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Load MAF data from a text file or data table into your CESAnalysis. Column names are expected to match MAF format specifications (Chromosome, Start_Position, etc.). It's recommended to use preload_maf() to prep the input (including, optionally, liftOver conversion of genomic coordinates), but if you have clean MAF data, you can run this function directly. By default, data is assumed to be derived from whole-exome sequencing. Whole-genome data and targeted sequencing data are also supported when the coverage option is specified.


  cesa = NULL,
  maf = NULL,
  maf_name = character(),
  coverage = "exome",
  covered_regions = NULL,
  covered_regions_name = NULL,
  covered_regions_padding = 0,
  sample_data_cols = character(),
  enforce_default_exome_coverage = FALSE





Path of tab-delimited text file in MAF format, or an MAF in data.table or data.frame format.


Optionally, a name to identify samples coming from the current MAF. Used to populate the maf_source field of the CESAnalysis samples table.


exome, genome, or targeted (default exome).


optional for exome, required for targeted: a GRanges object or a BED file of covered intervals matching the CESAnalysis genome.


a name describing the covered regions (e.g., "my_custom_targeted_regions"); required when covered_regions are supplied.


How many bases (default 0) to expand start and end of each covered_regions interval, to include variants called just outside of targeted regions. Consider setting from 0-100bp, or up to the sequencing read length. If the input data has been trimmed to the targeted regions, leave set to 0.


MAF columns containing sample-level data (e.g., tumor grade) that you would like to have copied into the CESAnalysis samples table.


When loading default exome data, exclude records that aren't covered in the default exome capture intervals included with CES genome reference data (default FALSE).


CESAnalysis with the specified MAF data loaded. The MAF data table includes CES-generated variant IDs, a list of all genes overlapping the site, and top_gene and top_consequence columns that give the most significant annotated coding changes for each mutation record. Annotation precedence is determined by MAF prevalence (usually equal), essential splice status, premature stop codon, nonsilent status, MAF mutation prevalence across the transcript (often favors longer transcripts), and finally alphabetical order. The columns are recalculated when more data is loaded, so changes in MAF prevalence can change which variants are highlighted. Note that

[CESAnalysis]$variants contains more information about all top_consequence variants and all noncoding variants from the MAF.