SQMtools (version 1.6.3)

subsetFun: Filter results by function

Description

Create a SQM object containing only the ORFs with a given function, and the contigs and bins that contain them.

Usage

subsetFun(
  SQM,
  fun,
  columns = NULL,
  ignore_case = TRUE,
  fixed = FALSE,
  trusted_functions_only = FALSE,
  ignore_unclassified_functions = FALSE,
  rescale_tpm = FALSE,
  rescale_copy_number = FALSE
)

Value

SQM object containing only the requested function.

Arguments

SQM

SQM object to be subsetted.

fun

character. Pattern to search for in the different functional classifications.

columns

character. Restrict the search to the provided column names from SQM$orfs$table. If not provided the search will be performed in all the columns containing functional information (default NULL).

ignore_case

logical Make pattern matching case-insensitive (default TRUE).

fixed

logical. If TRUE, pattern is a string to be matched as is. If FALSE the pattern is treated as a regular expression (default FALSE).

trusted_functions_only

logical. If TRUE, only highly trusted functional annotations (best hit + best average) will be considered when generating aggregated function tables. If FALSE, best hit annotations will be used (default FALSE).

ignore_unclassified_functions

logical. If FALSE, ORFs with no functional classification will be aggregated together into an "Unclassified" category. If TRUE, they will be ignored (default FALSE).

rescale_tpm

logical. If TRUE, TPMs for KEGGs, COGs, and PFAMs will be recalculated (so that the TPMs in the subset actually add up to 1 million). Otherwise, per-function TPMs will be calculated by aggregating the TPMs of the ORFs annotated with that function, and will thus keep the scaling present in the parent object (default FALSE).

rescale_copy_number

logical. If TRUE, copy numbers with be recalculated using the RecA/RadA coverages in the subset. Otherwise, RecA/RadA coverages will be taken from the parent object. By default it is set to FALSE, which means that the returned copy numbers for each function will represent the average copy number of that function per genome in the parent object.

See Also

subsetTax, subsetORFs, subsetSamples, combineSQM. The most abundant items of a particular table contained in a SQM object can be selected with mostAbundant.

Examples

data(Hadza)
Hadza.iron = subsetFun(Hadza, "iron")
Hadza.carb = subsetFun(Hadza, "Carbohydrate metabolism")
# Search for multiple patterns using regular expressions
Hadza.twoKOs = subsetFun(Hadza, "K00812|K00813", fixed=FALSE)