BarcodeObj: BarcodeObj object

In wenjie1991/CellBarcode: Cellular DNA Barcode Analysis toolkit

BarcodeObj object

Description

A S4 object holds the barcode data and samples' metadata. A set of operations can be applied to the BarcodeObj object for quality control and selecting barcodes/samples subset.

Details

The BarcodeObj object is a S4 object, it has three slots, which can be access by "@" operator, they are messyBc, cleanBc and metadata. A BarcodeObj object can be generated by bc_extract function. The bc_extract function can use various data types as input, such as data.frame, fastq files, or ShortReadQ.

Slot messyBc is a list that holds the raw barcodes sequence without filtering, where each element is a data.table corresponding to the successive samples. Each table has 3 columns: 1. umi_seq (optional): UMI sequence. 2. barcode_seq: barcode sequence. 3. count: how many reads a full sequence has. In this table, barcode_seq value can be duplicated, as two different full read sequences can have the same barcode sequence, due to the diversity of the UMI or mutations in the constant region.

Slot cleanBc is a list holds the barcodes sequence after filtering, where each element is a data.table corresponding to the successive samples. The "cleanBc" slot contains 2 columns 1. barcode_seq: barcode sequence 2. counts: reads count, or UMI count if the cleanBc was created by bc_cure_umi.

Value

A BarcodeObj object.

Examples

#######
# Create BarcodeObj with fastq file
fq_file <- system.file("extdata", "simple.fq", package="CellBarcode")
library(ShortRead)
bc_extract(fq_file, pattern = "AAAAA(.*)CCCCC")

#######
# data manipulation on BarcodeObj object
data(bc_obj)

bc_obj

# Select barcodes
bc_subset(bc_obj, barcode = c("AACCTT", "AACCTT"))
bc_obj[c("AGAG", "AAAG"), ]

# Select samples by metadata
bc_meta(bc_obj)$phenotype <- c("l", "b")
bc_meta(bc_obj)
bc_subset(bc_obj, sample = phenotype == "l")

# Select samples by sample name
bc_obj[, "test1"]
bc_obj[, c("test1", "test2")]
bc_subset(bc_obj, sample = "test1", barcode = c("AACCTT", "AACCTT"))

# Apply barcodes blacklist
bc_subset(
bc_obj,
    sample = c("test1", "test2"),
    barcode = c("AACCTT"))

# Join two samples with no barcodes overlap
bc_obj["AGAG", "test1"] + bc_obj["AAAG", "test2"]

# Join two samples with overlap barcodes
bc_obj_join <- bc_obj["AGAG", "test1"] + bc_obj["AGAG", "test2"]
bc_obj_join
# The same barcode will be merged after applying bc_cure_depth()
bc_cure_depth(bc_obj_join)

# Remove barcodes
bc_obj
bc_obj - "AAAG"

# Select barcodes in a white list
bc_obj
bc_obj * "AAAG"
###

wenjie1991/CellBarcode documentation built on April 17, 2024, 4:40 a.m.