Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST

Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST

Single-cell RNA-seq (scRNA-seq) is being widely used to resolve cellular heterogeneity. Here, the authors present a cell-querying method built on a neural network-based generative model and a customized cell-to-cell similarity metric.

Bibliographic Details
Main Authors: Zhi-Jie Cao, Lin Wei, Shen Lu, De-Chang Yang, Ge Gao
Format: Article
Language:English
Published: Nature Publishing Group 2020-07-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-020-17281-7
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spelling doaj-3e0cf5f83c044e5689b8ee6fcaa6bccd2021-07-11T11:44:12ZengNature Publishing GroupNature Communications2041-17232020-07-0111111310.1038/s41467-020-17281-7Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLASTZhi-Jie Cao0Lin Wei1Shen Lu2De-Chang Yang3Ge Gao4Biomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking UniversityBiomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking UniversityBiomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking UniversityBiomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking UniversityBiomedical Pioneering Innovation Center (BIOPIC), Beijing Advanced Innovation Center for Genomics (ICG), Center for Bioinformatics (CBI), and State Key Laboratory of Protein and Plant Gene Research at School of Life Sciences, Peking UniversitySingle-cell RNA-seq (scRNA-seq) is being widely used to resolve cellular heterogeneity. Here, the authors present a cell-querying method built on a neural network-based generative model and a customized cell-to-cell similarity metric.https://doi.org/10.1038/s41467-020-17281-7
collection DOAJ
language English
format Article
sources DOAJ
author Zhi-Jie Cao
Lin Wei
Shen Lu
De-Chang Yang
Ge Gao
spellingShingle Zhi-Jie Cao
Lin Wei
Shen Lu
De-Chang Yang
Ge Gao
Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST
Nature Communications
author_facet Zhi-Jie Cao
Lin Wei
Shen Lu
De-Chang Yang
Ge Gao
author_sort Zhi-Jie Cao
title Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST
title_short Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST
title_full Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST
title_fullStr Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST
title_full_unstemmed Searching large-scale scRNA-seq databases via unbiased cell embedding with Cell BLAST
title_sort searching large-scale scrna-seq databases via unbiased cell embedding with cell blast
publisher Nature Publishing Group
series Nature Communications
issn 2041-1723
publishDate 2020-07-01
description Single-cell RNA-seq (scRNA-seq) is being widely used to resolve cellular heterogeneity. Here, the authors present a cell-querying method built on a neural network-based generative model and a customized cell-to-cell similarity metric.
url https://doi.org/10.1038/s41467-020-17281-7
work_keys_str_mv AT zhijiecao searchinglargescalescrnaseqdatabasesviaunbiasedcellembeddingwithcellblast
AT linwei searchinglargescalescrnaseqdatabasesviaunbiasedcellembeddingwithcellblast
AT shenlu searchinglargescalescrnaseqdatabasesviaunbiasedcellembeddingwithcellblast
AT dechangyang searchinglargescalescrnaseqdatabasesviaunbiasedcellembeddingwithcellblast
AT gegao searchinglargescalescrnaseqdatabasesviaunbiasedcellembeddingwithcellblast
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