Identifying genetic variants that influence the abundance of cell states in single-cell data.
Laurie Rumker, Saori Sakaue, Yakir Reshef, Joyce B Kang, Seyhan Yazar, Jose Alquicira-Hernandez, Cristian Valencia, Kaitlyn A Lagattuta, Annelise Mah-Som, Aparna Nathan and 3 more
Article in Nature genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
2 · The registry
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Role of fibroblastic stromal cells and notch signaling in tissue inflammation in RA and SLEP01AI148102 · NIAID · BRIGHAM AND WOMEN'S HOSPITAL · PI Michael B. Brenner, Nir Hacohen · 2021 to 2026
$17.3M
Training Program in Bioinformatics and Integrative GenomicsT32HG002295 · NHGRI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI Peter J Park · 2001 to 2026
$15.8M
Medical Scientist Training ProgramT32GM144273 · NIGMS · HARVARD MEDICAL SCHOOL · PI David Shumway Jones, Jacqueline A. Lees · 2022 to 2026
$14.7M
Discovery and Functional Impact of Common and Rare Variants in RAR01AR063759 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Soumya Raychaudhuri · 2013 to 2026
$5.4M
Integrative analysis of high dimensional tissue molecular data to define key biological systems in autoimmune diseases (SBC)UC2AR081023 · NIAMS · BRIGHAM AND WOMEN'S HOSPITAL · PI Soumya Raychaudhuri · 2022 to 2026
$4.8M
Predicting the impact of genetic variants, genes and pathways on human DiseaseU01HG012009 · NHGRI · BRIGHAM AND WOMEN'S HOSPITAL · PI ALKES L PRICE, Soumya Raychaudhuri · 2021 to 2026
$4.2M
Integrative modelling of single-cell data to elucidate the genetic architecture of complex diseaseR56HG013083 · NHGRI · DANA-FARBER CANCER INST · PI GUSEV, ALEXANDER, PRICE, ALKES L · 2023 to 2023
$400k
Characterizing the Genomic Basis of Immune-Mediated Resilience Against Tuberculosis in an Admixed Peruvian PopulationF30AI157385 · NIAID · HARVARD MEDICAL SCHOOL · PI RUMKER, LAURIE ANN · 2021 to 2024
$178k
Pinpointing how single-cell states affect genetic regulation of HLA expression in autoimmune diseasesF30AI172238 · NIAID · HARVARD MEDICAL SCHOOL · PI KANG, JOYCE BLOSSOM · 2022 to 2024
$143k
Department of Health | National Health and Medical Research Council (NHMRC) 1175781Department of Health | National Health and Medical Research Council (NHMRC) 2018432NHGRI NIH HHS R56 HG013083NHGRI NIH HHS T32 HG002295NHGRI NIH HHS U01 HG012009NIAID NIH HHS F30 AI157385NIAID NIH HHS F30 AI172238NIAID NIH HHS P01 AI148102NIAMS NIH HHS R01 AR063759NIAMS NIH HHS UC2 AR081023NIGMS NIH HHS T32 GM144273U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) R56HG013083U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) T32HG01046U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) U01HG012009U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) F30AI157385U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) F30AI172238U.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID) P01AI148102U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) R01AR063759U.S. Department of Health & Human Services | NIH | National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS) UC2AR081023U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) T32GM144273U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (NIGMS) T32HG002295
6 · The paper itself
Abstract
Disease risk alleles influence the composition of cells present in the body, but modeling genetic effects on the cell states revealed by single-cell profiling is difficult because variant-associated states may reflect diverse combinations of the profiled cell features that are challenging to predefine. We introduce Genotype-Neighborhood Associations (GeNA), a statistical tool to identify cell-state abundance quantitative trait loci (csaQTLs) in high-dimensional single-cell datasets. Instead of testing associations to predefined cell states, GeNA flexibly identifies the cell states whose abundance is most associated with genetic variants. In a genome-wide survey of single-cell RNA sequencing peripheral blood profiling from 969 individuals, GeNA identifies five independent loci associated with shifts in the relative abundance of immune cell states. For example, rs3003-T (P = 1.96 × 10
Indexed as
Genome-Wide Association StudyQuantitative Trait LociSingle-Cell AnalysisGenetic Predisposition to DiseaseGenetic VariationGenotypeHumansKiller Cells, NaturalPolymorphism, Single NucleotidePsoriasisSequence Analysis, RNA
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.
Identifying genetic variants that influence the abundance of cell states in single-cell data. · full record | OpenQuestion