PlotFoldOverlapUpSet

Makes an UpSet plot showing the filtered pairs of analytes found in each fold.
This plot should only be made for cross-validation data.

This workflow takes analyte levels from two different types of analytes (e.g. gene expression and metabolite abundance), meta-information on each analyte type, and sample outcome and metadata to identify analyte pairs that are significantly associated with a continuous or discrete outcome (e.g. drug response or tumor type). The following references describe the methods in this package: (1) Jalal K. Siddiqui, et al. (2018) <doi:10.1186/s12859-018-2085-6>, (2) Andrew Patt, et al. (2019) <doi:10.1007/978-1-4939-9027-6_23>.

Tara Eicher

IntLIM

Integration of Omics Data Using Linear Modeling

Jalal Siddiqui

Shunchao Wang

Rohith Vanam

Elizabeth Baskin

Kyle Spencer

Ewy Mathe

PlotFoldOverlapUpSet function

<dl><dt>inputResults</dt>
<dd>List of outputs of ProcessResultsAllFolds(), each of which
is a list of IntLIMResults.</dd></dl>

Arguments

Makes an UpSet plot showing the filtered pairs of analytes found in each fold.
This plot should only be made for cross-validation data. — PlotFoldOverlapUpSet

<dl>

<dt>inputResults</dt>
<dd>List of outputs of ProcessResultsAllFolds(), each of which
is a list of IntLIMResults.</dd>

</dl>

PlotFoldOverlapUpSet: Makes an UpSet plot showing the filtered pairs of analytes found in each fold. This plot should only be made for cross-validation data.

Description

Usage

Value

Arguments