This implements MCMC for Poisson matrix factorization (PMF) with independent Poisson-randomized gamma (PRG) priors.
This model is based on the one presented by Stein-O’Brien et al. (2019) [1] for factorizing gene-cell matrices of RNA sequence data. The code is specifically written for that application.
The MCMC algorithm is based on the one presented by Schein et al. (2019) [2] and the code is adapted from the open-source code for that paper.
[1] Stein-O’Brien, Genevieve L., et al. "Decomposing cell identity for transfer learning across cellular measurements, platforms, tissues, and species." Cell systems 8.5 (2019): 395-411. https://www.cell.com/cell-systems/pdfExtended/S2405-4712(19)30146-2
[2] Schein, Aaron, et al. "Poisson-Randomized Gamma Dynamical Systems." Advances in Neural Information Processing Systems. 2019. http://papers.nips.cc/paper/8366-poisson-randomized-gamma-dynamical-systems
MIT License
Copyright (c) 2020 Aaron Schein
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
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- apf.pyx: Allocation-based Poisson factorization (APF). This is the base class for Poisson tensor decomposition models with non-negative priors.
- bessel.pyx: Sampling algorithms for the Bessel distribution.
- sbch.pyx: Sampling algorithms for the size-biased confluent hypergeometric (SCH) distribution.
- prgpmf.pyx: Poisson matrix factorization (PMF) with Poisson-randomized gamma (PRG) priors.
OSX users will have to install a version of the GNU Compiler Collection (GCC). If using Anaconda,
conda install -c anaconda gcc
and then change the relevant line in setup.py. OSX users may run into issues compiling on MacOS 10.14 or greater which can be fixed by following the solutions in this thread.
OSX users will also have to install the GNU Scientific library (GSL). If using Anaconda,
conda install -c conda-forge gsl