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PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets
Quality control and read preprocessing are critical steps in the analysis of data sets generated from high-throughput genomic screens. In the most extreme cases, improper preprocessing can negatively affect downstream analyses and may lead to incorrect biological conclusions. Here, we present PathoQ...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Libertas Academica
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4429651/ https://www.ncbi.nlm.nih.gov/pubmed/25983538 http://dx.doi.org/10.4137/CIN.S13890 |
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author | Hong, Changjin Manimaran, Solaiappan Johnson, William Evan |
author_facet | Hong, Changjin Manimaran, Solaiappan Johnson, William Evan |
author_sort | Hong, Changjin |
collection | PubMed |
description | Quality control and read preprocessing are critical steps in the analysis of data sets generated from high-throughput genomic screens. In the most extreme cases, improper preprocessing can negatively affect downstream analyses and may lead to incorrect biological conclusions. Here, we present PathoQC, a streamlined toolkit that seamlessly combines the benefits of several popular quality control software approaches for preprocessing next-generation sequencing data. PathoQC provides a variety of quality control options appropriate for most high-throughput sequencing applications. PathoQC is primarily developed as a module in the PathoScope software suite for metagenomic analysis. However, PathoQC is also available as an open-source Python module that can run as a stand-alone application or can be easily integrated into any bioinformatics workflow. PathoQC achieves high performance by supporting parallel computation and is an effective tool that removes technical sequencing artifacts and facilitates robust downstream analysis. The PathoQC software package is available at http://sourceforge.net/projects/PathoScope/. |
format | Online Article Text |
id | pubmed-4429651 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-44296512015-05-15 PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets Hong, Changjin Manimaran, Solaiappan Johnson, William Evan Cancer Inform Software or Database Review Quality control and read preprocessing are critical steps in the analysis of data sets generated from high-throughput genomic screens. In the most extreme cases, improper preprocessing can negatively affect downstream analyses and may lead to incorrect biological conclusions. Here, we present PathoQC, a streamlined toolkit that seamlessly combines the benefits of several popular quality control software approaches for preprocessing next-generation sequencing data. PathoQC provides a variety of quality control options appropriate for most high-throughput sequencing applications. PathoQC is primarily developed as a module in the PathoScope software suite for metagenomic analysis. However, PathoQC is also available as an open-source Python module that can run as a stand-alone application or can be easily integrated into any bioinformatics workflow. PathoQC achieves high performance by supporting parallel computation and is an effective tool that removes technical sequencing artifacts and facilitates robust downstream analysis. The PathoQC software package is available at http://sourceforge.net/projects/PathoScope/. Libertas Academica 2015-05-12 /pmc/articles/PMC4429651/ /pubmed/25983538 http://dx.doi.org/10.4137/CIN.S13890 Text en © 2014 the author(s), publisher and licensee Libertas Academica Limited This is an open-access article distributed under the terms of the Creative Commons CCCC-BY-NCNC 3.0 License. |
spellingShingle | Software or Database Review Hong, Changjin Manimaran, Solaiappan Johnson, William Evan PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets |
title | PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets |
title_full | PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets |
title_fullStr | PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets |
title_full_unstemmed | PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets |
title_short | PathoQC: Computationally Efficient Read Preprocessing and Quality Control for High-Throughput Sequencing Data Sets |
title_sort | pathoqc: computationally efficient read preprocessing and quality control for high-throughput sequencing data sets |
topic | Software or Database Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4429651/ https://www.ncbi.nlm.nih.gov/pubmed/25983538 http://dx.doi.org/10.4137/CIN.S13890 |
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