Single-cell Nucleosome, Methylation and Transcription sequencing

scNMT assembles data on-the-fly from ExperimentHub to provide a MultiAssayExperiment container. The DataType argument provides access to the mouse_gastrulation dataset as obtained from Argelaguet et al. (2019; DOI: 10.1038/s41586-019-1825-8). Pre-processing code can be seen at https://github.com/rargelaguet/scnmt_gastrulation. Protocol information for this dataset is available at Clark et al. (2018). See the vignette for the full citation.

Usage

scNMT(
  DataType = "mouse_gastrulation",
  modes = "*",
  version = "1.0.0",
  dry.run = TRUE,
  verbose = TRUE,
  ...
)

Source

http://ftp.ebi.ac.uk/pub/databases/scnmt_gastrulation/

Arguments

DataType: character(1) Indicates study that produces this type of data (default: 'mouse_gastrulation')
modes: character() A wildcard / glob pattern of modes, such as "acc*". A wildcard of "*" will return all modes including Chromatin Accessibilty ("acc"), Methylation ("met"), RNA-seq ("rna") which is the default.
version: character(1) Either version '1.0.0' or '2.0.0' depending on data version required (default '1.0.0'). See version section.
dry.run: logical(1) Whether to return the dataset names before actual download (default TRUE)
verbose: logical(1) Whether to show the dataset currently being (down)loaded (default TRUE)
...: Additional arguments passed on to the ExperimentHub-class constructor

Value

A single cell multi-modal MultiAssayExperiment or informative data.frame when dry.run is TRUE

Details

scNMT is a combination of RNA-seq (transcriptome) and an adaptation of Nucleosome Occupancy and Methylation sequencing (NOMe-seq, the methylome and chromatin accessibility) technologies. For more information, see Reik et al. (2018) DOI: 10.1038/s41467-018-03149-4

mouse_gastrulation - this dataset provides cell quality control filters in the object colData starting from version 2.0.0. Additionally, cell types annotations are provided through the lineage colData column.
- rna - RNA-seq
- acc_\* - chromatin accessibility
- met_\* - DNA methylation
  - cgi - CpG islands
  - CTCF - footprints of CTCF binding
  - DHS - DNase Hypersensitive Sites
  - genebody - gene bodies
  - p300 - p300 binding sites
  - promoter - gene promoters

Special thanks to Al J Abadi for preparing the published data in time for the 2020 BIRS Workshop, see the link here: https://github.com/BIRSBiointegration/Hackathon/tree/master/scNMT-seq

versions

Version '1.0.0' of the scNMT mouse_gastrulation dataset includes all of the above mentioned assay technologies with filtering of cells based on quality control metrics. Version '2.0.0' contains all of the cells without the QC filter and does not contain CTCF binding footprints or p300 binding sites.

metadata

The MultiAssayExperiment metadata includes the original function call that saves the function call and the data version requested.

References

Argelaguet et al. (2019)

Examples


scNMT(DataType = "mouse_gastrulation", modes = "*",
    version = "1.0.0", dry.run = TRUE)
#>     ah_id         mode file_size rdataclass rdatadateadded rdatadateremoved
#> 1  EH3738      acc_cgi      7 Mb     matrix     2020-09-03             <NA>
#> 2  EH3739     acc_CTCF    1.2 Mb     matrix     2020-09-03             <NA>
#> 3  EH3740      acc_DHS    0.3 Mb     matrix     2020-09-03             <NA>
#> 4  EH3741 acc_genebody   49.6 Mb     matrix     2020-09-03             <NA>
#> 5  EH3742     acc_p300    0.2 Mb     matrix     2020-09-03             <NA>
#> 6  EH3743 acc_promoter   27.2 Mb     matrix     2020-09-03             <NA>
#> 7  EH3745      met_cgi    4.6 Mb     matrix     2020-09-03             <NA>
#> 8  EH3746     met_CTCF    0.1 Mb     matrix     2020-09-03             <NA>
#> 9  EH3747      met_DHS    0.1 Mb     matrix     2020-09-03             <NA>
#> 10 EH3748 met_genebody   26.8 Mb     matrix     2020-09-03             <NA>
#> 11 EH3749     met_p300    0.1 Mb     matrix     2020-09-03             <NA>
#> 12 EH3750 met_promoter   11.5 Mb     matrix     2020-09-03             <NA>
#> 13 EH3751          rna   18.6 Mb     matrix     2020-09-03             <NA>