{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mucaki EJ"],"funding":["Natural Sciences and Engineering Research Council of Canada","Canadian Institutes of Health Research (CA)","Canada Foundation for Innovation","Canadian Institutes of Health Research"],"pagination":["1023"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12486589"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["23(1)"],"pubmed_abstract":["<h4>Background</h4>Formalin-fixed paraffin embedded (FFPE) samples suffer from the degradation of nucleic acids, a problem that becomes particularly acute with samples stored for extended periods. It remains challenging to profile FFPE using high-throughput sequencing technologies including RNA-sequencing, and the resulting FFPE RNA-seq (fRNA-seq) data has a high rate of transcript dropout, a property shared with single cell RNA-seq. Transcript counts also have high variance and are prone to extreme values, together making downstream analyses extremely challenging.<h4>Methods</h4>We introduce the PaRaffin Embedded Formalin-FixEd Cleaning Tool (PREFFECT), a probabilistic framework for the analysis of fRNA-seq data. PREFFECT uses generative models to fit distributions to observed expression "],"journal":["Journal of translational medicine"],"pubmed_title":["Generative and integrative modeling for transcriptomics with formalin fixed paraffin embedded material."],"pmcid":["PMC12486589"],"funding_grant_id":["RGPIN-2018-050","391682","43481"],"pubmed_authors":["Mucaki EJ","Zhang W","Saha A","Dumeaux V","Trebinjac S","Rakovitch E","Hallett MT","Nofech-Mozes S"],"additional_accession":[]},"is_claimable":false,"name":"Generative and integrative modeling for transcriptomics with formalin fixed paraffin embedded material.","description":"<h4>Background</h4>Formalin-fixed paraffin embedded (FFPE) samples suffer from the degradation of nucleic acids, a problem that becomes particularly acute with samples stored for extended periods. It remains challenging to profile FFPE using high-throughput sequencing technologies including RNA-sequencing, and the resulting FFPE RNA-seq (fRNA-seq) data has a high rate of transcript dropout, a property shared with single cell RNA-seq. Transcript counts also have high variance and are prone to extreme values, together making downstream analyses extremely challenging.<h4>Methods</h4>We introduce the PaRaffin Embedded Formalin-FixEd Cleaning Tool (PREFFECT), a probabilistic framework for the analysis of fRNA-seq data. PREFFECT uses generative models to fit distributions to observed expression ","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Sep","modification":"2026-06-04T01:27:03.089Z","creation":"2026-05-03T03:14:12.241Z"},"accession":"S-EPMC12486589","cross_references":{"pubmed":["41029822"],"doi":["10.1186/s12967-025-07031-y"]}}