Preprocess a bigstatsr FBM for CLAMP — preprocessCLAMPFBM • CLAMP

Makes a writable copy of the input FBM, cleans it (log2 transform if needed, fill NAs), filters rows by mean/variance, and returns the filtered FBM plus stats and indices.

preprocessCLAMPFBM(
  fbm,
  mean_cutoff = NULL,
  var_cutoff = NULL,
  backingfile = NULL,
  block_size = 1000,
  ncores = 1
)

Arguments

fbm: A bigstatsr::FBM (genes x samples), possibly read-only.
mean_cutoff: Numeric or NULL. Minimum row mean to keep (NULL = no mean filter).
var_cutoff: Numeric or NULL. Minimum row variance to keep (NULL = no var filter).
backingfile: Character or NULL. Base name for the copy FBM and filtered FBM on disk. If NULL, defaults to paste0(fbm$backingfile, '_preproc') and '_filtered'.
block_size: Number of rows to process at a time when copying data. Default is 1000.
ncores: Integer; number of cores to use for parallel operations (default 1).

Value

A list with:

fbm_filtered: The filtered FBM (writable).
rowStats: List with row_means & row_variances for fbm_filtered.
kept_rows: Integer vector of original row indices that were retained.

Examples

library(bigstatsr)
# create a toy matrix and back it with an FBM
mat <- matrix(
    c(
        1, 2, 3, # geneA
        10, 20, 30, # geneB
        100, 200, 300 # geneC
    ),
    nrow = 3, byrow = TRUE,
    dimnames = list(c("geneA", "geneB", "geneC"), paste0("s", seq_len(3)))
)
fbm <- FBM(nrow(mat), ncol(mat), init = mat)

# preprocess without filtering (all genes kept)
res_all <- preprocessCLAMPFBM(fbm)
#> Applying log2 transformation
#> No NA values found