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scClassify: sample size estimation and multiscale classification of cells using single and multiple...

scClassify: sample size estimation and multiscale classification of cells using single and multiple...

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_71435eb9e5d94b0db1e8fa3e180304ab

scClassify: sample size estimation and multiscale classification of cells using single and multiple reference

About this item

Full title

scClassify: sample size estimation and multiscale classification of cells using single and multiple reference

Publisher

London: Nature Publishing Group UK

Journal title

Molecular systems biology, 2020-06, Vol.16 (6), p.e9389-n/a

Language

English

Formats

Publication information

Publisher

London: Nature Publishing Group UK

More information

Scope and Contents

Contents

Automated cell type identification is a key computational challenge in single‐cell RNA‐sequencing (scRNA‐seq) data. To capitalise on the large collection of well‐annotated scRNA‐seq datasets, we developed scClassify, a multiscale classification framework based on ensemble learning and cell type hierarchies constructed from single or multiple annota...

Alternative Titles

Full title

scClassify: sample size estimation and multiscale classification of cells using single and multiple reference

Identifiers

Primary Identifiers

Record Identifier

TN_cdi_doaj_primary_oai_doaj_org_article_71435eb9e5d94b0db1e8fa3e180304ab

Permalink

https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_71435eb9e5d94b0db1e8fa3e180304ab

Other Identifiers

ISSN

1744-4292

E-ISSN

1744-4292

DOI

10.15252/msb.20199389

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