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Status |
Public on Jul 19, 2021 |
Title |
MultiK: An Automated Tool to Infer Optimal Cluster Numbers in Single-Cell RNA Sequencing Data |
Organism |
Mus musculus |
Experiment type |
Expression profiling by high throughput sequencing
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Summary |
This paper proposes MultiK, a data-driven tool for objective selection of multiple insightful numbers of clusters (K) from single-cell RNA-seq data.
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Overall design |
MultiK combines multiple clustering resolution solutions together through a consensus approach, and is capable of identifying robust and reproducible groups across multiple datasets.
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Contributor(s) |
Perou CM, Thennavan A |
Citation(s) |
34412669 |
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Submission date |
Jan 22, 2021 |
Last update date |
Aug 31, 2021 |
Contact name |
Charles M. Perou |
E-mail(s) |
cperou@med.unc.edu
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Organization name |
University of North Carolina at Chapel Hill
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Department |
Professor of Genetics, and Pathology & Laboratory Medicine; Lineberger Comprehensive Cancer Center
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Street address |
12-044 Lineberger Comprehensive Cancer Center CB# 7295
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City |
Chapel Hill |
State/province |
NC |
ZIP/Postal code |
27599-7264 |
Country |
USA |
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Platforms (1) |
GPL19057 |
Illumina NextSeq 500 (Mus musculus) |
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Samples (1) |
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Relations |
BioProject |
PRJNA694120 |
SRA |
SRP302889 |