TY - JOUR
T1 - Investigating open reading frames in known and novel transcripts using ORFanage
AU - Varabyou, Ales
AU - Erdogdu, Beril
AU - Salzberg, Steven L.
AU - Pertea, Mihaela
N1 - Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer Nature America, Inc.
PY - 2023/8
Y1 - 2023/8
N2 - ORFanage is a system designed to assign open reading frames (ORFs) to known and novel gene transcripts while maximizing similarity to annotated proteins. The primary intended use of ORFanage is the identification of ORFs in the assembled results of RNA-sequencing experiments, a capability that most transcriptome assembly methods do not have. Our experiments demonstrate how ORFanage can be used to find novel protein variants in RNA-seq datasets, and to improve the annotations of ORFs in tens of thousands of transcript models in the human annotation databases. Through its implementation of a highly accurate and efficient pseudo-alignment algorithm, ORFanage is substantially faster than other ORF annotation methods, enabling its application to very large datasets. When used to analyze transcriptome assemblies, ORFanage can aid in the separation of signal from transcriptional noise and the identification of likely functional transcript variants, ultimately advancing our understanding of biology and medicine.
AB - ORFanage is a system designed to assign open reading frames (ORFs) to known and novel gene transcripts while maximizing similarity to annotated proteins. The primary intended use of ORFanage is the identification of ORFs in the assembled results of RNA-sequencing experiments, a capability that most transcriptome assembly methods do not have. Our experiments demonstrate how ORFanage can be used to find novel protein variants in RNA-seq datasets, and to improve the annotations of ORFs in tens of thousands of transcript models in the human annotation databases. Through its implementation of a highly accurate and efficient pseudo-alignment algorithm, ORFanage is substantially faster than other ORF annotation methods, enabling its application to very large datasets. When used to analyze transcriptome assemblies, ORFanage can aid in the separation of signal from transcriptional noise and the identification of likely functional transcript variants, ultimately advancing our understanding of biology and medicine.
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U2 - 10.1038/s43588-023-00496-1
DO - 10.1038/s43588-023-00496-1
M3 - Article
C2 - 38098813
AN - SCOPUS:85166346883
SN - 2662-8457
VL - 3
SP - 700
EP - 708
JO - Nature Computational Science
JF - Nature Computational Science
IS - 8
ER -