ScRNA_imp_MM

Perform ScRNA-seq imputation using mean/Median

Performing single-cell imputation in a way that preserves the biological variations in the data. The package clusters the input data to do imputation for each cluster, and do a distribution check using the Anderson-Darling normality test to impute dropouts using mean or median (Yazici, B., & Yolacan, S. (2007) <DOI:10.1080/10629360600678310>).

Mohamed Soudy

ScRNAIMM

Performing Single-Cell RNA-Seq Imputation by Using Mean/Median
Imputation

Sascha Jung

Antonio DEL SOL

ScRNA_imp_MM function

<dl><dt>ScRNA_filtered</dt>
<dd>ScRNA-seq data set generated by prepare_dataset function</dd>
<dt>cluster_labels</dt>
<dd>Cluster labels generated by cluster_cells function or user-defined</dd>
<dt>cells</dt>
<dd>Boolean whether to do the imputation based on cell clustering or not</dd>
<dt>genes</dt>
<dd>Boolean whether to do the imputation based on genes or not</dd></dl>

Arguments

Mohamed Soudy <a href="/link/Mohmedsoudy2009%40gmail.com?package=ScRNAIMM&version=0.1" data-mini-rdoc="ScRNAIMM::Mohmedsoudy2009@gmail.com">Mohmedsoudy2009@gmail.com</a>

Author

Perform ScRNA-seq imputation using mean/Median — ScRNA_imp_MM

<dl>

<dt>ScRNA_filtered</dt>
<dd>ScRNA-seq data set generated by prepare_dataset function</dd>


<dt>cluster_labels</dt>
<dd>Cluster labels generated by cluster_cells function or user-defined</dd>


<dt>cells</dt>
<dd>Boolean whether to do the imputation based on cell clustering or not</dd>


<dt>genes</dt>
<dd>Boolean whether to do the imputation based on genes or not</dd>

</dl>

Mohamed Soudy <a href='mailto:Mohmedsoudy2009@gmail.com'>Mohmedsoudy2009@gmail.com</a>

ScRNA_imp_MM: Perform ScRNA-seq imputation using mean/Median

Description

Usage

Value

Arguments

Author