readSparseCounts {scuttle} | R Documentation

## Read sparse count matrix from file

### Description

Reads a sparse count matrix from file containing a dense tabular format.

### Usage

    readSparseCounts(
      file,
      sep = "\t",
      quote = NULL,
      comment.char = "",
      row.names = TRUE,
      col.names = TRUE,
      ignore.row = 0L,
      skip.row = 0L,
      ignore.col = 0L,
      skip.col = 0L,
      chunk = 1000L
    )

### Arguments

`file` | A string containing a file path to a count table, or a connection object opened in read-only text mode.
`sep` | A string specifying the delimiter between fields in `file`.
`quote` | A string specifying the quote character, e.g., in column or row names.
`comment.char` | A string specifying the comment character after which values are ignored.
`row.names` | A logical scalar specifying whether row names are present.
`col.names` | A logical scalar specifying whether column names are present.
`ignore.row` | An integer scalar specifying the number of rows to ignore at the start of the file, before the column names.
`skip.row` | An integer scalar specifying the number of rows to ignore at the start of the file, after the column names.
`ignore.col` | An integer scalar specifying the number of columns to ignore at the start of the file, before the column names.
`skip.col` | An integer scalar specifying the number of columns to ignore at the start of the file, after the column names.
`chunk` | A integer scalar indicating the chunk size to use, i.e., number of rows to read at any one time.

### Details

This function provides a convenient method for reading dense arrays from flat files into a sparse matrix in memory. Memory usage can be further improved by setting `chunk` to a smaller positive value.

The `ignore.*` and `skip.*` parameters allow irrelevant rows or columns to be skipped. Note that the distinction between the two parameters is only relevant when `row.names=FALSE` (for skipping/ignoring columns) or `col.names=FALSE` (for rows).

### Value

A dgCMatrix containing double-precision values (usually counts) for each row (gene) and column (cell).

### Author(s)

Aaron Lun

### See Also

`read.table`, `readMM`

### Examples

    outfile <- tempfile()
    write.table(data.frame(A=1:5, B=0, C=0:4, row.names=letters[1:5]),
        file=outfile, col.names=NA, sep="\t", quote=FALSE)

    readSparseCounts(outfile)

[Package scuttle version 1.4.0 Index]