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SEESAW: detecting isoform-level allelic imbalance accounting for inferential uncertainty.
Wu, Euphy Y; Singh, Noor P; Choi, Kwangbom; Zakeri, Mohsen; Vincent, Matthew; Churchill, Gary A; Ackert-Bicknell, Cheryl L; Patro, Rob; Love, Michael I.
Afiliação
  • Wu EY; Department of Biostatistics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
  • Singh NP; Department of Computer Science, University of Maryland, College Park, MD, USA.
  • Choi K; The Jackson Laboratory, Bar Harbor, ME, USA.
  • Zakeri M; Department of Computer Science, University of Maryland, College Park, MD, USA.
  • Vincent M; The Jackson Laboratory, Bar Harbor, ME, USA.
  • Churchill GA; The Jackson Laboratory, Bar Harbor, ME, USA.
  • Ackert-Bicknell CL; Department of Orthopedics, School of Medicine, University of Colorado, Anschutz Campus, Aurora, CO, USA.
  • Patro R; Department of Computer Science, University of Maryland, College Park, MD, USA.
  • Love MI; Department of Biostatistics, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA. michaelisaiahlove@gmail.com.
Genome Biol ; 24(1): 165, 2023 07 12.
Article em En | MEDLINE | ID: mdl-37438847
ABSTRACT
Detecting allelic imbalance at the isoform level requires accounting for inferential uncertainty, caused by multi-mapping of RNA-seq reads. Our proposed method, SEESAW, uses Salmon and Swish to offer analysis at various levels of resolution, including gene, isoform, and aggregating isoforms to groups by transcription start site. The aggregation strategies strengthen the signal for transcripts with high uncertainty. The SEESAW suite of methods is shown to have higher power than other allelic imbalance methods when there is isoform-level allelic imbalance. We also introduce a new test for detecting imbalance that varies across a covariate, such as time.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2023 Tipo de documento: Article