Compute log R ratios

Computes log R ratios from raw count matrices within muscadet objects. The log R ratios values are computed based on read counts from a sample muscadet object versus read counts a the reference muscadet object. In the output sample muscadet object, the newly computed matrix of log R ratios is added for the selected omic.

Usage

computeLogRatio(
  x,
  reference,
  omic,
  method = NULL,
  new.label.features = NULL,
  remove.raw = TRUE,
  quiet = FALSE,
  all_steps = FALSE,
  ...
)

Arguments

x

A muscadet object containing sample data (muscadet).

reference

Another muscadet object containing reference data (muscadet).

omic

Name of the omic to apply this function (character string).

method

Method to apply to the selected omic (character string). Supported methods are "ATAC" and "RNA":

"ATAC" method calls for computeLogRatioATAC() function
"RNA" method calls for computeLogRatioRNA() function

If NULL and if the omic type is either "ATAC" or "RNA", the corresponding method will be applied.

new.label.features

New label for features (character string). If NULL, the label remains unchanged when using the "RNA" method and becomes "windows of peaks" when using the "ATAC" method.

remove.raw

TRUE or FALSE (logical). Whether to remove raw count matrices. TRUE by default to reduce object size. Setting it to FALSE will keep raw count matrices within the object.

quiet

Logical. If TRUE, suppresses informative messages during execution. Default is FALSE.

all_steps

Logical value to indicate whether matrices at each step of the log ratio computation are kept and returned (logical). IMPORTANT: if TRUE, the function does not return an updated muscadet object but a list with matrices at each step of the log ratio computation (see Value section). Default is FALSE.

...

Arguments passed on to computeLogRatioATAC, computeLogRatioRNA

windowSize: Size of windows in base pairs (integer value). By default: 10e6 (10 Mbp).
slidingSize: Distance between start positions of sliding windows in base pairs (integer value). If set to the same value as windowSize, the windows don't overlap. By default: 2e6 (2 Mbp).
minReads: Minimum read average per window in reference cells (integer value). By default: 5.
minPeaks: Minimum number of peaks per window (integer value). By default: 100.
genesPerWindow: Number of genes per moving window (integer value). By default: 101.
refReads: Minimum of reads in reference cells (integer value). By default: 100.
refMeanReads: Minimum of average reads per reference cell (integer value). By default: 0.01.
thresh_capping: Threshold to cap the range of log R ratio values (numeric value). By default: 3.

Value

A muscadet object corresponding to the sample muscadet object (x) containing the computed log R ratio matrix in the coverage slot of the selected omic.

If the all_steps argument is set to TRUE, it returns a list with intermediate matrices matTumor and matRef from every step from step01 to step08 (no step06 for method = "ATAC"), coord table of features coordinates and associated data, and params list of parameters used for the function.

Details

Log R ratios computation steps are described in functions:

Examples

# Create muscomic objects
atac <- CreateMuscomicObject(
  type = "ATAC",
  mat_counts = mat_counts_atac_tumor,
  allele_counts = allele_counts_atac_tumor,
  features = peaks
)
rna <- CreateMuscomicObject(
  type = "RNA",
  mat_counts = mat_counts_rna_tumor,
  allele_counts = allele_counts_rna_tumor,
  features = genes
)
atac_ref <- CreateMuscomicObject(
  type = "ATAC",
  mat_counts = mat_counts_atac_ref,
  allele_counts = allele_counts_atac_ref,
  features = peaks
)
rna_ref <- CreateMuscomicObject(
  type = "RNA",
  mat_counts = mat_counts_rna_ref,
  allele_counts = allele_counts_rna_ref,
  features = genes
)

# Create muscadet objects
muscadet <- CreateMuscadetObject(
  omics = list(atac, rna),
  bulk.lrr = bulk_lrr,
  bulk.label = "WGS",
  genome = "hg38"
)
muscadet_ref <- CreateMuscadetObject(
  omics = list(atac_ref, rna_ref),
  genome = "hg38"
)

# compute log R ratios for ATAC
muscadet <- computeLogRatio(
  x = muscadet,
  reference = muscadet_ref,
  omic = "ATAC",
  method = "ATAC",
  minReads = 1, # low value for example subsampled datasets
  minPeaks = 1 # low value for example subsampled datasets
)
#> -- computeLogRatio: Method 'ATAC' using computeLogRatioATAC().
#> Step 01 - Group peaks in windows: window size set at 10 Mb, sliding by 2 Mb
#> Step 02 - Filtering windows: Minimum of 1 peaks per window with a minimum average of 1 read(s)
#> Step 03 - Normalization for sequencing depth: Normalized counts per million
#> Step 04 - Log transformation and normalization by reference data: log R ratio
#> Step 05 - Capping the range of values: threshold = 3
#> Step 06 - [No step 06 for scATAC-seq]
#> Step 07 - Centering of cells
#> Step 08 - Correcting by reference variability
#> Done.

# compute log R ratios for RNA
muscadet <- computeLogRatio(
  x = muscadet,
  reference = muscadet_ref,
  omic = "RNA",
  method = "RNA",
  refReads = 2 # low value for example subsampled datasets
)
#> -- computeLogRatio: Method 'RNA' using computeLogRatioRNA().
#> Step 01 - Match genes in count matrix with coordinates
#> Step 02 - Filtering genes: Minimum of 2 read(s) in reference cells and minimum of 0.01 read(s) in average per reference cell
#> Step 03 - Normalization for sequencing depth: Normalized counts per million
#> Step 04 - Log transformation and normalization by reference data: log R ratio
#> Step 05 - Capping the range of values: threshold = 3
#> Step 06 - Smoothing values on gene windows: 101 genes per window
#> Step 07 - Centering of cells
#> Step 08 - Correcting by reference variability
#> Done.

Usage

Arguments

Value

Details

See also

Examples