Identifies and removes collisions

A collision is an integration (aka a unique combination of the provided mandatory_IS_vars()) which is observed in more than one independent sample. The function tries to decide to which independent sample should an integration event be assigned to, and if no decision can be taken, the integration is completely removed from the data frame. For more details refer to the vignette "Collision removal functionality": vignette("workflow_start", package = "ISAnalytics")

Usage

remove_collisions(
  x,
  association_file,
  independent_sample_id = c("ProjectID", "SubjectID"),
  date_col = "SequencingDate",
  reads_ratio = 10,
  quant_cols = c(seqCount = "seqCount", fragmentEstimate = "fragmentEstimate"),
  fold_threshold = 10,
  report_path = default_report_path(),
  max_workers = NULL
)

Arguments

x

Either a multi-quantification matrix (recommended) or a named list of matrices (names must be quantification types)

association_file

The association file imported via import_association_file()

independent_sample_id

A character vector of column names that identify independent samples

date_col

The date column that should be considered.

reads_ratio

Deprecated alias for fold_threshold, kept for backward compatibility. If both parameters are supplied they must have the same value.

quant_cols

A named character vector where names are quantification types and values are the names of the corresponding columns. The quantification seqCount MUST be included in the vector.

fold_threshold

A single numeric value greater than 1. For each collision, the sequence count values are summed within independent samples and compared to the maximum summed sequence count observed for the same integration. Observations from independent samples with max(seqCount) / seqCount >= fold_threshold are removed before applying the temporal rule. The default is 10, and a ratio exactly equal to the threshold is considered sufficient for removal. If more than one independent sample is not clearly separated by this fold rule, only those remaining observations are passed to the temporal rule. Zero sequence counts are allowed: if the maximum abundance is positive, zero-abundance observations are removed by the fold rule; if all abundances are zero, the fold rule is unresolved and the temporal rule is used. Missing, non-finite or negative sequence counts are rejected.

report_path

The path where the report file should be saved. Can be a folder or NULL if no report should be produced. Defaults to {user_home}/ISAnalytics_reports.

max_workers

Maximum number of parallel workers to distribute the workload. If NULL (default) produces the maximum amount of workers allowed, a numeric value is requested otherwise. WARNING: a higher number of workers speeds up computation at the cost of memory consumption! Tune this parameter accordingly.

Value

Either a multi-quantification matrix or a list of data frames

Required tags

The function will explicitly check for the presence of these tags:

• project_id

• pool_id

• pcr_replicate

See also

Other Data cleaning and pre-processing: aggregate_metadata(), aggregate_values_by_key(), compute_near_integrations(), default_meta_agg(), outlier_filter(), outliers_by_pool_fragments(), purity_filter(), realign_after_collisions(), threshold_filter()

Examples

data("integration_matrices", package = "ISAnalytics")
data("association_file", package = "ISAnalytics")
no_coll <- remove_collisions(
    x = integration_matrices,
    association_file = association_file,
    fold_threshold = 10,
    report_path = NULL
)
#> Identifying collisions...
#> Processing collisions...
#> Finished!
head(no_coll)
#> # A tibble: 6 × 8
#>   chr   integration_locus strand GeneName GeneStrand CompleteAmplificationID    
#>   <chr>             <dbl> <chr>  <chr>    <chr>      <chr>                      
#> 1 1              16602483 +      FBXO42   -          PJ01_POOL01_LTR83LC46_PT00…
#> 2 1              16602483 +      FBXO42   -          PJ01_POOL01_LTR37LC2_PT001…
#> 3 1              16602483 +      FBXO42   -          PJ01_POOL01_LTR85LC54_PT00…
#> 4 1              26446899 +      PDIK1L   +          PJ01_POOL01_LTR85LC54_PT00…
#> 5 1              26446899 +      PDIK1L   +          PJ01_POOL01_LTR83LC46_PT00…
#> 6 1              26446899 +      PDIK1L   +          PJ01_POOL01_LTR69LC52_PT00…
#> # ℹ 2 more variables: seqCount <dbl>, fragmentEstimate <dbl>