BMC Bioinformatics | |
SEAseq: a portable and cloud-based chromatin occupancy analysis suite | |
Modupeore O. Adetunji1  Brian J. Abraham1  | |
[1] Department of Computational Biology, St. Jude Children’s Research Hospital; | |
关键词: ChIP sequencing; CUT&RUN; Peak calling; Motif analysis; Cloud; Data analysis; | |
DOI : 10.1186/s12859-022-04588-z | |
来源: DOAJ |
【 摘 要 】
Abstract Background Genome-wide protein-DNA binding is popularly assessed using specific antibody pulldown in Chromatin Immunoprecipitation Sequencing (ChIP-Seq) or Cleavage Under Targets and Release Using Nuclease (CUT&RUN) sequencing experiments. These technologies generate high-throughput sequencing data that necessitate the use of multiple sophisticated, computationally intensive genomic tools to make discoveries, but these genomic tools often have a high barrier to use because of computational resource constraints. Results We present a comprehensive, infrastructure-independent, computational pipeline called SEAseq, which leverages field-standard, open-source tools for processing and analyzing ChIP-Seq/CUT&RUN data. SEAseq performs extensive analyses from the raw output of the experiment, including alignment, peak calling, motif analysis, promoters and metagene coverage profiling, peak annotation distribution, clustered/stitched peaks (e.g. super-enhancer) identification, and multiple relevant quality assessment metrics, as well as automatic interfacing with data in GEO/SRA. SEAseq enables rapid and cost-effective resource for analysis of both new and publicly available datasets as demonstrated in our comparative case studies. Conclusions The easy-to-use and versatile design of SEAseq makes it a reliable and efficient resource for ensuring high quality analysis. Its cloud implementation enables a broad suite of analyses in environments with constrained computational resources. SEAseq is platform-independent and is aimed to be usable by everyone with or without programming skills. It is available on the cloud at https://platform.stjude.cloud/workflows/seaseq and can be locally installed from the repository at https://github.com/stjude/seaseq .
【 授权许可】
Unknown