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SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data
The current trend in clinical data analysis is to understand how individuals respond to therapies and drug interactions based on their genetic makeup. This has led to a paradigm shift in healthcare; caring for patients is now 99% information and 1% intervention. Reducing costs of next generation seq...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6247818/ https://www.ncbi.nlm.nih.gov/pubmed/30487811 http://dx.doi.org/10.3389/fgene.2018.00537 |
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author | Dharanipragada, Prashanthi Seelam, Sampreeth Reddy Parekh, Nita |
author_facet | Dharanipragada, Prashanthi Seelam, Sampreeth Reddy Parekh, Nita |
author_sort | Dharanipragada, Prashanthi |
collection | PubMed |
description | The current trend in clinical data analysis is to understand how individuals respond to therapies and drug interactions based on their genetic makeup. This has led to a paradigm shift in healthcare; caring for patients is now 99% information and 1% intervention. Reducing costs of next generation sequencing (NGS) technologies has made it possible to take genetic profiling to the clinical setting. This requires not just fast and accurate algorithms for variant detection, but also a knowledge-base for variant annotation and prioritization to facilitate tailored therapeutics based on an individual's genetic profile. Here we show that it is possible to provide a fast and easy access to all possible information about a variant and its impact on the gene, its protein product, associated pathways and drug-variant interactions by integrating previously reported knowledge from various databases. With this objective, we have developed a pipeline, Sequence Variants Identification and Annotation (SeqVItA) that provides end-to-end solution for small sequence variants detection, annotation and prioritization on a single platform. Parallelization of the variant detection step and with numerous resources incorporated to infer functional impact, clinical relevance and drug-variant associations, SeqVItA will benefit the clinical and research communities alike. Its open-source platform and modular framework allows for easy customization of the workflow depending on the data type (single, paired, or pooled samples), variant type (germline and somatic), and variant annotation and prioritization. Performance comparison of SeqVItA on simulated data and detection, interpretation and analysis of somatic variants on real data (24 liver cancer patients) is carried out. We demonstrate the efficacy of annotation module in facilitating personalized medicine based on patient's mutational landscape. SeqVItA is freely available at https://bioinf.iiit.ac.in/seqvita. |
format | Online Article Text |
id | pubmed-6247818 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-62478182018-11-28 SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data Dharanipragada, Prashanthi Seelam, Sampreeth Reddy Parekh, Nita Front Genet Genetics The current trend in clinical data analysis is to understand how individuals respond to therapies and drug interactions based on their genetic makeup. This has led to a paradigm shift in healthcare; caring for patients is now 99% information and 1% intervention. Reducing costs of next generation sequencing (NGS) technologies has made it possible to take genetic profiling to the clinical setting. This requires not just fast and accurate algorithms for variant detection, but also a knowledge-base for variant annotation and prioritization to facilitate tailored therapeutics based on an individual's genetic profile. Here we show that it is possible to provide a fast and easy access to all possible information about a variant and its impact on the gene, its protein product, associated pathways and drug-variant interactions by integrating previously reported knowledge from various databases. With this objective, we have developed a pipeline, Sequence Variants Identification and Annotation (SeqVItA) that provides end-to-end solution for small sequence variants detection, annotation and prioritization on a single platform. Parallelization of the variant detection step and with numerous resources incorporated to infer functional impact, clinical relevance and drug-variant associations, SeqVItA will benefit the clinical and research communities alike. Its open-source platform and modular framework allows for easy customization of the workflow depending on the data type (single, paired, or pooled samples), variant type (germline and somatic), and variant annotation and prioritization. Performance comparison of SeqVItA on simulated data and detection, interpretation and analysis of somatic variants on real data (24 liver cancer patients) is carried out. We demonstrate the efficacy of annotation module in facilitating personalized medicine based on patient's mutational landscape. SeqVItA is freely available at https://bioinf.iiit.ac.in/seqvita. Frontiers Media S.A. 2018-11-14 /pmc/articles/PMC6247818/ /pubmed/30487811 http://dx.doi.org/10.3389/fgene.2018.00537 Text en Copyright © 2018 Dharanipragada, Seelam and Parekh. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Dharanipragada, Prashanthi Seelam, Sampreeth Reddy Parekh, Nita SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data |
title | SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data |
title_full | SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data |
title_fullStr | SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data |
title_full_unstemmed | SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data |
title_short | SeqVItA: Sequence Variant Identification and Annotation Platform for Next Generation Sequencing Data |
title_sort | seqvita: sequence variant identification and annotation platform for next generation sequencing data |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6247818/ https://www.ncbi.nlm.nih.gov/pubmed/30487811 http://dx.doi.org/10.3389/fgene.2018.00537 |
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