{"doi":"10.1101/2022.08.20.504634","title":"Comparison of\n                  <i>de novo</i>\n                  and reference genome-based transcriptome assembly pipelines for differential expression analysis of RNA sequencing data","abstract":"<jats:title>Abstract</jats:title>\n                <jats:sec>\n                  <jats:title>Objective</jats:title>\n                  <jats:p>\n                    As sequencing technologies become more accessible and bioinformatic tools improve, genomic resources are increasingly available for non-model species. Using a draft genome to guide transcriptome assembly from RNA sequencing data, rather than performing assembly\n                    <jats:italic>de novo</jats:italic>\n                    , affects downstream analyses. Yet, direct comparisons of these approaches are rare. Here, we compare the results of the standard\n                    <jats:italic>de novo</jats:italic>\n                    assembly pipeline (‘Trinity’) and two reference genome-based pipelines (‘Tuxedo’ and the ‘new Tuxedo’) for differential expression and gene ontology enrichment analysis of a companion study on Atlantic cod (\n                    <jats:italic>Gadus morhua</jats:italic>\n                    ).\n                  </jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>The new Tuxedo pipeline produced a higher quality assembly than the Tuxedo suite. However, greater enrichment of Trinity-identified differentially expressed genes suggests that a higher proportion of them represent biologically meaningful differences in transcription, as opposed to transcriptional noise or false positives. Coupled with the ability to annotate novel loci, the increased sensitivity of the Trinity pipeline might make it preferable over the reference genome-based approaches for studies aimed at broadly characterizing variation in the magnitude of expression differences and biological processes. However, the ‘new Tuxedo’ pipeline might be appropriate when a more conservative approach is warranted, such as for the identification of candidate genes.</jats:p>\n                </jats:sec>","journal":null,"year":null,"id":634307,"datarank":0.16479184330021646,"base_score":1.0986122886681096,"endowment":1.0986122886681096,"self_citation_contribution":0.16479184330021646,"citation_network_contribution":0.0,"self_endowment_contribution":0.16479184330021646,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":2,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1645023,"name":"Halvor Knutsen","orcid":"0000-0002-7627-7634","position":1,"is_corresponding":false},{"id":1645025,"name":"Esben M. Olsen","orcid":"0000-0003-3807-7524","position":2,"is_corresponding":false},{"id":1645027,"name":"Sissel Jentoft","orcid":"0000-0001-8707-531X","position":3,"is_corresponding":false},{"id":342887,"name":"Nils Chr. Stenseth","orcid":"0000-0002-1591-5399","position":4,"is_corresponding":false},{"id":1645028,"name":"Jeffrey A. Hutchings","orcid":"0000-0003-1572-5429","position":5,"is_corresponding":false},{"id":230470,"name":"Rebekah A. Oomen","orcid":"0000-0002-2094-5592","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Comparison of\n                  <i>de novo</i>\n                  and reference genome-based transcriptome assembly pipelines for differential expression analysis of RNA sequencing data","abstract":"<jats:title>Abstract</jats:title>\n                <jats:sec>\n                  <jats:title>Objective</jats:title>\n                  <jats:p>\n                    As sequencing technologies become more accessible and bioinformatic tools improve, genomic resources are increasingly available for non-model species. Using a draft genome to guide transcriptome assembly from RNA sequencing data, rather than performing assembly\n                    <jats:italic>de novo</jats:italic>\n                    , affects downstream analyses. Yet, direct comparisons of these approaches are rare. Here, we compare the results of the standard\n                    <jats:italic>de novo</jats:italic>\n                    assembly pipeline (‘Trinity’) and two reference genome-based pipelines (‘Tuxedo’ and the ‘new Tuxedo’) for differential expression and gene ontology enrichment analysis of a companion study on Atlantic cod (\n                    <jats:italic>Gadus morhua</jats:italic>\n                    ).\n                  </jats:p>\n                </jats:sec>\n                <jats:sec>\n                  <jats:title>Results</jats:title>\n                  <jats:p>The new Tuxedo pipeline produced a higher quality assembly than the Tuxedo suite. However, greater enrichment of Trinity-identified differentially expressed genes suggests that a higher proportion of them represent biologically meaningful differences in transcription, as opposed to transcriptional noise or false positives. Coupled with the ability to annotate novel loci, the increased sensitivity of the Trinity pipeline might make it preferable over the reference genome-based approaches for studies aimed at broadly characterizing variation in the magnitude of expression differences and biological processes. However, the ‘new Tuxedo’ pipeline might be appropriate when a more conservative approach is warranted, such as for the identification of candidate genes.</jats:p>\n                </jats:sec>","is_dataset_classified":null,"base_score":0.0,"endowment":0.0,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"19910364","pmcid":null,"openalex_id":null,"authors":[],"funders":[{"funder_name":"Natural Sciences and Engineering Research Council of Canada","grant_id":"unidentified","title":"unidentified"}],"total_grants":1,"fwci":null,"citation_percentile":null,"influential_citations":0,"citation_trend":[],"oa_status":"green","license":"cc-by-nc-nd","oa_locations":[{"url":"https://www.biorxiv.org/content/biorxiv/early/2022/08/22/2022.08.20.504634.full.pdf","host_type":"repository"},{"url":"https://syndication.highwire.org/content/doi/10.1101/2022.08.20.504634","host_type":"publisher"},{"url":"https://doi.org/10.1101/2022.08.20.504634","host_type":""}],"fields_of_study":["0301 basic medicine","03 medical and health sciences","0206 medical engineering","02 engineering and technology"],"mesh_terms":[],"keywords":[],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-08-06T13:28:11.624159Z","pmid":null,"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":[]}