DeepImpute: an accurate, fast, and scalable deep neural network method to impute single-cell RNA-seq data

Publishing date: 2019-11-14

Published on: Genome Biology

summary: Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression of tens of thousands of single cells simultaneously. The authors present DeepImpute, a deep neural network-based imputation algorithm that uses dropout layers and loss functions to learn patterns in the data, allowing for accurate imputation. DeepImpute is an accurate, fast, and scalable imputation tool that is suited to handle the ever-increasing volume of scRNA-seq data.

authors: Cédric Arisdakessian, Olivier Poirion, Breck Yunits, Xun Zhu & Lana X. Garmire

link to paper: https://doi.org/10.1186/s13059-019-1837-6

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