Manages barcodes and samples in a BarcodeObj object

A set of functions and operators for subsetting or joining of BarcodeObj object(s). The bc_subset, * and - are used to select barcodes or samples in a BarcodeObj object. Two BarcodeObj objects can be joined by +.

bc_subset(
  barcodeObj,
  sample = NULL,
  barcode = NULL,
  black_list = NULL,
  is_sample_quoted_exp = FALSE
)

bc_merge(barcodeObj_x, barcodeObj_y)

# S4 method for class 'BarcodeObj'
bc_subset(
  barcodeObj,
  sample = NULL,
  barcode = NULL,
  black_list = NULL,
  is_sample_quoted_exp = FALSE
)

# S4 method for class 'BarcodeObj,BarcodeObj'
bc_merge(barcodeObj_x, barcodeObj_y)

# S3 method for class 'BarcodeObj'
barcodeObj_x + barcodeObj_y

# S3 method for class 'BarcodeObj'
barcodeObj - black_list

# S3 method for class 'BarcodeObj'
barcodeObj * white_list

Arguments

barcodeObj

A BarcodeObj object.

sample

A character vector or integer vector or an expression (expressio not applicable for [] operator), specifying the samples in the subsets. When the value is an expression, the columns in the metadata can be used as a variable.

barcode

A vector of integer or string, indicating the selected barcode.

black_list

A character vector, specifying the black list with excluded barcodes.

is_sample_quoted_exp

A logical value. If TRUE, the expression in sample argument will not be evaluated before executing the function.

barcodeObj_x

A BarcodeObj object.

barcodeObj_y

A BarcodeObj object.

white_list

A character vector, giving the barcode white list.

Value

A BarcodeObj object.

Details

bc_subset and []: Gets samples and barcodes subset from a BarcodeObj object.

+: Combines two BarcodeObj objects. The metadata, cleanBc and messyBc slot in the BarcodeObj objects will be joined. For the metadata slot, the sample_name column, and the Full outer join (the record in either BarcodeObj object) will be performed with row names as the key. The messyBc and cleanBc from two objects are combined by rows for the same sample from two BarcodeObj objects.

-: removes barcodes in the black_list.

*: selects barcodes in the white_list.

Examples

data(bc_obj)

bc_obj
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 3 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 10 Tags
#>     In sample $test2 there are: 9 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 4 barcodes
#>     In sample $test2 there are: 5 barcodes 

# Select barcodes
bc_subset(bc_obj, barcode = c("AACCTT", "AACCTT"))
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 3 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 0 Tags
#>     In sample $test2 there are: 0 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 0 barcodes
#>     In sample $test2 there are: 0 barcodes 
bc_obj[c("AGAG", "AAAG"), ]
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 3 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 6 Tags
#>     In sample $test2 there are: 5 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 2 barcodes
#>     In sample $test2 there are: 2 barcodes 

# Select samples by metadata
bc_meta(bc_obj)$phenotype <- c("l", "b")
bc_meta(bc_obj)
#>       raw_read_count barcode_read_count depth_cutoff phenotype
#> test1            184                178            5         l
#> test2            124                118            5         b
bc_subset(bc_obj, phenotype == "l")
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 1 sample(s) for raw barcodes:
#>     In sample $test1 there are: 10 Tags
#> ----------
#> @cleanBc: 1 samples for cleaned barcodes
#>     In sample $test1 there are: 4 barcodes 

# Select samples by sample name
bc_obj[, "test1"]
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 1 sample(s) for raw barcodes:
#>     In sample $test1 there are: 10 Tags
#> ----------
#> @cleanBc: 1 samples for cleaned barcodes
#>     In sample $test1 there are: 4 barcodes 
bc_obj[, c("test1", "test2")]
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 10 Tags
#>     In sample $test2 there are: 9 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 4 barcodes
#>     In sample $test2 there are: 5 barcodes 
bc_subset(bc_obj, sample = "test1", barcode = c("AACCTT", "AACCTT"))
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 1 sample(s) for raw barcodes:
#>     In sample $test1 there are: 0 Tags
#> ----------
#> @cleanBc: 1 samples for cleaned barcodes
#>     In sample $test1 there are: 0 barcodes 

# Apply barcode blacklist
bc_subset(
bc_obj,
    sample = c("test1", "test2"),
    barcode = c("AACCTT"))
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 0 Tags
#>     In sample $test2 there are: 0 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 0 barcodes
#>     In sample $test2 there are: 0 barcodes 

# Join two samples with different barcode sets
bc_obj["AGAG", "test1"] + bc_obj["AAAG", "test2"]
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 8 field(s) available:
#> raw_read_count.bc_obj["AGAG", "test1"]  barcode_read_count.bc_obj["AGAG", "test1"]  depth_cutoff.bc_obj["AGAG", "test1"]  phenotype.bc_obj["AGAG", "test1"]  raw_read_count.bc_obj["AAAG", "test2"]  barcode_read_count.bc_obj["AAAG", "test2"]  depth_cutoff.bc_obj["AAAG", "test2"]  phenotype.bc_obj["AAAG", "test2"]
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 3 Tags
#>     In sample $test2 there are: 2 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 1 barcodes
#>     In sample $test2 there are: 1 barcodes 

# Join two samples with overlap barcodes
bc_obj_join <- bc_obj["AGAG", "test1"] + bc_obj["AGAG", "test2"]
bc_obj_join
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 8 field(s) available:
#> raw_read_count.bc_obj["AGAG", "test1"]  barcode_read_count.bc_obj["AGAG", "test1"]  depth_cutoff.bc_obj["AGAG", "test1"]  phenotype.bc_obj["AGAG", "test1"]  raw_read_count.bc_obj["AGAG", "test2"]  barcode_read_count.bc_obj["AGAG", "test2"]  depth_cutoff.bc_obj["AGAG", "test2"]  phenotype.bc_obj["AGAG", "test2"]
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 3 Tags
#>     In sample $test2 there are: 3 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 1 barcodes
#>     In sample $test2 there are: 1 barcodes 
# The same barcode will be removed after applying bc_cure_depth()
bc_cure_depth(bc_obj_join)
#> ------------
#> bc_cure_depth: isUpdate is TRUE, update the cleanBc.
#> ------------
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 9 field(s) available:
#> raw_read_count.bc_obj["AGAG", "test1"]  barcode_read_count.bc_obj["AGAG", "test1"]  depth_cutoff.bc_obj["AGAG", "test1"]  phenotype.bc_obj["AGAG", "test1"]  raw_read_count.bc_obj["AGAG", "test2"]  barcode_read_count.bc_obj["AGAG", "test2"]  depth_cutoff.bc_obj["AGAG", "test2"]  phenotype.bc_obj["AGAG", "test2"]  depth_cutoff
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 3 Tags
#>     In sample $test2 there are: 3 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 1 barcodes
#>     In sample $test2 there are: 1 barcodes 

# Remove barcodes
bc_obj
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 10 Tags
#>     In sample $test2 there are: 9 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 4 barcodes
#>     In sample $test2 there are: 5 barcodes 
bc_obj - "AAAG"
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 7 Tags
#>     In sample $test2 there are: 7 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 3 barcodes
#>     In sample $test2 there are: 4 barcodes 

# Select barcodes in a whitelist
bc_obj
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 10 Tags
#>     In sample $test2 there are: 9 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 4 barcodes
#>     In sample $test2 there are: 5 barcodes 
bc_obj * "AAAG"
#> Bonjour le monde, This is a BarcodeObj.
#> ----------
#> It contains: 
#> ----------
#> @metadata: 4 field(s) available:
#> raw_read_count  barcode_read_count  depth_cutoff  phenotype
#> ----------
#> @messyBc: 2 sample(s) for raw barcodes:
#>     In sample $test1 there are: 3 Tags
#>     In sample $test2 there are: 2 Tags
#> ----------
#> @cleanBc: 2 samples for cleaned barcodes
#>     In sample $test1 there are: 1 barcodes
#>     In sample $test2 there are: 1 barcodes 
###