xAggregate: Function to aggregate data respecting number of features

In Pi: Leveraging Genetic Evidence to Prioritise Drug Targets at the Gene and Pathway Level

Description

xAggregate is supposed to aggregate data respecting number of features. Per row, the aggregated is the sum of two items: the number of features, and the sum of all but scaled into [0,0.9999999]. Also supported is the rank-transformation of the input data per column, binned into the predefined number of discrete bins.

Usage

xAggregate(data, bin = FALSE, nbin = 10, scale.log = TRUE, verbose =
TRUE)

Arguments

data	a data frame. The aggregation is done across columns per row. Each cell should contain positive values or NA; if infinite, it will be replaced with the maximum finite value
bin	logical to indicate whether the input data per column is rank-transformed into the predefined number of discrete bins. By default, it sets to false
nbin	the number of discrete bins. By default, it sets to 10 (only works when bin is true)
scale.log	logical to indicate whether the per-row sum is log-scaled. By default, it sets to true
verbose	logical to indicate whether the messages will be displayed in the screen. By default, it sets to true for display

Value

a data frame with an appended column 'Aggregate'

Note

None

See Also

xAggregate

Examples

RData.location <- "http://galahad.well.ox.ac.uk/bigdata"
## Not run: 
# HiC-gene pairs per cell types/states
g <- xRDataLoader(RData.customised='ig.PCHiC',
RData.location=RData.location)
df <- do.call(cbind, igraph::edge_attr(g))
# aggregate over cell types/states
data <- df
data[data<5] <- NA
res <- xAggregate(data)

## End(Not run)

Pi documentation built on Nov. 26, 2020, 2:01 a.m.