createOmicsData

Processing and analyzing omics data from genomics, transcriptomics, proteomics, and metabolomics platforms. It provides functions for preprocessing, normalization, visualization, and statistical analysis, as well as machine learning algorithms for predictive modeling. 'omicsTools' is an essential tool for researchers working with high-throughput omics data in fields such as biology, bioinformatics, and medicine.The QC-RLSC (quality control–based robust LOESS signal correction) algorithm is used for normalization. Dunn et al. (2011) <doi:10.1038/nprot.2011.335>.

Yaoxiang Li

omicsTools

Omics Data Process Toolbox

createOmicsData function

<dl><dt>data</dt>
<dd>The data frame containing the data. If not provided, synthetic data will be generated.</dd>
<dt>n_samples</dt>
<dd>The number of samples to generate if data is not provided. Defaults to 100.</dd>
<dt>n_features</dt>
<dd>The number of features to generate if data is not provided. Defaults to 2000.</dd></dl>

Arguments

Constructor for OmicsData — createOmicsData

<dl>

<dt>data</dt>
<dd>The data frame containing the data. If not provided, synthetic data will be generated.</dd>


<dt>n_samples</dt>
<dd>The number of samples to generate if data is not provided. Defaults to 100.</dd>


<dt>n_features</dt>
<dd>The number of features to generate if data is not provided. Defaults to 2000.</dd>

</dl>

createOmicsData: Constructor for OmicsData

Description

Usage

Value

Arguments

Examples