of cohesin sites with no CTCF binding have a characteristic genomic distribution different from the set of all cohesin sites. Conclusions: The PinkThing is a web application for fast and easy analysis of the context of genomic loci, such as peaks from ChIP profiling experiments. The output of the PinkThing analysis includes: categorisation of position relative to genes (intronic, exonic, 5' near, 3' near 5' far, 3' far and distant), distance to the closest annotated 3' and 5' end of genes, direction of transcription of the nearest gene, and the option to include other genomic elements like ESTs and CpG islands. The PinkThing enables easy statistical comparison between experiments, i.e. experimental versus background sets, reporting over- and underrepresentation as well as p-values for all comparisons. Access and use of the PinkThing is free and open (without registration) to all users via the website:.

Original languageEnglish
Article number133
JournalBMC Research Notes
Volume6
Issue number1
DOIs
Publication statusPublished - 2013
Externally publishedYes

Fingerprint

Dive into the research topics of 'The PinkThing for analysing ChIP profiling data in their genomic context'. Together they form a unique fingerprint.

Cite this