add SISUA

Author: seandavi

README.md

@@ -126,6 +126,7 @@ List of software packages (and the people developing these methods) for single-c
 - [SingleSplice](https://github.com/jw156605/SingleSplice) - [R, perl, C++] - A tool for detecting biological variation in alternative splicing within a population of single cells. See [Welch et al. 2016](https://academic.oup.com/nar/article/44/8/e73/2465993/Robust-detection-of-alternative-splicing-in-a).
 - [singlet](https://github.com/iosonofabio/singlet) - [Python] - Single cell RNA-Seq analysis with phenotypes.
 - [SinQC](http://www.morgridge.net/SinQC.html) - [R] - A Method and Tool to Control Single-cell RNA-seq Data Quality.
+- [SISUA](https://github.com/trungnt13/sisua) - [python] - In this study, we propose models based on the Bayesian generative approach, where protein quantification available as CITE-seq counts from the same cells are used to constrain the learning process, thus forming a semi-supervised model. The generative model is based on the deep variational autoencoder (VAE) neural network architecture. [bioRxiv](https://www.biorxiv.org/content/10.1101/631382v1)
 - [SLICER](https://github.com/jw156605/SLICER) - [R] - Selective Locally linear Inference of Cellular Expression Relationships (SLICER) algorithm for inferring cell trajectories.
 - [slingshot](https://github.com/kstreet13/slingshot) - [R] - Functions for identifying and characterizing continuous developmental trajectories in single-cell sequencing data.
 - [soupX](https://github.com/constantAmateur/SoupX) - [R] - An R package for the estimation and removal of cell free mRNA contamination in droplet based single cell RNA-seq data. The problem this package attempts to solve is that all droplet based single cell RNA-seq experiments also capture ambient mRNAs present in the input solution along with cell specific mRNAs of interest.