ArticleBMC bioinformatics2022
SEAseq: a portable and cloud-based chromatin occupancy analysis suite.
Article in BMC bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
- 3D-super-enhancers are condensate-associated cis-regulatory communities.Nucleic acids research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundGenome-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.
resultsWe 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.
conclusionsThe 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 .
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.