Venue: Biomedicum 1, Meeting room 10
Timing: 15:30 onwards
Presenter: Tuomo Hartonen, PhD student
Transcription factor binding site discovery from ChIP-exo and ChIP-nexus data
Novel chromatin immunoprecipitation (ChIP) experiments ChIP-nexus and ChIP-exo allow studying transcription factor binding with unprecedented accuracy. True transcription factor binding locations are separated from noise by peak calling softwares.
Most peak calling softwares search binding events by creating a model of “true” peaks from the sites with highest enrichment in the ChIP experiments and then accepting only the peaks resembling this model. It is however known that most transcription factors bind cooperatively with other factors, form dimers or interact with other proteins. Moreover, the currently most used approach to predict transcription factor binding sites with simple Position Weight Matrix (PWM) models dos not explain all binding that is observed in vivo. These different types of binding create different ChIP-nexus/exo fingerprints. Fitting the peaks to just one model may lead to missing important binding events.
PeakXus is a peak caller specifically designed to leverage the increased resolution of ChIP-nexus/exo experiments. PeakXus is developed with the aim of making as few assumptions of the data as possible to allow novel discoveries. PeakXus supports use of Unique Molecular Identifiers (UMI) to remove PCR-duplicates that can create artefacts closely resembling true ChIP-nexus/exo binding events. We show that PeakXus consistently finds more peaks overlapping with transcription factor specific PWM-hits than published methods.
I will try to give a clear introduction to the topic so that also those who are not so familiar with the ChIP experiments are able to follow. I will compare the ChIP-exo/nexus protocols to ChIP-seq in order to highlight applications where the novel experiments are more suitable (for example allele specific binding analysis). I will also briefly explain the kind of output the algorithm provides.
PeakXus is published at: http://bioinformatics.oxfordjournals.org/content/32/17/i629.short
PeakXus code at GitHub: https://github.com/hartonen/PeakXus
Other useful references for those who are interested in reading more:
He et al. (2015). ChIP-Nexus enables improved detection of in vivo transcription factor binding footprints. Nature biotechnology.
Rhee & Pugh (2011). Comprehensive genome-wide protein-DNA interactions detected at single-nucleotide resolution. Cell.
Kivioja et al. (2012). Counting absolute numbers of molecules using unique molecular identifiers. Nature methods.