nnls_deconv

Estimate cell type relative proportion

Methods for analyzing DNA methylation data via Most Recurrent Methylation Patterns (MRMPs). Supports cell-type annotation, spatial deconvolution, unsupervised clustering, and cancer cell-of-origin inference. Includes C-backed summaries for YAME “.cg/.cm” files (overlap counts, log2 odds ratios, beta/depth aggregation), an XGBoost classifier, NNLS deconvolution, and plotting utilities. Scales to large spatial and single-cell methylomes and is robust to extreme sparsity.

Hongxiang Fu

MethScope

Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent
Pattern Encoding

Wanding Zhou

The SAMtools/HTSlib authors 

Attractive Chaos

nnls_deconv function

<dl><dt>ref</dt>
<dd>An imputed wide cell by pattern matrix generated from GenerateInput function using reference Pseudobulk</dd>
<dt>mixture_matrix</dt>
<dd>An imputed wide cell by pattern matrix generated from GenerateInput function</dd>
<dt>number_patterns</dt>
<dd>a numeric value to indicate number of patterns to be used (Default: 1000)</dd>
<dt>var_threshold</dt>
<dd>a numeric value to indicate variance that should filter the patterns (Default: 0.1)</dd></dl>

Arguments

Estimate cell type relative proportion — nnls_deconv

<dl>

<dt>ref</dt>
<dd>An imputed wide cell by pattern matrix generated from GenerateInput function using reference Pseudobulk</dd>


<dt>mixture_matrix</dt>
<dd>An imputed wide cell by pattern matrix generated from GenerateInput function</dd>


<dt>number_patterns</dt>
<dd>a numeric value to indicate number of patterns to be used (Default: 1000)</dd>


<dt>var_threshold</dt>
<dd>a numeric value to indicate variance that should filter the patterns (Default: 0.1)</dd>

</dl>

nnls_deconv: Estimate cell type relative proportion

Description

Usage

Value

Arguments