RNA Solutions: Synthesizing Information to Support Transcriptomics (RNASSIST) | Zendy

Yi-Pei Chen | Zendy; Laura B. Ferguson | Zendy; Nihal A. Salem | Zendy; George Zheng | Zendy; R. Dayne Mayfield | Zendy; Mohammed Eslami | Zendy

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RNA Solutions: Synthesizing Information to Support Transcriptomics (RNASSIST)

Author(s) -

Yi-Pei Chen,

Laura B. Ferguson,

Nihal A. Salem,

George Zheng,

R. Dayne Mayfield,

Mohammed Eslami

Publication year - 2021

Publication title -

bioinformatics

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab673

Subject(s) - transcriptome , rna seq , gene , gene expression , computational biology , software , pipeline (software) , biology , gene expression profiling , computer science , bioinformatics , genetics , programming language

Transcriptomics is a common approach to identify changes in gene expression induced by a disease state. Standard transcriptomic analyses consider differentially expressed genes (DEGs) as indicative of disease states so only a few genes would be treated as signals when the effect size is small, such as in brain tissue. For tissue with small effect sizes, if the DEGs do not belong to a pathway known to be involved in the disease, there would be little left in the transcriptome for researchers to follow up with.

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