DCATS

DCATS detects differential composition abundances between conditions in single-cell RNA-seq experiments, with or without replicates, while correcting bias introduced by misclassification and enabling control of confounding covariates.

Key Features:

• Misclassification bias correction: DCATS corrects bias introduced by misclassification in cell type assignment.
• Confounding covariate control: DCATS enables controlling of confounding covariates in differential composition analysis.
• Flexible normalization: DCATS can use either total cell number or a specific reference group as normalization term to avoid the influence of proportion change from big cell types.
• Replicate handling: DCATS supports differential composition analysis with or without biological replicates.

Scientific Applications:

• Differential composition analysis: DCATS detects differential composition abundances between experimental conditions in single-cell RNA-seq data.

Methodology:

DCATS uses methods transformed by a similarity matrix for differential composition analysis.