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Serghei Mangul

Researcher at University of Southern California

Publications -  136
Citations -  5362

Serghei Mangul is an academic researcher from University of Southern California. The author has contributed to research in topics: Computer science & Biology. The author has an hindex of 19, co-authored 115 publications receiving 2832 citations. Previous affiliations of Serghei Mangul include University of California, Los Angeles & University of California, Berkeley.

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Journal ArticleDOI

The GTEx Consortium atlas of genetic regulatory effects across human tissues

François Aguet, +167 more
- 01 Jan 2020 - 
Journal ArticleDOI

Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics.

Alvaro N. Barbeira, +263 more
TL;DR: A mathematical expression is derived to compute PrediXcan results using summary data, and the effects of gene expression variation on human phenotypes in 44 GTEx tissues and >100 phenotypes are investigated.
Journal ArticleDOI

Cell type–specific genetic regulation of gene expression across human tissues

TL;DR: A growing number of in silico cell type deconvolution methods and associated reference panels with cell type–specific marker genes enable the robust estimation of the enrichment of specific cell types from bulk tissue gene expression data.
Journal ArticleDOI

Intratumoral CD4+ T Cells Mediate Anti-tumor Cytotoxicity in Human Bladder Cancer.

TL;DR: A gene signature of cytotoxic CD4+ T cells in tumors predicts a clinical response in 244 metastatic bladder cancer patients treated with anti-PD-L1, and several tumor-specific states are found, including multiple distinct states of regulatory T cells.
Journal ArticleDOI

Estimation of alternative splicing isoform frequencies from RNA-Seq data

TL;DR: A novel expectation-maximization algorithm for inference of isoform- and gene-specific expression levels from RNA-Seq data, referred to as IsoEM, is based on disambiguating information provided by the distribution of insert sizes generated during sequencing library preparation, and takes advantage of base quality scores, strand and read pairing information when available.