Filters barcodes by counts

bc_cure_depth filters barcodes by the read counts or the UMI counts.

bc_cure_depth(barcodeObj, depth = 0, isUpdate = TRUE)

# S4 method for BarcodeObj
bc_cure_depth(barcodeObj, depth = 0, isUpdate = TRUE)

Arguments

barcodeObj

A BarcodeObj object.

depth

A numeric or a vector of numeric, specifying the threshold of minimum count for a barcode to keep. If the input is a vector and the vector length is not the same as the sample number, the element will be repeatedly used. And when the depth argument is a number with a negative value, automatic cutoff point will be chosen by bc_auto_cutoff function for each samples. See bc_auto_cutoff for details.

isUpdate

A logical value. If TRUE, the cleanBc slot in BarcodeObj will be used preferentially, otherwise the messyBc slot will be used. If no cleanBc is available, messyBc will be used.

Value

A BarcodeObj object with cleanBc slot updated or created.

Examples

data(bc_obj)

d1 <- data.frame(
    seq = c(
        "ACTTCGATCGATCGAAAAGATCGATCGATC",
        "AATTCGATCGATCGAAGAGATCGATCGATC",
        "CCTTCGATCGATCGAAGAAGATCGATCGATC",
        "TTTTCGATCGATCGAAAAGATCGATCGATC",
        "AAATCGATCGATCGAAGAGATCGATCGATC",
        "CCCTCGATCGATCGAAGAAGATCGATCGATC",
        "GGGTCGATCGATCGAAAAGATCGATCGATC",
        "GGATCGATCGATCGAAGAGATCGATCGATC",
        "ACTTCGATCGATCGAACAAGATCGATCGATC",
        "GGTTCGATCGATCGACGAGATCGATCGATC",
        "GCGTCCATCGATCGAAGAAGATCGATCGATC"
        ),
    freq = c(
        30, 60, 9, 10, 14, 5, 10, 30, 6, 4 , 6
        )
    )

pattern <- "([ACTG]{3})TCGATCGATCGA([ACTG]+)ATCGATCGATC"
bc_obj <- bc_extract(list(test = d1), pattern, sample_name=c("test"),
    pattern_type=c(UMI=1, barcode=2))

# Remove barcodes with depth < 5
(bc_cured <- bc_cure_depth(bc_obj, depth=5))
#> ------------
#> bc_cure_depth: isUpdate is TRUE, update the cleanBc.
#> ------------
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 3 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff
#> ----------
#> @messyBc: 1 sample(s) for raw barcodes:
#>     In sample $test there are: 10 Tags
#> ----------
#> @cleanBc: 1 samples for cleaned barcodes
#>     In sample $test there are: 4 barcodes 
bc_2matrix(bc_cured)
#>       test
#> AAAG    50
#> ACAAG    6
#> AGAAG   14
#> AGAG   104

# Use UMI information, filter the barcode < 5 UMI
bc_umi_cured <- bc_cure_umi(bc_obj, depth =0, doFish=TRUE, isUniqueUMI=TRUE)
bc_cure_depth(bc_umi_cured, depth = 5)
#> ------------
#> bc_cure_depth: isUpdate is TRUE, update the cleanBc.
#> ------------
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 3 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff
#> ----------
#> @messyBc: 1 sample(s) for raw barcodes:
#>     In sample $test there are: 10 Tags
#> ----------
#> @cleanBc: 1 samples for cleaned barcodes
#>     In sample $test there are: 0 barcodes 

###