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Table 1 Computational tools for detecting APA

From: Alternative polyadenylation: methods, mechanism, function, and role in cancer

Name Description Environment Year Website Ref.
InPAS A package that can detect the dynamics of APA events from RNA-seq data by removing false sites due to internal-priming. R 2013 http://www.bioconductor.org/packages/release/bioc/html/InPAS.html [137]
ChangePoint A change-point model based on a likelihood ratio test for detecting 3’UTR switching. Java 2014 http://utr.sourceforge.net/ [13]
DaPars A bioinformatics algorithm for the de novo identification of dynamic APAs from standard RNA-seq. Python 2014 https://github.com/ZhengXia/dapars [8]
Roar A strategy for detecting alternative PAS usage and comparing these between two biological conditions. R 2016 https://github.com/vodkatad/roar/ [138]
QAPA An approach to infer and quantify APA from RNA-seq data. Python & R 2018 https://www.github.com/morrislab/qapa [139]
PAQR_KAPAC A combined method that can quantify PAS usage from RNA-seq data and infer regulatory sequence motifs on PAS usage. Python & R 2018 https://github.com/zavolanlab/PAQR_KAPAC.git [120]
APAtrap An approach to identify and quantify APA sites from RNA-seq data based on the mean squared error model. R 2018 https://apatrap.sourceforge.io. [140]
IntMap An integrated method for detecting novel APA events from RNA-seq and PAS-seq data. Matlab 2018 http://compbio.cs.umn.edu/IntMAP/ [141]
TAPAS A tool that can detect more than two APA sites in a gene and APA sites before the last exon from RNA-seq data. R 2018 https://github.com/arefeen/TAPAS [142]
APARENT A deep learning approach to predict APA from DNA sequences. Python 2019 https://github.com/johli/aparent [143]
DeepPASTA A deep learning method to predict APA from DNA sequences and RNA secondary structure data. Python 2019 https://github.com/arefeen/DeepPASTA [144]
scDAPA A tool to detect and visualize APA events from single-cell RNA-seq data. R 2019 https://scdapa.sourceforge.io/ [145]
APAlyzer A bioinformatics package which can examine 3’UTR-APA, intronic APA, and gene expression changes using RNA-seq data. R 2020 https://bioconductor.org/packages/
release/bioc/html/APAlyzer.html
[146]
APA-Scan A robust program that infers 3’UTR-APA events and visualizes the RNA-seq short-read coverage with gene annotations. Python 2020 https://github.com/compbiolabucf/APA-Scan [147]