adjust_Fg

A function that adjusts zero proportion values to meet the
requirements of beta regression by bounding values of 0 and 1
to 0.001 and 0.999.

A causal mediation framework for single-cell data that incorporates two key features ('MedZIsc', pronounced Magics): (1) zero-inflation using beta regression and (2) overdispersed expression counts using negative binomial regression. This approach also includes a screening step based on penalized and marginal models to handle high-dimensionality. Full methodological details are available in our recent preprint by Ahn S and Li Z (2025) <doi:10.48550/arXiv.2505.22986>.

Seungjun Ahn

MedZIsc

Statistical Framework for Co-Mediators of Zero-Inflated
Single-Cell Data

Zhigang Li

adjust_Fg function

<dl><dt>Fg</dt>
<dd>A numeric vector of length n, where each element represents the
proportion of zero counts for a given gene g across cells for subject i.</dd></dl>

Arguments

adjust_Fg — adjust_Fg

<dl>

<dt>Fg</dt>
<dd>A numeric vector of length n, where each element represents the
proportion of zero counts for a given gene g across cells for subject i.</dd>

</dl>

adjust_Fg: adjust_Fg

Description

Usage

Value

Arguments