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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "InPAS" in publications use:'
type: software
license: GPL-2.0-or-later
title: 'InPAS: Identify Novel Alternative PolyAdenylation Sites (PAS) from RNA-seq
  data'
version: 2.20.0
doi: 10.31083/j.fbs1604021
identifiers:
- type: doi
  value: 10.32614/CRAN.package.InPAS
abstract: Alternative polyadenylation (APA) is one of the important post- transcriptional
  regulation mechanisms which occurs in most human genes. InPAS facilitates the discovery
  of novel APA sites and the differential usage of APA sites from RNA-Seq data. It
  leverages cleanUpdTSeq to fine tune identified APA sites by removing false sites.
authors:
- family-names: Ou
  given-names: Jianhong
  email: jou@morgridge.org
- family-names: Liu
  given-names: Haibo
  email: haibo.liu@umassmed.edu
- family-names: Zhu
  given-names: Lihua Julie
  email: Julie.Zhu@umassmed.edu
- family-names: Park
  given-names: Sungmi M.
- family-names: Green
  given-names: Michael R.
preferred-citation:
  type: article
  title: 'InPAS: An R/Bioconductor Package for Identifying Novel Polyadenylation Sites
    and Alternative Polyadenylation from Bulk RNA-seq Data'
  authors:
  - family-names: Ou
    given-names: Jianhong
    email: jou@morgridge.org
  - family-names: Liu
    given-names: Haibo
    email: haibo.liu@umassmed.edu
  - family-names: Park
    given-names: Sungmi
  - family-names: Green
    given-names: Michael R.
  - family-names: Zhu
    given-names: Lihua Julie
    email: Julie.Zhu@umassmed.edu
  journal: FBS
  volume: '16'
  year: '2024'
  issue: '4'
  url: https://www.imrpress.com/journal/FBS/16/4/10.31083/j.fbs1604021
  doi: 10.31083/j.fbs1604021
  issn: 1945-0516
  abstract: 'Background: Alternative cleavage and polyadenylation (APA) is a crucial
    post-transcriptional gene regulation mechanism that regulates gene expression
    in eukaryotes by increasing the diversity and complexity of both the transcriptome
    and proteome. Despite the development of more than a dozen experimental methods
    over the last decade to identify and quantify APA events, widespread adoption
    of these methods has been limited by technical, financial, and time constraints.
    Consequently, APA remains poorly understood in most eukaryotes. However, RNA sequencing
    (RNA-seq) technology has revolutionized transcriptome profiling and recent studies
    have shown that RNA-seq data can be leveraged to identify and quantify APA events.
    Results: To fully capitalize on the exponentially growing RNA-seq data, we developed
    InPAS (Identification of Novel alternative PolyAdenylation Sites), an R/Bioconductor
    package for accurate identification of novel and known cleavage and polyadenylation
    sites (CPSs), as well as quantification of APA from RNA-seq data of various experimental
    designs. Compared to other APA analysis tools, InPAS offers several important
    advantages, including the ability to detect both novel proximal and distal CPSs,
    to fine tune positions of CPSs using a naive Bayes classifier based on flanking
    sequence features, and to identify APA events from RNA-seq data of complex experimental
    designs using linear models. We benchmarked the performance of InPAS and other
    leading tools using simulated and experimental RNA-seq data with matched 3''-end
    RNA-seq data. Our results reveal that InPAS frequently outperforms existing tools
    in terms of precision, sensitivity, and specificity. Furthermore, we demonstrate
    its scalability and versatility by applying it to large, diverse RNA-seq datasets.
    Conclusions: InPAS is an efficient and robust tool for identifying and quantifying
    APA events using readily accessible conventional RNA-seq data. Its versatility
    opens doors to explore APA regulation across diverse eukaryotic systems with various
    experimental designs. We believe that InPAS will drive APA research forward, deepening
    our understanding of its role in regulating gene expression, and potentially leading
    to the discovery of biomarkers or therapeutics for diseases.'
  start: '21'
repository: https://bioc-release.r-universe.dev
commit: 596861b7320123552867050864fbcda0e8800ad3
date-released: '2026-04-28'
contact:
- family-names: Ou
  given-names: Jianhong
  email: jou@morgridge.org