Computational cleaning of noisy 5' end tag sequencing data sets from rare in vivo cells

Authors

  • Johannes Eichler Waage Bioinformatics Centre, University of Copenhagen
  • Ilka Hoof Bioinformatics Centre, University of Copenhagen
  • Jette Bornholdt Bioinformatics Centre, University of Copenhagen
  • Esben Pedersen Biomedical Institute, BRIC, University of Copenhagen, Copenhagen
  • Mette Jørgesen Bioinformatics Centre, University of Copenhagen
  • Kim Theilgaard Biotech Research and Innovation Centre, University of Copenhagen
  • Cord Brakebusch Biomedical Institute, BRIC, University of Copenhagen, Copenhagen
  • Bo Porse The Finsen Laboratory, Rigshospitalet, Faculty of Health Sciences, University of Copenhagen, Copenhagen
  • Albin Sandelin Bioinformatics Centre, University of Copenhagen, Copenhagen

DOI:

https://doi.org/10.14806/ej.19.A.613

Keywords:

nanoCAGE, CAGE, promoterome, 5' end tag sequencing

Abstract

We present a data filtration and processing pipeline for analysis of nanoCAGE-seq, a variant of the CAGE method allowing for very small amounts of input material, and thus expanding the number of tissue- and cell types available for proteome profiling. For this inherently noisy method, rigorous filter methods, including tag clustering, cluster width and profile filtering, and variance filtering rescue bona fide promoters, allowing for detection of promoter usage, inter-sample promoter switching and detection of new putative promoters. We present result from nanoCAGE from two different studies.

Author Biography

  • Johannes Eichler Waage, Bioinformatics Centre, University of Copenhagen
    PhD-student, Bioinformatics Centre, Department of Biology, University of Copenhagen

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Published

2013-04-08

Issue

Vol. 19: Supplement A

Section

Posters

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