README.md

In csoneson/iCOBRA: Comparison and Visualization of Ranking and Assignment Methods

iCOBRA - Interactive benchmarking of ranking and assignment methods

iCOBRA is a package to calculate and visualize performance metrics for ranking and binary assignment methods. A typical use case could be, for example, comparing methods calling differential expression in gene expression experiments, which could be seen as either a ranking problem (estimating the correct effect size and ordering the genes by significance) or a binary assignment problem (classifying the genes into differentially expressed and non-differentially expressed).

iCOBRA can be used either directly from the console, or via the interactive shiny application (see the function COBRAapp()). It can also be accessed from the web server http://imlspenticton.uzh.ch:3838/iCOBRA/

We have also collected a set of benchmarking data sets, addressing different aspects of genomic data analysis. The collection is reachable via the following link: http://imlspenticton.uzh.ch/robinson_lab/benchmark_collection/

Installation

iCOBRA can be installed from Bioconductor using BiocManager:

install.packages("BiocManager")
BiocManager::install("iCOBRA")

or, optionally,

BiocManager::install("markrobinsonuzh/iCOBRA")

Quick start guide

The iCOBRA workflow starts from an object of class COBRAData, containing (adjusted) p-values and/or scores for a set of features as well as the true status of the features. An example data set is provided in the package

library(iCOBRA)
data(cobradata_example)

The function calculate_performance() calculates the different performance metrics for a COBRAData object. By default, all performance metrics are calculated, but a subset can be selected using the aspects argument.

cobraperf <- calculate_performance(cobradata_example, binary_truth = "status",
                                   cont_truth = "logFC", 
                                   aspects = c("fdrtpr", "fdrtprcurve", 
                                               "corr"))

Next, the performance metrics are prepared for plotting using the prepare_for_plot() function. This function defines colors for the various methods and can also be used for selecting only a subset of the methods for visualization, without having to recalculate the performance metrics.

cobraplot <- prepare_data_for_plot(cobraperf, colorscheme = "Set2",
                                   keepmethods = c("voom", "edgeR"))

The resulting object can then be used to generate plots of the selected aspects.

plot_fdrtprcurve(cobraplot)
plot_corr(cobraplot, corrtype = "spearman")

Vignette

The vignette can be found in the vignettes/ directory. Further information is also available in the 'Instructions' tab of the shiny app. After installation, the vignette can be accessed from the R console by typing

browseVignettes("iCOBRA")

Benchmarking data set collection

To facilitate future benchmarking studies, we have collected a set of benchmarking data sets on http://imlspenticton.uzh.ch/robinson_lab/benchmark_collection/. The page provides links to raw data as well as evaluation results suitable for import into iCOBRA.

csoneson/iCOBRA documentation built on Nov. 5, 2024, 7:20 p.m.