Filter rows of a Filebacked Big Matrix based on mean and variance

Source: R/utils.R

Filters an FBM based on row-level mean and variance thresholds, returning a new FBM with only the selected rows.

filterFBM(
  fbm,
  rowStats,
  keep_samples_idx = NULL,
  mean_cutoff = NULL,
  var_cutoff = NULL,
  backingfile = "filtered_fbm"
)

Arguments

fbm

A bigstatsr::FBM object.

rowStats

A list with numeric vectors row_means and row_variances.

keep_samples_idx

Optional integer vector of column indices to retain. Default is filtered_fbm.

mean_cutoff

Optional minimum mean threshold; rows with means below this are removed.

var_cutoff

Optional minimum variance threshold; rows with variances below this are removed.

backingfile

A character string specifying the filename (without extension) for the new FBM.

Value

A list with:

fbm_filtered

A new FBM object containing only filtered rows.

kept_rows

Indices of rows retained in the filtering step.

Details

This function creates a new FBM and copies over only the rows that pass the filtering criteria. The original FBM is unchanged.

Examples

fbm <- bigstatsr::FBM(5, 3, init = matrix(rnorm(15), nrow = 5))
rs <- list(
    row_means = rowMeans(fbm[]),
    row_variances = apply(fbm[], 1, var)
)
out <- filterFBM(fbm, rs,
    mean_cutoff = -0.2, var_cutoff = 0.5,
    backingfile = tempfile()
)