PT  - JOURNAL ARTICLE
AU  - Haruka Ozaki
AU  - Tetsutaro Hayashi
AU  - Mana Umeda
AU  - Itoshi Nikaido
TI  - Millefy: visualizing cell-to-cell heterogeneity in read coverage of single-cell RNA sequencing datasets
AID  - 10.1101/537936
DP  - 2019 Jan 01
TA  - bioRxiv
PG  - 537936
4099  - http://biorxiv.org/content/early/2019/02/02/537936.short
4100  - http://biorxiv.org/content/early/2019/02/02/537936.full
AB  - 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).eRNAsenhancer RNAsmESCsmouse embryonic stem cellsPCAprincipal component analysisQCquality controlscRNA-seqsingle-cell RNA sequencing