Get SSM By Patients.

Get MAF-format data frame for more than one patient.

Usage

get_ssm_by_patients(
  these_patient_ids,
  these_samples_metadata,
  projection = "grch37",
  this_seq_type = "genome",
  tool_name = "slms-3",
  this_study,
  verbose = FALSE,
  ...
)

Arguments

these_patient_ids

A vector of patient IDs that you want results for. The user can also use a metadata table that has been subset to the patient IDs of interest (see these_samples_metadata).

these_samples_metadata

A metadata subset to contain the rows corresponding to the patients of interest. If the vector of patient IDs is missing (these_patient_ids), this function will default to all patient IDs in the metadata table given to this parameter.

projection

Obtain variants projected to this reference (one of grch37 or hg38). Default is grch37.

this_seq_type

The seq type you want results for. Default is "genome".

tool_name

Optionally specify which tool to report variant from. The default is slms-3, also supports "publication" to return the exact variants as reported in the original papers.

this_study

Optionally specify first name of the author for the paper from which the variants should be returned for. This parameter can either be a vector of indexes (integer) or a vector of characters (matching columns in MAF).

verbose

Set to FALSE to minimize the output to console. Default is TRUE. This parameter also dictates the verbosity of any helper function internally called inside the main function.

...

Any additional parameters.

Value

A data frame with SSM calls for the selected patients in MAF format.

Details

This function returns variants from a set of patients. This function internally calls get_ssm_by_samples. Thus, the main contents of this function is to wrangle the provided patient IDs, so that the corresponding sample IDs can be provided to the internal call of get_ssm_by_samples. This function expects either a vector of patient IDs (these_patients_ids) or an already subset metadata table (these_samples_metadata).

Examples

# Lets find which patient_id occur more than once in the metadata first
my_ids = get_gambl_metadata(seq_type_filter = c("genome","capture")) %>%
             dplyr::group_by(patient_id) %>%
             dplyr::tally() %>%
             dplyr::filter(n>1) %>%
             dplyr::pull(patient_id)
#> Using the bundled metadata in GAMBLR.data...

#now let's get every SSM for all samples from these patients
patient_maf = get_ssm_by_patients(these_patient_ids = my_ids)
#> Using the bundled metadata in GAMBLR.data...
#> Patient IDs and metadata were provided, this function will resort to all available patient IDs in the provided metadata.
#> Using the bundled SSM calls (.maf) calls in GAMBLR.data...
patient_maf %>% dplyr::group_by(Tumor_Sample_Barcode) %>% 
                dplyr::count() %>% head()
#> genomic_data Object
#> Genome Build: grch37 
#> Showing first 10 rows:
#>   Tumor_Sample_Barcode   n
#> 1      00-14595_tumorA 476
#> 2      00-14595_tumorB 596
#> 3      00-14595_tumorC 679
#> 4      00-14595_tumorD 679
#> 5      00-15201_tumorA 208
#> 6      00-15201_tumorB 142