set_default_fs_methods

Set Default Feature Selection Methods

The workflow is a versatile R package designed for comprehensive feature selection in bulk RNAseq datasets. Its key innovation lies in the seamless integration of the 'Python' 'scikit-learn' (<https://scikit-learn.org/stable/index.html>) machine learning framework with R-based bioinformatics tools. 'GeneSelectR' performs robust Machine Learning-driven (ML) feature selection while leveraging 'Gene Ontology' (GO) enrichment analysis as described by Thomas PD et al. (2022) <doi:10.1002/pro.4218>, using 'clusterProfiler' (Wu et al., 2021) <doi:10.1016/j.xinn.2021.100141> and semantic similarity analysis powered by 'simplifyEnrichment' (Gu, Huebschmann, 2021) <doi:10.1016/j.gpb.2022.04.008>. This combination of methodologies optimizes computational and biological insights for analyzing complex RNAseq datasets.

Damir Zhakparov

GeneSelectR

'GeneSelectR' - Comprehensive Feature Selection Workflow for
Bulk RNAseq Datasets

set_default_fs_methods function

<dl><dt>modules</dt>
<dd>A list containing the definitions for the Python modules and submodules.</dd>
<dt>max_features</dt>
<dd>The maximum number of features to consider.</dd>
<dt>random_state</dt>
<dd>An integer value setting the random seed for feature selection algorithms and cross validation procedure. By default set to NULL to use different random seed every time an algorithm is used. For reproducibility could be fixed, otherwise for an unbiased estimation should be left as NULL.</dd></dl>

Arguments

Set Default Feature Selection Methods — set_default_fs_methods

<dl>

<dt>modules</dt>
<dd>A list containing the definitions for the Python modules and submodules.</dd>


<dt>max_features</dt>
<dd>The maximum number of features to consider.</dd>


<dt>random_state</dt>
<dd>An integer value setting the random seed for feature selection algorithms and cross validation procedure. By default set to NULL to use different random seed every time an algorithm is used. For reproducibility could be fixed, otherwise for an unbiased estimation should be left as NULL.</dd>

</dl>

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set_default_fs_methods: Set Default Feature Selection Methods

Description

Usage

Value

Arguments