TY - JOUR

T1 - Fold-change-specific enrichment analysis (FSEA)

T2 - Quantification of transcriptional response magnitude for functional gene groups

AU - Wiebe, Daniil S.

AU - Omelyanchuk, Nadezhda A.

AU - Mukhin, Aleksei M.

AU - Grosse, Ivo

AU - Lashin, Sergey A.

AU - Zemlyanskaya, Elena V.

AU - Mironova, Victoria V.

PY - 2020/4/17

Y1 - 2020/4/17

N2 - Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes from transcriptome data with respect to their fold changes. FSEA identifies Gene Ontology (GO) terms, which are shared by the group of genes with a similar magnitude of response, and assesses these changes. GO terms found by FSEA are fold-change-specifically (e.g., weakly, moderately, or strongly) affected by a stimulus under investigation. We demonstrate that many responses to abiotic factors, mutations, treatments, and diseases occur in a fold-change-specific manner. FSEA analyses suggest that there are two prevailing responses of functionally-related gene groups, either weak or strong. Notably, some of the fold-change-specific GO terms are invisible by classical algorithms for functional gene enrichment, Singular Enrichment Analysis (SEA), and Gene Set Enrichment Analysis (GSEA). These are GO terms not enriched compared to the genome background but strictly regulated by a factor within specific fold-change intervals. FSEA analysis of a cancer-related transcriptome suggested that the gene groups with a tightly coordinated response can be the valuable source to search for possible regulators, markers, and therapeutic targets in oncogenic processes. Availability and Implementation: FSEA is implemented as the FoldGO Bioconductor R package and a web-server.

AB - Gene expression profiling data contains more information than is routinely extracted with standard approaches. Here we present Fold-Change-Specific Enrichment Analysis (FSEA), a new method for functional annotation of differentially expressed genes from transcriptome data with respect to their fold changes. FSEA identifies Gene Ontology (GO) terms, which are shared by the group of genes with a similar magnitude of response, and assesses these changes. GO terms found by FSEA are fold-change-specifically (e.g., weakly, moderately, or strongly) affected by a stimulus under investigation. We demonstrate that many responses to abiotic factors, mutations, treatments, and diseases occur in a fold-change-specific manner. FSEA analyses suggest that there are two prevailing responses of functionally-related gene groups, either weak or strong. Notably, some of the fold-change-specific GO terms are invisible by classical algorithms for functional gene enrichment, Singular Enrichment Analysis (SEA), and Gene Set Enrichment Analysis (GSEA). These are GO terms not enriched compared to the genome background but strictly regulated by a factor within specific fold-change intervals. FSEA analysis of a cancer-related transcriptome suggested that the gene groups with a tightly coordinated response can be the valuable source to search for possible regulators, markers, and therapeutic targets in oncogenic processes. Availability and Implementation: FSEA is implemented as the FoldGO Bioconductor R package and a web-server.

KW - Enrichment analysis

KW - Gene expression

KW - Gene ontology

KW - Transcriptomics

KW - PATHWAYS

KW - ACTIVATION

KW - PROTEIN

KW - enrichment analysis

KW - EXPRESSION PATTERNS

KW - gene ontology

KW - PROSTATE-CANCER CELLS

KW - transcriptomics

KW - gene expression

UR - http://www.scopus.com/inward/record.url?scp=85083836523&partnerID=8YFLogxK

U2 - 10.3390/genes11040434

DO - 10.3390/genes11040434

M3 - Article

C2 - 32316383

AN - SCOPUS:85083836523

VL - 11

JO - Genes

JF - Genes

SN - 2073-4425

IS - 4

M1 - 434

ER -