hanabi: hanabi

In charles-plessy/smallCAGEqc: ad-hoc QC functions for shallow-sequenced test CAGE libraries

Description

Rarefy data at multiple sample sizes, in preparation for plotting.

Usage

hanabi(expr_data, npoints = 20, step = 0.75, from = NULL)

Arguments

expr_data	An expression table where columns are samples and rows are features such as genes, TSS, etc, or a vector of counts.
npoints	The maximum number of rarefactions per sample.
step	Subsample sizes are calculated by taking the largest sample and multiplying it by the step "npoints" times.
from	Add one sample size (typically "0") in order to extend the plot on the left-hand side.

Details

The computation can be long, so the steps of rarefaction and plotting are kept separate.

The input must be a data frame, or a vector or a matrix, which will be coerced into a matrix. The data must be counts (tag counts, molecule counts, ...).

Value

A list-based object of class "hanabi".

See Also

'[.hanabi', as.list.hanabi, and vegan::rarecurve.

Other Hanabi functions: hanabiPlot, plot.hanabi, points.hanabi

Examples

bedFiles <- system.file(package = "smallCAGEqc", "extdata") %>%
              list.files("*BED", full.names = TRUE)
bed <- loadBED12(bedFiles)
rar <- tapply(bed$score, bed$library, hanabi, from = 0) %>%
         structure(class = "hanabi")  # tapply discards the class !
hanabiPlot(rar, GROUP = levels(bed$library))

charles-plessy/smallCAGEqc documentation built on May 13, 2019, 3:31 p.m.