Exhaustive Search for Over-represented DNA Sequence Motifs with CisFinder

We present CisFinder software, which generates a comprehensive list of motifs enriched in a set of DNA sequences and describes them with position frequency matrices (PFMs). A new algorithm was designed to estimate PFMs directly from counts of n-mer words with and without gaps; then PFMs are extended...

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Bibliographic Details
Published in:DNA research Vol. 16; no. 5; pp. 261 - 273
Main Authors: Sharov, Alexei A., Ko, Minoru S.H.
Format: Journal Article
Language:English
Published: Oxford Oxford University Press 01.10.2009
Subjects:
Algorithms
Amino Acid Motifs
Animals
Base Sequence
Binding Sites
Biological and medical sciences
Computational Biology - methods
Embryonic Stem Cells - metabolism
Fundamental and applied biological sciences. Psychology
Genes. Genome
Genetics of eukaryotes. Biological and molecular evolution
Molecular and cellular biology
Molecular genetics
Pluripotent Stem Cells - metabolism
Position-Specific Scoring Matrices
Software
Transcription Factors - metabolism
ChIP-seq
transcription factor binding site
software
embryonic stem cells
algorithm
Nucleotide sequence
Embryonic cell
Stem cell
Software
Binding site
Transcription factor
Chip
Algorithm
ISSN:1340-2838, 1756-1663, 1756-1663
Online Access:Get full text
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Summary:We present CisFinder software, which generates a comprehensive list of motifs enriched in a set of DNA sequences and describes them with position frequency matrices (PFMs). A new algorithm was designed to estimate PFMs directly from counts of n-mer words with and without gaps; then PFMs are extended over gaps and flanking regions and clustered to generate non-redundant sets of motifs. The algorithm successfully identified binding motifs for 12 transcription factors (TFs) in embryonic stem cells based on published chromatin immunoprecipitation sequencing data. Furthermore, CisFinder successfully identified alternative binding motifs of TFs (e.g. POU5F1, ESRRB, and CTCF) and motifs for known and unknown co-factors of genes associated with the pluripotent state of ES cells. CisFinder also showed robust performance in the identification of motifs that were only slightly enriched in a set of DNA sequences.
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ISSN:1340-2838
1756-1663
1756-1663
DOI:10.1093/dnares/dsp014