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A robust statistical framework to detect multiple sources of hidden variation in single-cell transcriptomes

Donghyung Lee, Anthony Cheng, Duygu Ucar
doi: https://doi.org/10.1101/151217
Donghyung Lee
1 The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, Unites States of America,
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  • For correspondence: donghyung.lee@jax.org duygu.ucar@jax.org
Anthony Cheng
1 The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, Unites States of America,
2 University of Connecticut Health Center, Farmington, Connecticut, Unites States of America
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Duygu Ucar
1 The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, Unites States of America,
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  • For correspondence: donghyung.lee@jax.org duygu.ucar@jax.org
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Posted June 18, 2017.
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A robust statistical framework to detect multiple sources of hidden variation in single-cell transcriptomes
Donghyung Lee, Anthony Cheng, Duygu Ucar
bioRxiv 151217; doi: https://doi.org/10.1101/151217
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A robust statistical framework to detect multiple sources of hidden variation in single-cell transcriptomes
Donghyung Lee, Anthony Cheng, Duygu Ucar
bioRxiv 151217; doi: https://doi.org/10.1101/151217

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