getQuantileForInteractionCoefficient

Function that gets numeric cutoffs from percentile

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

getQuantileForInteractionCoefficient function

<dl><dt>tofilter</dt>
<dd>dataframe for percentile filtering</dd>
<dt>interactionCoeffPercentile</dt>
<dd>percentile cutoff for interaction coefficient (default bottom 10 percent (high negative coefficients) and top 10 percent (high positive coefficients))</dd></dl>

Arguments

Function that gets numeric cutoffs from percentile — getQuantileForInteractionCoefficient

<dl>

<dt>tofilter</dt>
<dd>dataframe for percentile filtering</dd>


<dt>interactionCoeffPercentile</dt>
<dd>percentile cutoff for interaction coefficient (default bottom 10 percent (high negative coefficients) and top 10 percent (high positive coefficients))</dd>

</dl>

getQuantileForInteractionCoefficient: Function that gets numeric cutoffs from percentile

Description

Usage

Value

Arguments