RNA-seq Data Analysis for Differential Expression

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

Changes in the surrounding environment are mirrored by changes in the transcript profile of an organism. In the case of a plant pathogen, host colonization would be a challenge that triggers changes in transcript expression patterns. Determining the transcriptional profile could provide valuable clues on how an organism responds to defined stimuli, in this case, how a pathogen colonizes its host. Several robust data analysis methods and pipelines are available that can identify these differentially expressed transcripts. In this chapter we outline the steps and other caveats that are needed to run one such pipeline.

Original languageAmerican English
Title of host publicationMethods in Molecular Biology
Pages45-54
Number of pages10
DOIs
StatePublished - Oct 23 2021
Externally publishedYes

Publication series

NameMethods in Molecular Biology
Volume2391

Bibliographical note

Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Funding

This work is supported by the USDA National Institute of Food and Agriculture, Hatch project FLA-FTL-005926. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the author(s) and do not necessarily reflect the view of the National Institute of Food and Agriculture (NIFA) or the US Department of Agriculture (USDA).

FundersFunder number
U.S. Department of Agriculture
National Institute of Food and AgricultureFLA-FTL-005926

    ASJC Scopus Subject Areas

    • Molecular Biology
    • Genetics

    Keywords

    • DESeq2
    • Data analysis
    • Differentially expressed genes
    • HISAT2
    • Pipeline
    • RNA-seq
    • Splice-aware
    • StringTie
    • Transcript profile
    • Transcriptome

    Disciplines

    • Biology
    • Life Sciences

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