ICpG-Pos: an accurate computational approach for identification of CpG sites using positional features on single-cell whole genome sequence data.

ABSTRACT:

Motivation

The investigation of DNA methylation can shed light on the processes underlying human well-being and help determine overall human health. However, insufficient coverage makes it challenging to implement single-stranded DNA methylation sequencing technologies, highlighting the need for an efficient prediction model. Models are required to create an understanding of the underlying biological systems and to project single-cell (methylated) data accurately.

Results

In this study, we developed positional features for predicting CpG sites. Positional characteristics of the sequence are derived using data from CpG regions and the separation between nearby CpG sites. Multiple optimized classifiers and different ensemble learning approaches are evaluated. The OPTUNA framew

SUBMITTER: Park S 

PROVIDER: S-EPMC10444964 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature