Aug 26, 2020 · In this investigation, we apply TOBIAS to ATAC-seq data from both human and mouse PD and show how visible TF footprints correlate with the timings of TF activity throughout development.

Apr 23, 2024 · Transcription factors (TFs) are crucial epigenetic regulators, which enable cells to dynamically adjust gene expression in response to environmental signals. Computational procedures like digital...

Jan 31, 2023 · We first compared maxATAC model performance to the most popular method of TFBS prediction, TF motif scanning in ATAC-seq peaks [35–38] (implementation described in S3 Fig and Methods). maxATAC outperformed standard motif …

Mar 21, 2024 · Finding multiple ATAC-seq motifs. ATAC-seq can reveal all opening chromatin, which means that there are multiple motifs in an ATAC-seq dataset. In this study, we developed the GNNMF model to find ATAC-seq motifs by employing the GNN and coexisting probability.

Apr 20, 2024 · Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation.

In this tutorial we use an R / Bioconductor packages ATACseqQC and MotifDb to detect TF binding signatures in ATAC-seq data. Please note this tutorial is merely an early attempt to determine whether TF bindng sites can be identified in ATAC-seq data, and not a statistical framework for TF footrpinting .

Feb 26, 2019 · We also evaluate motifs supported by Wellington footprints or motifs inside ATAC-seq peaks Footnote 4. We observe a number of TFs with statistically significant difference in activity between cDC1 and pDC (Fig 6 b; p value <0.05; t test).

Using public ATAC-seq data from a variety of human and mouse cell lines (IMR90, H524, NJH29, and BRG1 fl/fl) and perturbations (nutlin, doxycycline, and tamoxifen), we assessed changes in accessibility over all putative TF sequence recognition motifs (for all motifs within the HOCOMOCO database).

Aug 26, 2020 · TOBIAS is a collection of command-line tools utilizing a minimal input of ATAC-seq reads, TF motifs and genome information (Fig. 1b) to perform all levels of footprinting analysis including bias correction (Fig. 1c), footprinting (Fig. 1d), …

Oct 23, 2024 · Here we benchmark methods for differential TF activity inference from ATAC-seq. We curated a set of ATAC-seq datasets with replicates, profiling genome-wide accessibility upon perturbation (activation or repression) of a specific TF with …