ProSampler: an ultrafast and accurate motif finder in large ChIP-seq datasets for combinatory motif discovery

Author:

Li Yang12,Ni Pengyu2,Zhang Shaoqiang3,Li Guojun12,Su Zhengchang2ORCID

Affiliation:

1. School of Mathematics, Shandong University, Jinan 250100, China

2. Department of Bioinformatics and Genomics, College of Computing and Informatics, The University of North Carolina at Charlotte, Charlotte, NC 28223, USA

3. College of Computer and Information Engineering, Tianjin Normal University, Tianjin 300387, China

Abstract

Abstract Motivation The availability of numerous ChIP-seq datasets for transcription factors (TF) has provided an unprecedented opportunity to identify all TF binding sites in genomes. However, the progress has been hindered by the lack of a highly efficient and accurate tool to find not only the target motifs, but also cooperative motifs in very big datasets. Results We herein present an ultrafast and accurate motif-finding algorithm, ProSampler, based on a novel numeration method and Gibbs sampler. ProSampler runs orders of magnitude faster than the fastest existing tools while often more accurately identifying motifs of both the target TFs and cooperators. Thus, ProSampler can greatly facilitate the efforts to identify the entire cis-regulatory code in genomes. Availability and implementation Source code and binaries are freely available for download at https://github.com/zhengchangsulab/prosampler. It was implemented in C++ and supported on Linux, macOS and MS Windows platforms. Supplementary information Supplementary materials are available at Bioinformatics online.

Funder

National Science Foundation

NIH

National Natural Science Foundation of China

Natural Science Foundation of Tianjin Science and Technology Committee

National Science Foundation of China

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Reference34 articles.

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