Modupeore O. Adetunji, PhD Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA Brian J. Abraham, PhD Department of Computational Biology, St. Jude Children's Research Hospital, Memphis, TN, 38105, USA
Poster not on display
Epigenomic Next Generation Sequencing experiments typically generate high-throughput sequencing data that necessitate the use of sophisticated, computationally intensive genomic tools to make discoveries, but these tools often have a high barrier to use because of computational resource constraints. Here, we present a comprehensive, infrastructure-independent, computational pipeline, called SEAseq for single-end chromatin antibody pull-down sequencing data and PEAseq for paired-end, which leverages field-standard, open-source tools for processing and analyzing ChIP-Seq/CUT&RUN data. S(P)EAseq performs extensive analyses from the raw output of the experiment, including alignment, peak calling, motif analysis, read coverage profiling, clustered peak (e.g. super-enhancer) identification, and quality assessment metrics, as well as automatic interfacing with data in GEO/SRA. To facilitate the broadest usage of our pipeline, S(P)EAseq can be executed on a single computer/server or HPC using the compatible execution engines, or via a secure cloud interface empowering researchers with either little to no computational skills or resources the flexibility to implement this invaluable resource. The easy-to-use and versatile format of S(P)EAseq makes it a reliable and efficient resource for ensuring high-quality ChIP-Seq analysis. ----------------
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