Your browser doesn't support javascript.
loading
Retained introns in long RNA-seq reads are not reliably detected in sample-matched short reads.
David, Julianne K; Maden, Sean K; Wood, Mary A; Thompson, Reid F; Nellore, Abhinav.
Afiliación
  • David JK; Computational Biology Program, Oregon Health & Science University, Portland, OR, USA.
  • Maden SK; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
  • Wood MA; Base5 Genomics, Inc., Mountain View, CA, USA.
  • Thompson RF; Computational Biology Program, Oregon Health & Science University, Portland, OR, USA.
  • Nellore A; Department of Biomedical Engineering, Oregon Health & Science University, Portland, OR, USA.
Genome Biol ; 23(1): 240, 2022 11 11.
Article en En | MEDLINE | ID: mdl-36369064
BACKGROUND: There is growing interest in retained introns in a variety of disease contexts including cancer and aging. Many software tools have been developed to detect retained introns from short RNA-seq reads, but reliable detection is complicated by overlapping genes and transcripts as well as the presence of unprocessed or partially processed RNAs. RESULTS: We compared introns detected by 8 tools using short RNA-seq reads with introns observed in long RNA-seq reads from the same biological specimens. We found significant disagreement among tools (Fleiss' [Formula: see text]) such that 47.7% of all detected intron retentions were not called by more than one tool. We also observed poor performance of all tools, with none achieving an F1-score greater than 0.26, and qualitatively different behaviors between general-purpose alternative splicing detection tools and tools confined to retained intron detection. CONCLUSIONS: Short-read tools detect intron retention with poor recall and precision, calling into question the completeness and validity of a large percentage of putatively retained introns called by commonly used methods.
Asunto(s)
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Empalme Alternativo Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Empalme Alternativo Idioma: En Revista: Genome Biol Asunto de la revista: BIOLOGIA MOLECULAR / GENETICA Año: 2022 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Reino Unido