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Less-is-more: Selecting Transcription Factor Binding Regions Informative for Motif Inference by Jinrui Xu; Jiahao Gao; Pengyu Ni; Mark Gerstein is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

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## Abstract Numerous statistical methods have emerged for inferring DNA motifs for transcription factors (TFs) from genomic regions. However, the process of selecting informative regions for motif inference remains understudied. Current approaches select regions with strong ChIP-seq signal for a given TF, assuming that such strong signal primarily results from specific interactions between the TF and its motif. Additionally, these selection approaches do not account for non-target motifs, i.e. motifs of other TFs; they presume the occurrence of these non-target motifs infrequent compared to that of the target motif, and thus assume these have minimal interference with the identification of the target. Leveraging extensive ChIP-seq datasets, we introduced the concept of TF signal ‘crowdedness’, referred to as C-score, for each genomic region. The C-score helps in highlighting TF signals arising from non-specific interactions. Moreover, by considering the C-score (and adjusting for the length of genomic regions), we can effectively mitigate interference of non-target motifs. Using these tools, we find that in many instances, strong ChIP-seq signal stems mainly from non-specific inter

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Author

Jinrui Xu; Jiahao Gao; Pengyu Ni; Mark Gerstein

Publisher

Oxford University Press

Published

2024

Language

EN

Field

Biochemistry, Genetics and Molecular Biology (Life Sciences)