Function reference • MuSiC

Deconvolution Deconvolution functions
`music_prop()`	MuSiC Deconvolution
`music_prop.cluster()`	MuSiC Deconvolution with Clusters
`music.basic()`	Estimate cell type proportion with MuSiC and NNLS
`music.iter()`	Scaling bulk data and signature matrix and estimate cell type proportion
`music.basic.ct()`	Estimate cell type proportion with MuSiC and NNLS
`music.iter.ct()`	Scaling bulk data and signature matrix and estimate cell type proportion
`weight.cal.ct()`	Calculate weight with cross cell type covariance
`Weight_cal()`	Calculate weight with cross-subject variance for each cell types
Construction Construct artificial bulk expression. Construct matrices for MuSiC deconvolution, such as design matrix, cross-subject mean matrix, cross-subject variance matrix and library size vector.
`bulk_construct()`	Construct artificial bulk tissue expression from single cell data
`music_basis()`	Prepare Design matrix and Cross-subject Variance for MuSiC Deconvolution
`music_M.theta()`	Cross-subject Mean of Relative Abudance
`music_Theta()`	Subject and cell type specific relative abundance
`music_Sigma.ct()`	Cross-subject Covariance of Relative Abundance
`music_Sigma()`	Cross-subject Variance of Relative Abundance
`music_S()`	Cell type specific library size
`music_Design.matrix()`	Cell type specific library size
MuSiC2 Cell type deconvolution for multi-condition bulk RNA-seq data
`music2_prop()`	MuSiC2_Deconvolution
`music2_prop_t_statistics()`	MuSiC2 Deconvolution with T Statistics
`music2_prop_toast()`	MuSiC2 Deconvolution with TOAST
Graphics Create graphics for visualization and evaluation. The numerical evaluation function is also included.
`Relative_gene_boxplot()`	Boxplot of relative abundance
`Prop_comp_multi()`	Plot heatmap of real and estimated cell type proportions
`Abs_diff_multi()`	Plot heatmap of Absolute difference between estimated and real cell type proportions
`Scatter_multi()`	Plot Scatter plot of real and estimated cell type proportions
`Boxplot_Est()`	Boxplot of estimated cell type proportions
`Jitter_Est()`	Jitter plot of estimated cell type proportions
`Prop_heat_Est()`	Heatmap of estimated cell type proportions
`Eval_multi()`	Evaluate estimation methods
`Prop_convert()`	Convert list of real and estimated cell type proportions to data frame
`CellTotal.df()`	Compare cell type specific total expression (library size) between 2 dataset
`plotCellTotal.two()`	Plot the cell type specific library size of 2 single cell datasets
Simulations Generate simulations
`Twocelltype.Generator()`	Simulate Single cell read counts
`Eval_sim_boxplot()`	Evaluate simulation results by boxplots
Utilities
`relative.ab()`	Calculate relative abundance
`fpkmToTpm()`	Calculate fpkm to tpm
`my.log()`	log transformation with regulation
`my.sqrt()`	Calculate square root of all values
`my.rowMeans()`	Calculate Row Means with NA remove
`get_upper_tri()`	Get upper triangle matrix
`Anova_info()`	ANOVA Test for each gene

Reference

Deconvolution

Construction

MuSiC2

Graphics

Simulations

Utilities