Skip to main content

Probabilistic factor analysis model with covariate guided factors

Project description

Semi-supervised Omics Factor Analysis (SOFA)

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 SOFA 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 biosofa

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

biosofa-0.3.0.tar.gz (15.5 kB view details)

Uploaded Source

Built Distribution

biosofa-0.3.0-py3-none-any.whl (15.9 kB view details)

Uploaded Python 3

File details

Details for the file biosofa-0.3.0.tar.gz.

File metadata

  • Download URL: biosofa-0.3.0.tar.gz
  • Upload date:
  • Size: 15.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.8.10 Linux/5.15.0-119-generic

File hashes

Hashes for biosofa-0.3.0.tar.gz
Algorithm Hash digest
SHA256 e41e05f5d518e5caa84205f0ab556a8b6f1c19646d661dafa909b3ef161858dd
MD5 192c96e97e1f89141fa0b71e8d5120fa
BLAKE2b-256 a2256c6ca705f9534e1daab0157dc1a68fcec89a68753e1b43aa25bc8771d5ce

See more details on using hashes here.

File details

Details for the file biosofa-0.3.0-py3-none-any.whl.

File metadata

  • Download URL: biosofa-0.3.0-py3-none-any.whl
  • Upload date:
  • Size: 15.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.8.10 Linux/5.15.0-119-generic

File hashes

Hashes for biosofa-0.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 ecdfbf53d954ea7d2997216a6c451d0cbe928ae040d65971cd7b8e18643d012d
MD5 e7a848e4ea646cdca8d6e4b609df2554
BLAKE2b-256 5aa4a7dc4de3ccb5788cb9062ade4e03eba739c16fab1de33998dba5f946513b

See more details on using hashes here.

Supported by

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