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Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets

View ORCID ProfileHaruka Ozaki, View ORCID ProfileTetsutaro Hayashi, View ORCID ProfileUmeda Mana, View ORCID ProfileItoshi Nikaido
doi: https://doi.org/10.1101/537936
Haruka Ozaki
Bioinformatics Laboratory, Faculty of Medicine, University of Tsukuba;
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  • For correspondence: harukao.cb@gmail.com
Tetsutaro Hayashi
Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research
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  • For correspondence: tetsutaro.hayashi@riken.jp
Umeda Mana
Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research
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  • For correspondence: mana.umeda@riken.jp
Itoshi Nikaido
Laboratory for Bioinformatics Research, RIKEN Center for Biosystems Dynamics Research
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  • For correspondence: itoshi.nikaido@riken.jp
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Abstract

Background: Read coverage of RNA sequencing data reflects gene expression and RNA processing events. Single-cell RNA sequencing (scRNA-seq) methods, particularly "full-length" ones, provide read coverage of many individual cells and have the potential to reveal cellular heterogeneity in RNA transcription and processing. However, visualization tools suited to highlighting cell-to-cell heterogeneity in read coverage are still lacking. Results: Here, we have developed Millefy, a tool for visualizing read coverage of scRNA-seq data in genomic contexts. Millefy is designed to show read coverage of all individual cells at once in genomic contexts and to highlight cell-to-cell heterogeneity in read coverage. By visualizing read coverage of all cells as a heat map and dynamically reordering cells based on diffusion maps, Millefy facilitates discovery of "local" region-specific, cell-to-cell heterogeneity in read coverage, including variability of transcribed regions. Conclusions: Millefy simplifies the examination of cellular heterogeneity in RNA transcription and processing events using scRNA-seq data. Millefy is available as an R package (https://github.com/yuifu/millefy) and a Docker image to help use Millefy on the Jupyter notebook (https://hub.docker.com/r/yuifu/datascience-notebook-millefy).

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  • Revised Figure 1.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
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Posted February 02, 2019.
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Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets
Haruka Ozaki, Tetsutaro Hayashi, Umeda Mana, Itoshi Nikaido
bioRxiv 537936; doi: https://doi.org/10.1101/537936
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Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets
Haruka Ozaki, Tetsutaro Hayashi, Umeda Mana, Itoshi Nikaido
bioRxiv 537936; doi: https://doi.org/10.1101/537936

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