Examples#

A series of four example notebooks demonstrating the use of modality are available as a JupyterBook:

Exploratory analysis: shows how you can use modality to perform series of informative exploratory analyses of your data.
Working with genomic ranges: illustrates how you can use modality to work with genomic range data (for instance a list of CpG islands or exons), and how useful information can be extracted and plotted from these ranges, such as the mean methylation across the range.
Plotting methylation traces: shows how to use modality to plot methylation traces for a given genomic region.
Calling differentially methylated regions: shows how to call regions that are differentially methylated across a cohort (DMRs).

A python script to annotate DMRs and to produce a volcano plot.

modality deep dives#

Predicting gene expression

Part 1: Feature Generation: shows how to use modality to extract features for machine learning tasks.
Part 2: Training and Evaluating the Model: shows how to use a set of extracted features and train XGBoost models to predict gene expression.

Predicting chromatin accessibility

Part 1: Feature Generation: shows how to use modality to extract features for machine learning tasks.
Part 2: Training and Evaluating the Model: shows how to use a set of extracted features and train XGBoost models to predict chromatin accessibility.