Literature DB >> 28463398

Using FunSeq2 for Coding and Non-Coding Variant Annotation and Prioritization.

Priyanka Dhingra1,2, Yao Fu3, Mark Gerstein4,5,6, Ekta Khurana1,2,7,8.   

Abstract

The identification of non-coding drivers remains a challenge and bottleneck for the use of whole-genome sequencing in the clinic. FunSeq2 is a computational tool for annotation and prioritization of somatic mutations in coding and non-coding regions. It integrates a data context made from large-scale genomic datasets and uses a high-throughput variant prioritization pipeline. This unit provides guidelines for installing and running FunSeq2 to (a) annotate and prioritize variants, (b) incorporate user-defined annotations, and (c) detect differential gene expression. © 2017 by John Wiley & Sons, Inc.
Copyright © 2017 John Wiley & Sons, Inc.

Keywords:  cancer drivers; differential gene expression; disease-causing; indels; non-coding variants; single nucleotide variants

Mesh:

Year:  2017        PMID: 28463398     DOI: 10.1002/cpbi.23

Source DB:  PubMed          Journal:  Curr Protoc Bioinformatics        ISSN: 1934-3396


  2 in total

1.  Clinical-grade whole-genome sequencing and 3' transcriptome analysis of colorectal cancer patients.

Authors:  Agata Stodolna; Miao He; Mahesh Vasipalli; Zoya Kingsbury; Jennifer Becq; Joanne D Stockton; Mark P Dilworth; Jonathan James; Toju Sillo; Daniel Blakeway; Stephen T Ward; Tariq Ismail; Mark T Ross; Andrew D Beggs
Journal:  Genome Med       Date:  2021-02-25       Impact factor: 11.117

Review 2.  Cutting-Edge AI Technologies Meet Precision Medicine to Improve Cancer Care.

Authors:  Peng-Chan Lin; Yi-Shan Tsai; Yu-Min Yeh; Meng-Ru Shen
Journal:  Biomolecules       Date:  2022-08-17
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.