TOM – 21.09.2016

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:

PeakXus code at GitHub:

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.

TOM – Course description


Usually starts at 15.30
Biomedicum 1

First things first, this meetings’ setting is a very casual one. We want to create a society for exchange of knowledge and ideas of people doing/interested in Bioinformatics/Applied Statistics. The idea is to bring them together and we hope that this will be beneficial for all of us.

Tool Of the Month (TOM) is a platform to discuss the various tools and methods that we use in our research. We can discuss various bioinformatics algorithms, softwares, packages in R/Python/Perl/any-of-your-favourite-language. And if you want to talk about your research that’s even better!

Each time we meet, we will have one or two talks about a method/tool/idea in a format the that can be freely decided by the presenter. And if you want to continue the exciting conversation with the eclectic crowd, feel free to take it to nearby restaurants/pubs. What’s more, you can receive credits, by only presenting once and actively participating to TOM meetings!


Students can obtain credits from presenting and/or attending TOM-meetings as follows:
a) attending 6 meetings & filling the feedback form =1 cr
b) doing a) and giving a presentation = 2 cr

Attendances do not all have to be from the same year
Credits can be registered after each spring term


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