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MuSiC Deconvolution (version 0.1.1+galaxy4)

scRNA Dataset:

Bulk RNA Dataset:

Purpose:

Methods to use:

Cell Types Label from scRNA dataset:

Samples Identifier from scRNA dataset:

Comma list of cell types to use from scRNA dataset:

If blank, then use all available cell types.

Phenotype factors:

List of phenotypes factors to be used in the linear regression. Please make sure that each factor has more than one unique value. Names correspond to column names in the bulk RNA dataset phenotype table. If blank, then treat all bulk phenotype columns as factors.

Excluded phenotype factors:

List of phenotype factors to always exclude in the analysis

Show proportions of a disease factor?:

Scale all Y-axes to max limit:

Leave blank to autoscale each plot.

MuSiC utilizes cell-type specific gene expression from single-cell RNA sequencing (RNA-seq) data to characterize cell type compositions from bulk RNA-seq data in complex tissues. By appropriate weighting of genes showing cross-subject and cross-cell consistency, MuSiC enables the transfer of cell type-specific gene expression information from one dataset to another.

Solid tissues often contain closely related cell types which leads to collinearity. To deal with collinearity, MuSiC employs a tree-guided procedure that recursively zooms in on closely related cell types. Briefly, we first group similar cell types into the same cluster and estimate cluster proportions, then recursively repeat this procedure within each cluster.