PlotConfusion

Generate confusion table for the final prediction

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

PlotConfusion function

<dl><dt>prediction_result</dt>
<dd>Prediction result from PredictCellType</dd>
<dt>actual_label</dt>
<dd>Ground truth cell label</dd>
<dt>log2</dt>
<dd>Log scale count (Default: False)</dd></dl>

Arguments

Generate confusion table for the final prediction — PlotConfusion

<dl>

<dt>prediction_result</dt>
<dd>Prediction result from PredictCellType</dd>


<dt>actual_label</dt>
<dd>Ground truth cell label</dd>


<dt>log2</dt>
<dd>Log scale count (Default: False)</dd>

</dl>

PlotConfusion: Generate confusion table for the final prediction

Description

Usage

Value

Arguments