A cloud-based training module for efficient de novo transcriptome assembly using Nextflow and Google cloud

被引:2
作者
Seaman, Ryan P. [1 ]
Campbell, Ross [2 ]
Doe, Valena [3 ]
Yosufzai, Zelaikha [2 ]
Graber, Joel H. [1 ]
机构
[1] MDI Biol Lab, 159 Old Bar Harbor Rd, Bar Harbor, ME 04609 USA
[2] Deloitte Consulting LLP, Hlth Data & AI, 4301 Fairfax Dr,Unit 210, Arlington, VA 22203 USA
[3] Google, Google Cloud, 1900 Reston Metro Plaza, Reston, VA 20190 USA
基金
美国国家卫生研究院;
关键词
cloud computing; nextflow; training module; transcriptome; assembly; annotation; PREDICTION;
D O I
10.1093/bib/bbae313
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
This study describes the development of a resource module that is part of a learning platform named "NIGMS Sandbox for Cloud-based Learning" (https://github.com/NIGMS/NIGMS-Sandbox). The overall genesis of the Sandbox is described in the editorial NIGMS Sandbox at the beginning of this Supplement. This module delivers learning materials on de novo transcriptome assembly using Nextflow in an interactive format that uses appropriate cloud resources for data access and analysis. Cloud computing is a powerful new means by which biomedical researchers can access resources and capacity that were previously either unattainable or prohibitively expensive. To take advantage of these resources, however, the biomedical research community needs new skills and knowledge. We present here a cloud-based training module, developed in conjunction with Google Cloud, Deloitte Consulting, and the NIH STRIDES Program, that uses the biological problem of de novo transcriptome assembly to demonstrate and teach the concepts of computational workflows (using Nextflow) and cost- and resource-efficient use of Cloud services (using Google Cloud Platform). Our work highlights the reduced necessity of on-site computing resources and the accessibility of cloud-based infrastructure for bioinformatics applications.
引用
收藏
页数:8
相关论文
共 21 条
  • [1] Genome-Wide Discovery of Long Non-Coding RNAs in Rainbow Trout
    Al-Tobasei, Rafet
    Paneru, Bam
    Salem, Mohamed
    [J]. PLOS ONE, 2016, 11 (02):
  • [2] rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data
    Bushmanova, Elena
    Antipov, Dmitry
    Lapidus, Alla
    Prjibelski, Andrey D.
    [J]. GIGASCIENCE, 2019, 8 (09):
  • [3] A survey of best practices for RNA-seq data analysis
    Conesa, Ana
    Madrigal, Pedro
    Tarazona, Sonia
    Gomez-Cabrero, David
    Cervera, Alejandra
    McPherson, Andrew
    Szczesniak, Michal Wojciech
    Gaffney, Daniel J.
    Elo, Laura L.
    Zhang, Xuegong
    Mortazavi, Ali
    [J]. GENOME BIOLOGY, 2016, 17
  • [4] Nextflow enables reproducible computational workflows
    Di Tommaso, Paolo
    Chatzou, Maria
    Floden, Evan W.
    Prieto Barja, Pablo
    Palumbo, Emilio
    Notredame, Cedric
    [J]. NATURE BIOTECHNOLOGY, 2017, 35 (04) : 316 - 319
  • [5] The nf-core framework for community-curated bioinformatics pipelines
    Ewels, Philip A.
    Peltzer, Alexander
    Fillinger, Sven
    Patel, Harshil
    Alneberg, Johannes
    Wilm, Andreas
    Garcia, Maxime Ulysse
    Di Tommaso, Paolo
    Nahnsen, Sven
    [J]. NATURE BIOTECHNOLOGY, 2020, 38 (03) : 276 - 278
  • [6] Full-length transcriptome assembly from RNA-Seq data without a reference genome
    Grabherr, Manfred G.
    Haas, Brian J.
    Yassour, Moran
    Levin, Joshua Z.
    Thompson, Dawn A.
    Amit, Ido
    Adiconis, Xian
    Fan, Lin
    Raychowdhury, Raktima
    Zeng, Qiandong
    Chen, Zehua
    Mauceli, Evan
    Hacohen, Nir
    Gnirke, Andreas
    Rhind, Nicholas
    di Palma, Federica
    Birren, Bruce W.
    Nusbaum, Chad
    Lindblad-Toh, Kerstin
    Friedman, Nir
    Regev, Aviv
    [J]. NATURE BIOTECHNOLOGY, 2011, 29 (07) : 644 - U130
  • [7] Cortisol-treated zebrafish embryos develop into pro-inflammatory adults with aberrant immune gene regulation
    Hartig, Ellen I.
    Zhu, Shusen
    King, Benjamin L.
    Coffman, James A.
    [J]. BIOLOGY OPEN, 2016, 5 (08): : 1134 - 1141
  • [8] De novo transcriptome assembly: A comprehensive cross-species comparison of short-read RNA-Seq assemblers
    Hoelzer, Martin
    Marz, Manja
    [J]. GIGASCIENCE, 2019, 8 (05):
  • [9] Manni M, 2021, CURR PROTOC, V1, DOI 10.1002/cpz1.323
  • [10] A simple guide to de novo transcriptome assembly and annotation
    Raghavan, Venket
    Kraft, Louis
    Mesny, Fantin
    Rigerte, Linda
    [J]. BRIEFINGS IN BIOINFORMATICS, 2022, 23 (02)