getstatsOneLM

Function that runs linear models for analyte vs. all analytes of the other type

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

getstatsOneLM function

<dl><dt>form</dt>
<dd>LM formulat (typically m~g+t+g:t)</dd>
<dt>clindata</dt>
<dd>data frame with 1st column: expression of one analyte; 2nd column
sample type (e.g. cancer/non-cancer)</dd>
<dt>arraydata</dt>
<dd>matrix of analyte values</dd>
<dt>analytename</dt>
<dd>name of independent analyte in the model</dd>
<dt>suppressWarnings</dt>
<dd>whether or not to suppress warnings</dd></dl>

Arguments

Function that runs linear models for analyte vs. all analytes of the other type — getstatsOneLM

<dl>

<dt>form</dt>
<dd>LM formulat (typically m~g+t+g:t)</dd>


<dt>clindata</dt>
<dd>data frame with 1st column: expression of one analyte; 2nd column
sample type (e.g. cancer/non-cancer)</dd>


<dt>arraydata</dt>
<dd>matrix of analyte values</dd>


<dt>analytename</dt>
<dd>name of independent analyte in the model</dd>


<dt>suppressWarnings</dt>
<dd>whether or not to suppress warnings</dd>

</dl>

getstatsOneLM: Function that runs linear models for analyte vs. all analytes of the other type

Description

Usage

Arguments