Skip to main content

Probabilistic factor analysis model with covariate guided factors

Project description

spFA

Introduction

Here we present semi-supervised probabilistic Factor Analysis (SOFA), a multi-omics integration method, which infers a set of low dimensional latent factors that represent the main sources of variability. SOFA enables the discovery of primary sources of variation while adjusting for known covariates and simultaneously disentangling variation that is shared between multiple omics modalities and specific to single modalities. The spFA method is implemented in python using the pyro framework for probabilistic programming.

Installation

To install sofa first create Python 3.8 environment e.g. by

conda create --name sofa-env python=3.8
conda activate sofa-env

and install the package using

pip install sofa

How to use sofa for multi-omics analyses

A detailed manual with examples and how to use sofa can be found here https://tcapraz.github.io/sofa/index.html.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page