Single-Cell Data Science
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Updated
Nov 30, 2020 - Python
Single-Cell Data Science
Pytorch implementation of "Multi-domain translation between single-cell imaging and sequencing data using autoencoders" (https://www.nature.com/articles/s41467-020-20249-2) with custom models.
As part of the IEE Healthcare Summit Data Hackathon(2022) Challenge designed a classification model to predict severity of COVID-19 infection from scRNA-seq data.
An unofficial demultiplexing strategy for SPLiT-seq RNA-Seq data
Cell cluster Analysis with Variational Autoencoder using Conditional Hierarchy Of latent representioN
Custom codes for Flysta3D paper.
Factorial latent dynamic models trained on Markovian simulations of biological processes using single cell RNA sequencing data.
One single-cell pipeline to rule them all, one pipeline to find them, one pipeline to unify them all, and with the data bind them.
Biology-driven deep generative model for cell-type annotation in cytometry. Scyan is an interpretable model that also corrects batch-effect and can be used for debarcoding or population discovery.
A command-line tool and library to process and analyze sequencing data from Molecular Pixelation (MPX) assays.
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