FUSE: Improving the estimation and imputation of variant impacts in functional screening

Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening.

Authors

Institutions

Publication Details

Journal
Cell Genomics
Published
2024-10-01
DOI
https://doi.org/10.1016/j.xgen.2024.100667
Citations
7
Primary Topic
Genetic factors in colorectal cancer
Type
article
Field-Weighted Citation Impact
2.97

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

FUSE: Improving the estimation and imputation of variant impacts in functional screening

Christopher A. Cassa, Ivan Adzhubey, Richard I. Sherwood, James D. Fife et al.
7 citations
Cell Genomics
Genetic factors in colorectal cancer
2.97
article

FUSE: Improving the estimation and imputation of variant impacts in functional screening

Christopher A. Cassa, Ivan Adzhubey, Richard I. Sherwood, James D. Fife, Vineel Bhat, Yu Tian
article en
7 citations

Abstract

Deep mutational scanning enables high-throughput functional assessment of genetic variants. While phenotypic measurements from screening assays generally align with clinical outcomes, experimental noise may affect the accuracy of individual variant estimates. We developed the FUSE (functional substitution estimation) pipeline, which leverages measurements collectively within screening assays to improve the estimation of variant impacts. Drawing data from 115 published functional assays, FUSE assesses the mean functional effect per amino acid position and makes estimates for individual allelic variants. It enhances the correlation of variant functional effects from different assay platforms and increases the classification accuracy of missense variants in ClinVar across 29 genes (area under the receiver operating characteristic [ROC] curve [AUC] from 0.83 to 0.90). In UK Biobank patients with rare missense variants in BRCA1, LDLR, or TP53, FUSE improves the classification accuracy of associated phenotypes. FUSE can also impute variant effects for substitutions not experimentally screened. This approach improves accuracy and broadens the utility of data from functional screening.

Cell GenomicsVol. 4(10)
Brigham and Women's Hospital (US), Harvard University (US), Boston VA Research Institute (US)
American Heart Association, Massachusetts General Hospital, National Human Genome Research Institute
Openalex Percentile: Top 9%
Genetic factors in colorectal cancer
2.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

FUSE: Improving the estimation and imputation of variant impacts in functional screening — Christopher A. Cassa, Ivan Adzhubey, et al. · Cell Genomics (2024) | TGRS Research Map | TGRS