queryATAC: A function to query scATAC-seq datasets available in this...

In shooshtarilab/scATAC.Explorer: A Collection of Single-cell ATAC Sequencing Datasets and Corresponding Metadata

A function to query scATAC-seq datasets available in this package

Description

This function allows you to search and subset included scATAC-seq datasets. A named list of scATAC-seq_data objects matching the provided options will be returned. Some included datasets are represented using multiple matrices. Each matrix will be a seperate named object within the list. The returned list is named by matrix allow easy identification of data. If queryATAC is called without any options it will retrieve all available datasets in sparse matrix format. This should only be done on machines with a large amount of ram (>64gb) because some datasets are quite large. In most cases it is recommended to instead filter databases with some criteria.

Usage

queryATAC(
  accession = NULL,
  author = NULL,
  journal = NULL,
  year = NULL,
  pmid = NULL,
  sequence_tech = NULL,
  score_type = NULL,
  has_cluster_annotation = NULL,
  has_cell_type_annotation = NULL,
  organism = NULL,
  genome_build = NULL,
  broad_cell_category = NULL,
  tissue_cell_type = NULL,
  disease = NULL,
  metadata_only = FALSE,
  sparse = TRUE
)

Arguments

accession	Search by geo accession number. Good for returning individual datasets
author	Search by the author who published the dataset
journal	Search by the journal the dataset was published in.
year	Search by exact year or year ranges with '<', '>', or '-'. For example, you can return datasets newer than 2013 with '>2013'
pmid	Search by Pubmed ID associated with the study. Good for returning individual datasets
sequence_tech	Search by sequencing technology used to sample the cells.
score_type	Search by type of score (TPM, FPKM, raw count)
has_cluster_annotation	Return only those datasets that have clustering results available, or only those without (TRUE/FALSE)
has_cell_type_annotation	Return only those datasets that have cell-type annotations available, or only those without annotations (TRUE/FALSE)
organism	Search by source organism used in the study, for example human or mouse.
genome_build	Return datasets built only using specified genome build (ex. hg19)
broad_cell_category	Return datasets based on broad cell categories (ex. Hematopoetic cells). To view all cell categories available, explore the metadata table
tissue_cell_type	Return datasets based on tissue or cell types sampled (ex. PBMCs, Bone marrow, Oligodendrocytes)
disease	Return datasets based on sampled disease (ex. carcinoma, leukemia, diabetes)
metadata_only	Return rows of metadata instead of actual datasets. Useful for exploring what data is available without actually downloading data. Defaults to FALSE
sparse	Return expression as a sparse matrix. Reccomended to use sparse format, as dense formats tend to be excessively large.

Value

A list containing a table of metadata or one or more SingleCellExperiment objects

Examples

## Retrieve the metadata table to see what data is available
res <- queryATAC(metadata_only = TRUE)

## Retrieve a single dataset based on its accession number
res <- queryATAC(accession = "GSE129785")

## Retrieve the metadata of datasets between 2016 and 2020
res = queryATAC(year = "2016-2020", metadata_only = TRUE)

## From the table of datasets between 2016 and 2020,
## retrieve the dataset on the third row.
res = queryATAC(year = "2016-2020")[[3]]

## Retrieve a filtered metadata table that only shows mouse
## datasets derived from blood cells with cell type annotations
res_mus <- queryATAC(has_cell_type_annotation = TRUE, 
                 organism = "Mus musculus",
                 tissue_cell_type = "blood",
                 metadata_only = TRUE)

shooshtarilab/scATAC.Explorer documentation built on Oct. 20, 2024, 8:20 p.m.