Mahmoud M Ibrahim1, Scott A Lacadie2, Uwe Ohler1. 1. Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany. 2. Department of Biology, Humboldt University, Invalidenstrasse 43, D-10115 Berlin, Germany and The Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine Berlin-Buch, Robert Rössle Str. 10, Berlin 13125, Germany.
Abstract
MOTIVATION: Although peak finding in next-generation sequencing (NGS) datasets has been addressed extensively, there is no consensus on how to analyze and process biological replicates. Furthermore, most peak finders do not focus on accurate determination of enrichment site widths and are not widely applicable to different types of datasets. RESULTS: We developed JAMM (Joint Analysis of NGS replicates via Mixture Model clustering): a peak finder that can integrate information from biological replicates, determine enrichment site widths accurately and resolve neighboring narrow peaks. JAMM is a universal peak finder that is applicable to different types of datasets. We show that JAMM is among the best performing peak finders in terms of site detection accuracy and in terms of accurate determination of enrichment sites widths. In addition, JAMM's replicate integration improves peak spatial resolution, sorting and peak finding accuracy. AVAILABILITY AND IMPLEMENTATION: JAMM is available for free and can run on Linux machines through the command line: http://code.google.com/p/jamm-peak-finder.
MOTIVATION: Although peak finding in next-generation sequencing (NGS) datasets has been addressed extensively, there is no consensus on how to analyze and process biological replicates. Furthermore, most peak finders do not focus on accurate determination of enrichment site widths and are not widely applicable to different types of datasets. RESULTS: We developed JAMM (Joint Analysis of NGS replicates via Mixture Model clustering): a peak finder that can integrate information from biological replicates, determine enrichment site widths accurately and resolve neighboring narrow peaks. JAMM is a universal peak finder that is applicable to different types of datasets. We show that JAMM is among the best performing peak finders in terms of site detection accuracy and in terms of accurate determination of enrichment sites widths. In addition, JAMM's replicate integration improves peak spatial resolution, sorting and peak finding accuracy. AVAILABILITY AND IMPLEMENTATION: JAMM is available for free and can run on Linux machines through the command line: http://code.google.com/p/jamm-peak-finder.
Authors: Sascha H C Duttke; Scott A Lacadie; Mahmoud M Ibrahim; Christopher K Glass; David L Corcoran; Christopher Benner; Sven Heinz; James T Kadonaga; Uwe Ohler Journal: Mol Cell Date: 2015-01-29 Impact factor: 17.970
Authors: Kelly P Stanton; Jiaqi Jin; Roy R Lederman; Sherman M Weissman; Yuval Kluger Journal: Nucleic Acids Res Date: 2017-12-01 Impact factor: 16.971
Authors: Florian Schmidt; Alexander Marx; Nina Baumgarten; Marie Hebel; Martin Wegner; Manuel Kaulich; Matthias S Leisegang; Ralf P Brandes; Jonathan Göke; Jilles Vreeken; Marcel H Schulz Journal: Nucleic Acids Res Date: 2021-10-11 Impact factor: 16.971