Using ChIPMotifs for de novo motif discovery of OCT4 and ZNF263 based on ChIP-based high-throughput experiments

Brian A. Kennedy, Xun Lan, Tim H.M. Huang, Peggy J. Farnham, Victor X. Jin

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations

Abstract

DNA motifs are short sequences varying from 6 to 25 bp and can be highly variable and degenerated. One major approach for predicting transcription factor (TF) binding is using position weight matrix (PWM) to represent information content of regulatory sites; however, when used as the sole means of identifying binding sites suffers from the limited amount of training data available and a high rate of false-positive predictions. ChIPMotifs program is a de novo motif finding tool developed for ChIP-based high-throughput data, and W-ChIPMotifs is a Web application tool for ChIPMotifs. It composes various ab initio motif discovery tools such as MEME, MaMF, Weeder and optimizes the significance of the detected motifs by using bootstrap re-sampling error estimation and a Fisher test. Using these techniques, we determined a PWM for OCT4 which is similar to canonical OCT4 consensus sequence. In a separate study, we also use de novo motif discovery to suggest that ZNF263 binds to a 24-nt site that differs from the motif predicted by the zinc finger code in several positions.

Original languageEnglish (US)
Title of host publicationNext Generation Microarray Bioinformatics
Subtitle of host publicationMethods and Protocols
EditorsJunbai Wang, Tianhai Tian, Aik Choon Tan
Pages323-334
Number of pages12
DOIs
StatePublished - Jan 2 2012
Externally publishedYes

Publication series

NameMethods in Molecular Biology
Volume802
ISSN (Print)1064-3745

Keywords

  • ChIP
  • Motif
  • OCT4
  • Position weight matrix
  • ZNF263

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

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  • Cite this

    Kennedy, B. A., Lan, X., Huang, T. H. M., Farnham, P. J., & Jin, V. X. (2012). Using ChIPMotifs for de novo motif discovery of OCT4 and ZNF263 based on ChIP-based high-throughput experiments. In J. Wang, T. Tian, & A. C. Tan (Eds.), Next Generation Microarray Bioinformatics: Methods and Protocols (pp. 323-334). (Methods in Molecular Biology; Vol. 802). https://doi.org/10.1007/978-1-61779-400-1_21