{"doi":"10.12688/f1000research.14880.4","title":"SeqAcademy: an educational pipeline for RNA-Seq and ChIP-Seq analysis","abstract":" Quantification of gene expression and characterization of gene transcript structures are central problems in molecular biology. RNA sequencing (RNA-Seq) and chromatin immunoprecipitation sequencing (ChIP-Seq) are important methods, but can be cumbersome and difficult for beginners to learn. To teach interested students and scientists how to analyze RNA-Seq and ChIP-Seq data, we present a start-to-finish tutorial for analyzing RNA-Seq and ChIP-Seq data: SeqAcademy ( source code: https://github.com/NCBI-Hackathons/seqacademy , webpage: http://www.seqacademy.org/ ). This user-friendly pipeline, fully written in markdown language, emphasizes the use of publicly available RNA-Seq and ChIP-Seq data and strings together popular tools that bridge that gap between raw sequencing reads and biological insight. We demonstrate practical and conceptual considerations for various RNA-Seq and ChIP-Seq analysis steps with a biological use case - a previously published yeast experiment. This work complements existing sophisticated RNA-Seq and ChIP-Seq pipelines designed for advanced users by gently introducing the critical components of RNA-Seq and ChIP-Seq analysis to the novice bioinformatician. In conclusion, this well-documented pipeline will introduce state-of-the-art RNA-Seq and ChIP-Seq analysis tools to beginning bioinformaticians and help facilitate the analysis of the burgeoning amounts of public RNA-Seq and ChIP-Seq data. ","journal":"F1000Research","year":2020,"id":83895,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":10,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9567,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":430923,"name":"Olaitan I. Awe","orcid":"0000-0002-4257-3611","position":1,"is_corresponding":false},{"id":345042,"name":"Thomas Bütler","orcid":"0000-0003-3180-9868","position":2,"is_corresponding":false},{"id":431562,"name":"Tamiru Denka","orcid":null,"position":3,"is_corresponding":false},{"id":430924,"name":"Stephen A. Semick","orcid":"0000-0001-8100-2312","position":4,"is_corresponding":false},{"id":430925,"name":"Wanhu Tang","orcid":"0000-0001-9887-6905","position":5,"is_corresponding":false},{"id":430926,"name":"Ben Busby","orcid":"0000-0001-5267-4988","position":6,"is_corresponding":false},{"id":430922,"name":"Syed Hussain Ather","orcid":"0000-0002-2691-5589","position":0,"is_corresponding":true}],"reference_count":31,"raw_metadata":null,"created_at":"2026-07-18T21:54:32.422022Z","pmid":"33014338","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}