finalModelObject

Trained MOCHA models - LOESS and linear regression

datasets

A statistical framework and analysis tool for open chromatin
analysis designed specifically for single cell ATAC-seq (Assay for
Transposase-Accessible Chromatin) data, after cell type/cluster
identification. These novel modules remove unwanted technical variation,
identify open chromatin, robustly models repeated measures in single cell
data, implement advanced statistical frameworks to model zero-inflation for
differential and co-accessibility analyses, and integrate with existing
databases and modules for downstream analyses to reveal biological insights.
MOCHA provides a statistical foundation for complex downstream analysis to
help advance the potential of single cell ATAC-seq for applied studies.
Methods for zero-inflated statistics are as described in:
Ghazanfar, S., Lin, Y., Su, X. et al. (2020) <doi:10.1038/s41592-020-0885-x>.
Pimentel, Ronald Silva, "Kendall's Tau and Spearman's Rho for Zero-Inflated
Data" (2009) <https://scholarworks.wmich.edu/dissertations/721/>.

Imran McGrath

MOCHA

Modeling for Single-Cell Open Chromatin Analysis

Samir Rachid Zaim

Mark-Phillip Pebworth

Lauren Okada

Xiaojun Li

finalModelObject function

A list of lists containing 2 items: "Loess" and "Linear" each with "Total" "Max" and "Intercept"<dl>
<dt>Loess</dt>
<dd>LOESS model</dd><dt>Linear</dt>
<dd>Linear model</dd>
</dl>

Format

finalModelObject — finalModelObject

A list of lists containing 2 items: "Loess" and "Linear" each with "Total" "Max" and "Intercept"<dl>
<dt>Loess</dt>
<dd>LOESS model</dd>

<dt>Linear</dt>
<dd>Linear model</dd>


</dl>

finalModelObject: finalModelObject

Description

Usage

Arguments

Format