--- title: "scNMT Mouse Gastrulation" date: "`r BiocStyle::doc_date()`" vignette: | %\VignetteIndexEntry{scNMT Mouse Gastrulation} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} output: BiocStyle::html_document: toc_float: true Package: SingleCellMultiModal bibliography: ../inst/REFERENCES.bib --- # Installation ```{r,eval=FALSE} if (!requireNamespace("BiocManager", quietly = TRUE)) install.packages("BiocManager") BiocManager::install("SingleCellMultiModal") ``` ## Load packages ```{r,include=TRUE,results="hide",message=FALSE,warning=FALSE} library(SingleCellMultiModal) library(MultiAssayExperiment) ``` # scNMT: single-cell nucleosome, methylation and transcription sequencing 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. ## Dataset lookup The user can see the available datasets by using the `dry.run` argument: ```{r} scNMT("mouse_gastrulation", mode = "*", version = "1.0.0", dry.run = TRUE) ``` Or by simply running the `scNMT` function with defaults: ```{r} scNMT("mouse_gastrulation", version = "1.0.0") ``` ## Data versions 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`): ```{r} scNMT("mouse_gastrulation", version = '2.0.0', dry.run = TRUE) ``` ## Downloading the data 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`. ```{r,message=FALSE} nmt <- scNMT("mouse_gastrulation", mode = c("*_DHS", "*_cgi", "*_genebody"), version = "1.0.0", dry.run = FALSE) nmt ``` ## Checking the cell metadata 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: ```{r} colData(nmt) ``` ## Exploring the data structure Check row annotations: ```{r} rownames(nmt) ``` The `sampleMap` is a graph representation of the relationships between cells and 'assay' datasets: ```{r} sampleMap(nmt) ``` Take a look at the cell identifiers or barcodes across assays: ```{r} colnames(nmt) ``` ## Chromatin Accessibility (acc_*) See the accessibilty levels (as proportions) for DNase Hypersensitive Sites: ```{r} head(assay(nmt, "acc_DHS"))[, 1:4] ``` ## DNA Methylation (met_*) See the methylation percentage / proportion: ```{r} head(assay(nmt, "met_DHS"))[, 1:4] ``` For protocol information, see the references below. # sessionInfo ```{r} sessionInfo() ``` # References