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bioRxiv · 10.1101/2021.11.08.467820

scDeepHash: An automatic cell type annotation and cell retrieval method for large-scale scRNA-seq datasets using neural network-based hashing

Ma, S.·Zhang, Y.·Wang, B.·Hu, Z.·Zhang, J.
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Abstract

Single-cell RNA-sequencing technologies measure transcriptomic expressions, which quantifies cell-to-cell heterogeneity at an unprecedented resolution. As these technologies become more readily available, the number of scRNA-seq datasets increases drastically. Prior works have demonstrated that bias-free, holistic single-cell profiling infrastructures are essential to the emerging automatic cell-type annotation methods. We propose scDeepHash, a scalable scRNA-seq analytic tool that employs content-based deep hashing to index single-cell gene expressions. scDeepHash allows for fast and accurate automated cell-type annotation and similar-cell retrieval. We also demonstrate the performance of scDeepHash by benchmarking it against current state-of-the-art methods across multiple public scRNA-seq datasets.

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Ma, S., Zhang, Y., Wang, B., Hu, Z., Zhang, J.. 2021-11-10. scDeepHash: An automatic cell type annotation and cell retrieval method for large-scale scRNA-seq datasets using neural network-based hashing. https://doi.org/10.1101/2021.11.08.467820

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