plot_cellheatmap: cell-rPLR outlier identification

Description Usage Arguments Value Author(s) References Examples

View source: R/Functions.R

Description

Plot function of algorithm for cellwise outlier diagnostics using robust pairwise log-ratios.

Usage

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plot_cellheatmap(data, type = "biweight", g1, g2, mainGroup = "max", 
             plotly = FALSE, grid=FALSE,title=NULL)

Arguments

data

dataset, either 'matrix' or 'data.frame'

type

type of weighting function, possible values are 'biweight', 'huber', 'hampel'

g1

vector with positions of samples from group 1

g2

vector with positions of samples from group 2

mainGroup

integer or character: group which is chosen as based. Possible values are: 1,'1' - group 1, 2, '2' - group2, 'all' - all samples, 'max' - the bigger group

plotly

logical, should interactive plotly be used.

grid

logical, should grid be added to the plot.

title

title of plot

Value

matrix with cellwise outlier information, in range <-1,1>.

Author(s)

Jan Walach <walach.jan@gmail.com>

References

'Cellwise outlier detection and biomarker identification in metabolomics based on pairwise log-ratios', Walach J., Filzmoser P., Kouril S., submitted

Examples

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set.seed(741)
data <- gendata1_c()$X
colnames(data) <- LETTERS[1:9]
plot_cellheatmap(data, type = "biweight", g1 = 1:20 , g2 = 21:40, mainGroup = "max",grid = TRUE,plotly = TRUE,title = 'Simulated example')

walachja/cellrPLR documentation built on May 22, 2019, 2:47 p.m.