Type: Package
Title: Download and Merge Single-Cell RNA-Seq Data from the PanglaoDB Database
Version: 0.2.1
Description: Download and merge labeled single-cell RNA-seq data from the PanglaoDB https://panglaodb.se/ into a Seurat object.
URL: https://github.com/dosorio/rPanglaoDB/
License: GPL-3
Encoding: UTF-8
LazyData: false
RoxygenNote: 7.1.1
Imports: methods, XML, xml2, Seurat, pbapply, Matrix
NeedsCompilation: no
Packaged: 2021-05-12 19:51:08 UTC; danie
Author: Daniel Osorio ORCID iD [aut, cre], Marieke Kuijjer ORCID iD [aut], James J. Cai ORCID iD [aut]
Maintainer: Daniel Osorio <daniecos@uio.no>
Repository: CRAN
Date/Publication: 2021-05-12 22:00:02 UTC

Get the list of samples from the panglaoDB database with a pattern of expression for a set of molecular markers.

Description

Get the list of samples from the panglaoDB database with a pattern of expression for a set of molecular markers.

Usage

getMarkers(include, exclude = NULL)

Arguments

include

A set of molecular markers to query the database. This set of genes needs to be expressed in the sample.

exclude

A set of molecular markers to query the database. This set of genes needs to be absent in the sample.

Value

The rows in the data frame are the samples matching the requested pattern. The returned data frame contain 7 columns as follows:

Examples

## Not run: 
Fibrocytes <- getMarkers(include = c('ACTA2', 'CD34', 'FAP'))
Fibrocytes
## End(Not run)

#       SRA        SRS       Specie Tissue Cluster   Cell-Type         Markers
# SRA681285 SRS3121028 Mus musculus Dermis       4 Fibroblasts +ACTA2+CD34+FAP

Get the cell-type content for each sample from the panglaoDB database.

Description

Get the cell-type content for each sample from the panglaoDB database.

Usage

getSampleComposition(
  sra = "All",
  srs = "All",
  tissue = "All",
  protocol = "All",
  specie = "All",
  verbose = TRUE
)

Arguments

sra

Filter based on the SRA identifier of the biological sample in the SRA database

srs

Filter based on the SRS identifier of the biological sample in the SRA database

tissue

Filter based on the tissue from which the biological samples originates from

protocol

Filter based on the single-cell library preparation protocol used to generate the data

specie

Filter based on the specie from which the biological samples originates from

verbose

A boolean value TRUE or FALSE to activate the verbose mode

Value

This function returns the cell-type composition of the samples included in the PanglaoDB database in a data frame with 8 columns as follows:

Examples

# From PanglaoDB
# https://panglaodb.se/list_clusters_and_cell_types.html?sra=SRA689041&srs=SRS3166675

SRS3166675 <- getSampleComposition(srs = 'SRS3166675')
head(SRS3166675)

#       SRA        SRS Tissue     Protocol      Species Cluster Cells           Cell Type
# SRA689041 SRS3166675  Colon 10x chromium Mus musculus       0   735         Fibroblasts
# SRA689041 SRS3166675  Colon 10x chromium Mus musculus       1   526 Smooth muscle cells
# SRA689041 SRS3166675  Colon 10x chromium Mus musculus       2   465             Unknown
# SRA689041 SRS3166675  Colon 10x chromium Mus musculus       3   157             Unknown
# SRA689041 SRS3166675  Colon 10x chromium Mus musculus       4   140        Goblet cells
# SRA689041 SRS3166675  Colon 10x chromium Mus musculus       5   100         Fibroblasts

Get the sample list from the panglaoDB database.

Description

Get the sample list from the panglaoDB database.

Usage

getSampleList()

Value

This function returns a data frame with 6 columns as follows:

Examples

# From the PanglaoDB database
# https://panglaodb.se/samples.html

sampleList <- getSampleList()
head(sampleList)

#       SRA        SRS                          Tissue     Protocol      Species Cells
# SRA553822 SRS2119548   Cultured embryonic stem cells 10x chromium Homo sapiens  6501
# SRA570744 SRS2253536                 Lung mesenchyme 10x chromium Mus musculus  4611
# SRA598936 SRS2428405                   Kidney cortex 10x chromium Homo sapiens  3759
# SRA644036 SRS2808714 Cervical and lumbar spinal cord 10x chromium Mus musculus  1025
# SRA670243 SRS3078084                Ventral midbrain 10x chromium Mus musculus  5603
# SRA689041 SRS3166675                           Colon 10x chromium Mus musculus  2878

Download the expression matrix and annotations from the panglaoDB database.

Description

Download the expression matrix and annotations from the panglaoDB database.

Usage

getSamples(
  sra = "All",
  srs = "All",
  tissue = "All",
  protocol = "All",
  specie = "All",
  celltype = "All",
  include = NA,
  exclude = NA,
  merge = TRUE
)

Arguments

sra

Filter based on the SRA identifier of the biological sample in the SRA database

srs

Filter based on the SRS identifier of the biological sample in the SRA database

tissue

Filter based on the tissue from which the biological samples originates from

protocol

Filter based on the single-cell library preparation protocol used to generate the data

specie

Filter based on the specie from which the biological samples originates from

celltype

Filter based on the cell-type from which the counts originates from

include

A set of molecular markers to filter the dataset. This set of genes needs to be expressed in each cell.

exclude

A set of molecular markers to filter the dataset. This set of genes needs to be absent in each cell.

merge

A boolean value TRUE or FALSE defining if the samples should be returned as a list or as a unique Seurat object

Value

A Seurat object, as described in ?SeuratObject::`Seurat-class`

Examples

# From PanglaoDB SRS3805255
# https://panglaodb.se/view_data.php?sra=SRA705190&srs=SRS4139632

## Not run: 
SRS4139632 <- getSamples(srs = 'SRS4139632')
SRS4139632
## End(Not run)

# An object of class Seurat
# 19859 features across 102 samples within 1 assay
# Active assay: RNA (19859 features, 0 variable features)

# Metadata from the PanglaoDB database can be accessed as follows:
# head(SRS4139632[[]])