preprocess {TSCAN} | R Documentation

## preprocess

### Description

preprocess the raw single-cell data

### Usage

    preprocess(data, clusternum = NULL, takelog = TRUE, logbase = 2,
      pseudocount = 1, minexpr_value = 1, minexpr_percent = 0.5,
      cvcutoff = 1)

### Arguments

`data` | The raw single_cell data, which is a numeric matrix or data.frame. Rows represent genes/features and columns represent single cells.
`clusternum` | The number of clusters for doing cluster, typically 5 percent of number of all genes. The clustering will be done after all the transformation and trimming. If NULL no clustering will be performed.
`takelog` | Logical value indicating whether to take logarithm
`logbase` | Numeric value specifiying base of logarithm
`pseudocount` | Numeric value to be added to the raw data when taking logarithm
`minexpr_value` | Numeric value specifying the minimum cutoff of log transformed (if takelog is TRUE) value
`minexpr_percent` | Numeric value specifying the lowest percentage of highly expressed cells (expression value bigger than minexpr_value) for the genes/features to be retained.
`cvcutoff` | Numeric value specifying the minimum value of coefficient of variance for the genes/features to be retained.

### Details

This function first takes logarithm of the raw data and then filters out genes/features in which too many cells are low expressed. It also filters out genes/features with low coefficient of variance which indicates the genes/features does not contain much information. The default setting will first take log2 of the raw data after adding a pseudocount of 1. Then genes/features in which at least half of cells have expression values are greater than 1 and the coefficeints of variance across all cells are at least 1 are retained.

### Value

Matrix or data frame with the same format as the input dataset.

### Author(s)

Zhicheng Ji, Hongkai Ji <zji4@zji4.edu>

### Examples

    data(lpsdata)
    procdata <- preprocess(lpsdata)

[Package TSCAN version 1.20.0 Index]