OutputResults

Output results into a zipped CSV file. Results include gene and metabolite pairs, along with model interaction p-values, and correlations in each group being evaluated.

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

OutputResults function

<dl><dt>inputResults</dt>
<dd>IntLimResults object with model results (output of ProcessResults())</dd>
<dt>filename</dt>
<dd>name of file to be output (default: 'tempdir/results.csv')</dd></dl>

Arguments

Output results into a zipped CSV file.  Results include gene and metabolite pairs, along with model interaction p-values, and correlations in each group being evaluated. — OutputResults

<dl>

<dt>inputResults</dt>
<dd>IntLimResults object with model results (output of ProcessResults())</dd>


<dt>filename</dt>
<dd>name of file to be output (default: 'tempdir/results.csv')</dd>

</dl>

Output results into a zipped CSV file.  Results include gene and metabolite pairs, along with model interaction p-values, and correlations in each group being evaluated.

OutputResults: Output results into a zipped CSV file. Results include gene and metabolite pairs, along with model interaction p-values, and correlations in each group being evaluated.

Description

Usage

Value

Arguments