SCIPAC: quantitative estimation of cell-phenotype associations.
Genome Biol
; 25(1): 119, 2024 05 13.
Article
in En
| MEDLINE
| ID: mdl-38741183
ABSTRACT
Numerous algorithms have been proposed to identify cell types in single-cell RNA sequencing data, yet a fundamental problem remains determining associations between cells and phenotypes such as cancer. We develop SCIPAC, the first algorithm that quantitatively estimates the association between each cell in single-cell data and a phenotype. SCIPAC also provides a p-value for each association and applies to data with virtually any type of phenotype. We demonstrate SCIPAC's accuracy in simulated data. On four real cancerous or noncancerous datasets, insights from SCIPAC help interpret the data and generate new hypotheses. SCIPAC requires minimum tuning and is computationally very fast.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Phenotype
/
Algorithms
/
Single-Cell Analysis
Limits:
Humans
Language:
En
Journal:
Genome Biol
/
Genome biol
/
Genome biology (Online)
Journal subject:
BIOLOGIA MOLECULAR
/
GENETICA
Year:
2024
Document type:
Article
Affiliation country:
Estados Unidos
Country of publication:
Reino Unido