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ASJA: A Program for Assembling Splice Junctions Analysis
RNA splicing may generate different kinds of splice junctions, such as linear, back-splice and fusion junctions. Only a limited number of programs are available for detection and quantification of splice junctions. Here, we present Assembling Splice Junctions Analysis (ASJA), a software package that...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Research Network of Computational and Structural Biotechnology
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709372/ https://www.ncbi.nlm.nih.gov/pubmed/31462970 http://dx.doi.org/10.1016/j.csbj.2019.08.001 |
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author | Zhao, Jingjing Li, Qin Li, Yuchen He, Xianghuo Zheng, Qiupeng Huang, Shenglin |
author_facet | Zhao, Jingjing Li, Qin Li, Yuchen He, Xianghuo Zheng, Qiupeng Huang, Shenglin |
author_sort | Zhao, Jingjing |
collection | PubMed |
description | RNA splicing may generate different kinds of splice junctions, such as linear, back-splice and fusion junctions. Only a limited number of programs are available for detection and quantification of splice junctions. Here, we present Assembling Splice Junctions Analysis (ASJA), a software package that identifies and characterizes all splice junctions from high-throughput RNA sequencing (RNA-seq) data. ASJA processes assembled transcripts and chimeric alignments from the STAR aligner and StringTie assembler. ASJA provides the unique position and normalized expression level of each junction. Annotations and integrative analysis of the junctions enable additional filtering. It is also appropriate for the identification of novel junctions. ASJA is available at https://github.com/HuangLab-Fudan/ASJA. |
format | Online Article Text |
id | pubmed-6709372 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Research Network of Computational and Structural Biotechnology |
record_format | MEDLINE/PubMed |
spelling | pubmed-67093722019-08-28 ASJA: A Program for Assembling Splice Junctions Analysis Zhao, Jingjing Li, Qin Li, Yuchen He, Xianghuo Zheng, Qiupeng Huang, Shenglin Comput Struct Biotechnol J Method Article RNA splicing may generate different kinds of splice junctions, such as linear, back-splice and fusion junctions. Only a limited number of programs are available for detection and quantification of splice junctions. Here, we present Assembling Splice Junctions Analysis (ASJA), a software package that identifies and characterizes all splice junctions from high-throughput RNA sequencing (RNA-seq) data. ASJA processes assembled transcripts and chimeric alignments from the STAR aligner and StringTie assembler. ASJA provides the unique position and normalized expression level of each junction. Annotations and integrative analysis of the junctions enable additional filtering. It is also appropriate for the identification of novel junctions. ASJA is available at https://github.com/HuangLab-Fudan/ASJA. Research Network of Computational and Structural Biotechnology 2019-08-07 /pmc/articles/PMC6709372/ /pubmed/31462970 http://dx.doi.org/10.1016/j.csbj.2019.08.001 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Method Article Zhao, Jingjing Li, Qin Li, Yuchen He, Xianghuo Zheng, Qiupeng Huang, Shenglin ASJA: A Program for Assembling Splice Junctions Analysis |
title | ASJA: A Program for Assembling Splice Junctions Analysis |
title_full | ASJA: A Program for Assembling Splice Junctions Analysis |
title_fullStr | ASJA: A Program for Assembling Splice Junctions Analysis |
title_full_unstemmed | ASJA: A Program for Assembling Splice Junctions Analysis |
title_short | ASJA: A Program for Assembling Splice Junctions Analysis |
title_sort | asja: a program for assembling splice junctions analysis |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6709372/ https://www.ncbi.nlm.nih.gov/pubmed/31462970 http://dx.doi.org/10.1016/j.csbj.2019.08.001 |
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