if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("SingleCellMultiModal")
library(SingleCellMultiModal) library(MultiAssayExperiment)
The dataset was graciously provided by @Argelaguet2019-et.
Scripts used to process the raw data were written and maintained by Argelaguet and colleagues and reside on GitHub: https://github.com/rargelaguet/scnmt_gastrulation
For more information on the protocol, see @Clark2018-qg.
The user can see the available datasets by using the dry.run
argument:
scNMT("mouse_gastrulation", mode = "*", version = "1.0.0", dry.run = TRUE)
Or by simply running the scNMT
function with defaults:
scNMT("mouse_gastrulation", version = "1.0.0")
A more recent release of the 'mouse_gastrulation' dataset was provided
by Argelaguet and colleagues. This dataset includes additional cells that
did not pass the original quality metrics as imposed for the version 1.0.0
dataset.
Use the version
argument to indicate the newer dataset version
(i.e., 2.0.0
):
scNMT("mouse_gastrulation", version = '2.0.0', dry.run = TRUE)
To obtain the data, we can use the mode
argument to indicate specific
datasets using 'glob' patterns that will match the outputs above. For example,
if we would like to have all 'genebody' datasets for all available assays,
we would use *_genebody
as an input to mode
.
nmt <- scNMT("mouse_gastrulation", mode = c("*_DHS", "*_cgi", "*_genebody"), version = "1.0.0", dry.run = FALSE) nmt
Included in the colData
DataFrame
within the MultiAssayExperiment
class
are the variables cellID
, stage
, lineage10x_2
, and stage_lineage
.
To extract this DataFrame
, one has to use colData
on the
MultiAssayExperiment
object:
colData(nmt)
Check row annotations:
rownames(nmt)
The sampleMap
is a graph representation of the relationships between cells
and 'assay' datasets:
sampleMap(nmt)
Take a look at the cell identifiers or barcodes across assays:
colnames(nmt)
See the accessibilty levels (as proportions) for DNase Hypersensitive Sites:
head(assay(nmt, "acc_DHS"))[, 1:4]
See the methylation percentage / proportion:
head(assay(nmt, "met_DHS"))[, 1:4]
For protocol information, see the references below.
sessionInfo()
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