Corticosteroid-sensitive lymphocytes are normal in atopic asthma

Schuyler, Mark; Bondarevsky, Ernesto; Schwartz, Howard J.; Schmitt, David

doi:10.1016/0091-6749(81)90126-3

Cited by 10 publications

(1 citation statement)

References 31 publications

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“…5g ). Asthma is known as a self-immune disease, and the correlation between asthma disease with lymphocyte type and neutrophil to lymphocyte ratio is well studied ( Gungen et al , 2017 ; Moldaver et al , 2017 ; Schuyler et al , 1981 ). In summary, RE-GOA provides reasonable results in revealing genetic correlation among phenotypes from their GWAS summary statistics data.…”

Section: Resultsmentioning

confidence: 99%

Annotating regulatory elements by heterogeneous network embedding

Feng

Zhang

et al. 2022

Bioinformatics

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Motivation Regulatory elements (REs), such as enhancers and promoters, are known as regulatory sequences functional in a heterogeneous regulatory network to control gene expression by recruiting transcription regulators and carrying genetic variants in a context specific way. Annotating those REs relies on costly and labor-intensive next generation sequencing and RNA-guided editing technologies in many cellular contexts. Results We propose a systematic Gene Ontology Annotation method for Regulatory Elements (RE-GOA) by leveraging the powerful word embedding in natural language processing. We first assemble a heterogeneous network by integrating context specific regulations, protein-protein interactions, and gene ontology (GO) terms. Then we perform network embedding and associate regulatory elements with GO terms by assessing their similarity in low dimensional vector space. With three applications, we show that RE-GOA outperforms existing methods in annotating TFs’ binding sites from ChIP-seq data, in functional enrichment analysis of differentially accessible peaks from ATAC-seq data, and in revealing genetic correlation among phenotypes from their GWAS summary statistics data. Availability The source code and the systematic RE annotation for human and mouse are available at https://github.com/AMSSwanglab/RE-GOA. Supplementary information Supplementary data are available at Bioinformatics online.

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Section: Resultsmentioning

confidence: 99%