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Computes the abundance for every integration event in the input data frame.

Source: R/analysis-functions.R
compute_abundance.Rd

[Stable] Abundance is obtained for every integration event by calculating the ratio between the single value and the total value for the given group.

Usage

compute_abundance(
  x,
  columns = c("fragmentEstimate_sum"),
  percentage = TRUE,
  key = c("SubjectID", "CellMarker", "Tissue", "TimePoint"),
  keep_totals = FALSE
)

Arguments

x

An integration matrix - aka a data frame that includes the mandatory_IS_vars() as columns. The matrix can either be aggregated (via aggregate_values_by_key()) or not.

columns

A character vector of column names to process, must be numeric or integer columns

percentage

Add abundance as percentage?

key

The key to group by when calculating totals

keep_totals

A value between TRUE, FALSE or df. If TRUE, the intermediate totals for each group will be kept in the output data frame as a dedicated column with a trailing "_tot". If FALSE, totals won't be included in the output data frame. If df, the totals are returned to the user as a separate data frame, together with the abundance data frame.

Value

Either a single data frame with computed abundance values or a list of 2 data frames (abundance_df, quant_totals)

Details

Abundance will be computed upon the user selected columns in the columns parameter. For each column a corresponding relative abundance column (and optionally a percentage abundance column) will be produced.

Required tags

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

See also

Other Analysis functions: CIS_grubbs(), HSC_population_size_estimate(), cumulative_is(), gene_frequency_fisher(), is_sharing(), iss_source(), sample_statistics(), top_integrations(), top_targeted_genes()

Examples

data("integration_matrices", package = "ISAnalytics")
abund <- compute_abundance(
    x = integration_matrices,
    columns = "fragmentEstimate",
    key = "CompleteAmplificationID"
)
head(abund)
#>    chr integration_locus strand     GeneName GeneStrand
#> 1:  16          68164148      +       NFATC3          +
#> 2:   4         129390130      + LOC100507487          +
#> 3:   5          84009671      -        EDIL3          -
#> 4:  12          54635693      -         CBX5          -
#> 5:   5          84009671      -        EDIL3          -
#> 6:  12          54635693      -         CBX5          -
#>                                                 CompleteAmplificationID
#> 1: PJ01_POOL01_LTR75LC38_PT001_PT001-103_lenti_GLOBE_PB_1_SLiM_0060_MNC
#> 2:  PJ01_POOL01_LTR53LC32_PT001_PT001-81_lenti_GLOBE_BM_1_SLiM_0180_MNC
#> 3:  PJ01_POOL01_LTR53LC32_PT001_PT001-81_lenti_GLOBE_BM_1_SLiM_0180_MNC
#> 4:  PJ01_POOL01_LTR83LC66_PT001_PT001-81_lenti_GLOBE_BM_1_SLiM_0180_MNC
#> 5:  PJ01_POOL01_LTR83LC66_PT001_PT001-81_lenti_GLOBE_BM_1_SLiM_0180_MNC
#> 6:  PJ01_POOL01_LTR27LC94_PT001_PT001-81_lenti_GLOBE_BM_1_SLiM_0180_MNC
#>    seqCount fragmentEstimate fragmentEstimate_RelAbundance
#> 1:      182        102.94572                     0.5120030
#> 2:    23219         68.73747                     0.1472510
#> 3:    20205         67.12349                     0.1437935
#> 4:    13269         65.15760                     0.1461826
#> 5:    14748         61.46981                     0.1379090
#> 6:    12588         60.84781                     0.1718091
#>    fragmentEstimate_PercAbundance
#> 1:                       51.20030
#> 2:                       14.72510
#> 3:                       14.37935
#> 4:                       14.61826
#> 5:                       13.79090
#> 6:                       17.18091