Description Usage Arguments Details Value Author(s) References Examples
View source: R/app.R View source: R/cell_shinyApp.R
Shiny app:Plot function of algorithm for cellwise outlier diagnostics using robust pairwise log-ratios.
1 | cell_shinyApp(data, g1, g2, mainGroup = "max", mainGroup2 = "all", simul = FALSE)
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data |
dataset, either 'matrix' or 'data.frame' |
g1 |
vector with positions of samples from group 1 |
g2 |
vector with positions of samples from group 2 |
mainGroup |
first plotly: integer or character: group which is chosen as based. Possible values are: |
mainGroup2 |
second plotly: integer or character: group which is chosen as based. Possible values are: |
simul |
compute cellwise outlier diagnostics simultaneously, might be hard on memory (RAM) |
For an easier exploration and understanding of the data, a Shiny app is included. Shiny , an open source R package, is a web application and serves as an interactive tool for visualization. The Shiny app allows to interactively apply different weighting and aggregation functions for the cell-rPLR algorithm, and supports zooming into regions of the data matrix to see more details. Moreover, the variables can be interactively ordered based on their importance for the group discrimination.
Shiny app is launched.
Jan Walach <walach.jan@gmail.com>
'Cellwise outlier detection and biomarker identification in metabolomics based on pairwise log-ratios', Walach J., Filzmoser P., Kouril S., submitted
1 2 3 4 | set.seed(741)
data <- gendata1_c()$X
colnames(data) <- LETTERS[1:9]
cell_shinyApp(data, g1 = 1:20 , g2 = 21:40,simul = TRUE)
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