M3DropCleanData {M3Drop} | R Documentation

## Filter Expression Data

### Description

Filters and normalizes a given expression matrix. Removes low quality cells and undetected genes, and normalizes counts to counts per million. Functions tagged with "bg__" are not meant for direct usage and are not available in the Bioconductor release.

### Usage

      M3DropCleanData(expr_mat, labels = NA, is.counts = TRUE, suppress.plot = FALSE, pseudo_genes = NA, min_detected_genes = NA)
      bg__filter_cells(expr_mat, labels = NA, suppress.plot = FALSE, min_detected_genes = NA)

### Arguments

`expr_mat` | a numeric matrix of raw or normalized (not log-transformed) expression values, columns = samples/cells, rows = genes.
`labels` | a vector of length equal to the number of columns of expr_mat with names or group IDs for each cell.
`is.counts` | logical, whether the provided data is unnormalized read/fragment counts.
`suppress.plot` | logical, whether to plot the distribution of number of detected genes per cell.
`pseudo_genes` | a vector of gene names of known pseudogenes which will be removed from the cleaned data.
`min_detected_genes` | minimum number of genes/cell for a cell to be included in the cleaned data.

### Details

Retains genes detected (expression>0) in more than 3 cells and with mean normalized expression >= 10^-5. If min_detected_genes is defined all cells not reaching the threshold are removed. Otherwise, fits a normal distribution to the distribution of detected genes/cell and removes those cells with significantly few detected genes (FDR 5%). This fit is plotted for visual inspection. If is.counts==TRUE then each column is converted to counts per million (ignoring ERCC spike-ins if present).

### Value

A list with elements: data, the normalized filtered expression matrix; and labels, labels of the remaining cells.

### Examples

      library(M3DExampleData)
      # Remove all cells with < 2000 detected genes and convert to cpm
      cpm <- M3DropCleanData(Mmus_example_list$data, Mmus_example_list$labels,
    			is.counts=TRUE, min_detected_genes=2000)
      # Removes cells with significantly few detected genes (FDR=5%)
      filtered_only <- M3DropCleanData(Mmus_example_list$data, Mmus_example_list$labels,
    			is.counts=FALSE)
    #  QCed <- bg__filter_cells(Mmus_example_list$data[,1:10], Mmus_example_list$labels[1:10], suppress.plot=TRUE)

[Package M3Drop version 1.18.0 Index]