PLoS Comput Biol. 2022 Jun 7;18(6):e1009773. doi: 10.1371/journal.pcbi.1009773. Online ahead of print.
ABSTRACT
BACKGROUND: Transcription factor (TF) regulates the transcription of DNA to messenger RNA by binding to upstream sequence motifs. Identifying the locations of known motifs in whole genomes is computationally intensive.
METHODOLOGY/PRINCIPAL FINDINGS: This study presents a computational tool, named “Grit”, for screening TF-binding sites (TFBS) by coordinating transcription factors to their promoter sequences in orthologous genes. This tool employs a newly developed mixed Student’s t-test statistical method that detects high-scoring binding sites utilizing conservation information among species. The program performs sequence scanning at a rate of 3.2 Mbp/s on a quad-core Amazon server and has been benchmarked by the well-established ChIP-Seq datasets, putting Grit amongst the top-ranked TFBS predictors. It significantly outperforms the well-known transcription factor motif scanning tools, Pscan (4.8%) and FIMO (17.8%), in analyzing well-documented ChIP-Atlas human genome Chip-Seq datasets.
SIGNIFICANCE: Grit is a good alternative to current available motif scanning tools.
PMID:35671296 | DOI:10.1371/journal.pcbi.1009773
