modNormalize

modNormalize,ExprsArray-method

Specifies the <code>ExprsArray</code> object to undergo pre-processing.

object

A numeric vector. The margin by which to normalize.
Provide <code>MARGIN = 1</code> to normalize the feature vector.
Provide <code>MARGIN = 2</code> to normalize the subject vector.
Provide <code>MARGIN = c(1, 2)</code> to normalize by the subject vector
and then by the feature vector.

MARGIN

A logical scalar. Toggles whether to produce side-by-side plots
of the before and after <code>ExprsArray</code> summary.

plotSkip


<code>modNormalize</code> normalizes feature data.


Supervised machine learning has an increasingly important role in biological
studies. However, the sheer complexity of classification pipelines poses a significant
barrier to the expert biologist unfamiliar with machine learning. Moreover,
many biologists lack the time or technical skills necessary to establish their own
pipelines. This package introduces a framework for the rapid implementation of
high-throughput supervised machine learning built with the biologist user in mind.
Written by biologists, for biologists, this package provides a user-friendly interface
that empowers investigators to execute state-of-the-art binary and multi-class
classification, including deep learning, with minimal programming
experience necessary.

Thomas Quinn

exprso

Rapid Implementation of Machine Learning Algorithms for Genomic
Data

modNormalize function

<ul>
<li> <code>ExprsArray</code>: Method to normalize an <code>ExprsArray</code> object.
</li>
</ul>

modNormalize: Normalize Data

Description

Usage

Arguments

Value

Methods (by class)

Details

See Also