bc_summary_barcode: Summary and evaluate barcode diversity

Description Usage Arguments Details Value Examples

Description

bc_summary_barcode evaluates sequence diversity metrics using the barcodes data in the cleanBc slot of BarcodeObj object. It also generates Lorenz curve and barcode frequency distribution graphs.

Usage

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bc_summary_barcode(barcodeObj, plot = TRUE, log_x = TRUE)

## S4 method for signature 'BarcodeObj'
bc_summary_barcode(barcodeObj, plot = TRUE, log_x = TRUE)

Arguments

barcodeObj

A BarcodeObj object.

plot

A logical value, if TRUE, draw the Lorenz curve and barcode distribution graphs.

log_x

A logical value, if TRUE, the x axis is logarized.

Details

Followings are the metrics used for evaluating the barcode diversity:

Richness: The unique barcodes number R, it evaluates the richness of the barcodes.

Shannon index: Shannon diversity index is weighted geometric average of the proportion p of barcodes.

H' = - ∑_{i=1}^{R}p_ilnp_i

Equitability index: Shannon equitability E_H characterize the evenness of the barcodes, it is a value between 0 and 1, with 1 being complete evenness.

E_H = H' / H'_{max} = H / ln(R)

Bit: Shannon entropy H, with a units of bit,

H = - ∑_{i=1}^{R}p_ilog_2p_i

Value

A data.frame with following columns:

Examples

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data(bc_obj)

# filter barcode by depth
bc_obj <- bc_cure_depth(bc_obj)

# Output the summary of the barcodes
bc_summary_barcode(bc_obj)

wenjie1991/CellBarocde documentation built on Dec. 23, 2021, 5:11 p.m.