Literature DB >> 34595290

Brief Protocol for EDGE Bioinformatics: Analyzing Microbial and Metagenomic NGS Data.

Casandra Philipson1,2, Karen Davenport3, Logan Voegtly1,4, Chien-Chi Lo3, Po-E Li3, Yan Xu3, Migun Shakya3, Regina Z Cer1,4, Kimberly A Bishop-Lilly1, Theron Hamilton1, Patrick S G Chain3.   

Abstract

Next-generation sequencing (NGS) offers unparalleled resolution for untargeted organism detection and characterization. However, the majority of NGS analysis programs require users to be proficient in programming and command-line interfaces. EDGE bioinformatics was developed to offer scientists with little to no bioinformatics expertise a point-and-click platform for analyzing sequencing data in a rapid and reproducible manner. EDGE (Empowering the Development of Genomics Expertise) v1.0 released in January 2017, is an intuitive web-based bioinformatics platform engineered for the analysis of microbial and metagenomic NGS-based data ( Li et al., 2017 ). The EDGE bioinformatics suite combines vetted publicly available tools, and tracks settings to ensure reliable and reproducible analysis workflows. To execute the EDGE workflow, only raw sequencing reads and a project ID are necessary. Users can access in-house data, or run analyses on samples deposited in Sequence Read Archive. Default settings offer a robust first-glance and are often sufficient for novice users. All analyses are modular; users can easily turn workflows on/off, and modify parameters to cater to project needs. Results are compiled and available for download in a PDF-formatted report containing publication quality figures. We caution that interpreting results still requires in-depth scientific understanding, however report visuals are often informative, even to novice users.
Copyright © 2017 The Authors; exclusive licensee Bio-protocol LLC.

Entities:  

Keywords:  Bioinformatics; Genomics; Metagenomics; Next-generation sequencing

Year:  2017        PMID: 34595290      PMCID: PMC8438472          DOI: 10.21769/BioProtoc.2622

Source DB:  PubMed          Journal:  Bio Protoc        ISSN: 2331-8325


  20 in total

1.  IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth.

Authors:  Yu Peng; Henry C M Leung; S M Yiu; Francis Y L Chin
Journal:  Bioinformatics       Date:  2012-04-11       Impact factor: 6.937

2.  FastTree 2--approximately maximum-likelihood trees for large alignments.

Authors:  Morgan N Price; Paramvir S Dehal; Adam P Arkin
Journal:  PLoS One       Date:  2010-03-10       Impact factor: 3.240

3.  MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph.

Authors:  Dinghua Li; Chi-Man Liu; Ruibang Luo; Kunihiko Sadakane; Tak-Wah Lam
Journal:  Bioinformatics       Date:  2015-01-20       Impact factor: 6.937

4.  Prokka: rapid prokaryotic genome annotation.

Authors:  Torsten Seemann
Journal:  Bioinformatics       Date:  2014-03-18       Impact factor: 6.937

5.  The Sequence Alignment/Map format and SAMtools.

Authors:  Heng Li; Bob Handsaker; Alec Wysoker; Tim Fennell; Jue Ruan; Nils Homer; Gabor Marth; Goncalo Abecasis; Richard Durbin
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

6.  Primer3--new capabilities and interfaces.

Authors:  Andreas Untergasser; Ioana Cutcutache; Triinu Koressaar; Jian Ye; Brant C Faircloth; Maido Remm; Steven G Rozen
Journal:  Nucleic Acids Res       Date:  2012-06-22       Impact factor: 16.971

7.  RATT: Rapid Annotation Transfer Tool.

Authors:  Thomas D Otto; Gary P Dillon; Wim S Degrave; Matthew Berriman
Journal:  Nucleic Acids Res       Date:  2011-02-08       Impact factor: 16.971

8.  RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies.

Authors:  Alexandros Stamatakis
Journal:  Bioinformatics       Date:  2014-01-21       Impact factor: 6.937

9.  Rapid evaluation and quality control of next generation sequencing data with FaQCs.

Authors:  Chien-Chi Lo; Patrick S G Chain
Journal:  BMC Bioinformatics       Date:  2014-11-19       Impact factor: 3.169

10.  High-Specificity Targeted Functional Profiling in Microbial Communities with ShortBRED.

Authors:  James Kaminski; Molly K Gibson; Eric A Franzosa; Nicola Segata; Gautam Dantas; Curtis Huttenhower
Journal:  PLoS Comput Biol       Date:  2015-12-18       Impact factor: 4.475

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