.TXI_sc_adaptive

Automatically selects the best TXI implementation based on dataset size
and available computational resources. Uses R implementation for smaller datasets
and C++ implementation with optimal parallelization for larger datasets.

internal

Investigate the evolution of biological processes by capturing evolutionary signatures in transcriptomes (Drost et al. (2018) <doi:10.1093/bioinformatics/btx835>). This package aims to provide a transcriptome analysis environment to quantify the average evolutionary age of genes contributing to a transcriptome of interest.

Hajk-Georg Drost

myTAI

Evolutionary Transcriptomics

Stefan Manolache

Jaruwatana Sodai Lotharukpong

Nikola Kalábová

Filipa Martins Costa

Kristian K Ullrich

.TXI_sc_adaptive function

<dl><dt>expression</dt>
<dd>Matrix of expression values, dgCMatrix</dd>
<dt>strata_values</dt>
<dd>Numeric vector of phylostratum values</dd>
<dt>force_method</dt>
<dd>Character, force specific method: "r", "cpp_simple", or "cpp_batched"</dd>
<dt>ncores</dt>
<dd>Integer, number of cores to use (default: parallel::detectCores())</dd></dl>

Arguments

Adaptive TXI calculation for single cell expression — .TXI_sc_adaptive

<dl>

<dt>expression</dt>
<dd>Matrix of expression values, dgCMatrix</dd>


<dt>strata_values</dt>
<dd>Numeric vector of phylostratum values</dd>


<dt>force_method</dt>
<dd>Character, force specific method: "r", "cpp_simple", or "cpp_batched"</dd>


<dt>ncores</dt>
<dd>Integer, number of cores to use (default: parallel::detectCores())</dd>

</dl>

.TXI_sc_adaptive: Adaptive TXI calculation for single cell expression

Description

Usage

Value

Arguments

Details