sourceDataFrame: SPATAData source data.frame
In theMILOlab/SPATAData: The MILOLab Spatial Transriptomic Database

sourceDataFrame

R Documentation

SPATAData source data.frame

Description

Access the source data.frame which contains information about various spatial transcriptomic experiments. Use ... to subset according to dplyr::filter().

Usage

sourceDataFrame(..., .rm_na_cols = NULL)

Arguments

`...`	<`data-masking`> Expressions that return a logical value, and are defined in terms of the variables in `.data`. If multiple expressions are included, they are combined with the `&` operator. Only rows for which all conditions evaluate to `TRUE` are kept.
`.rm_na_cols`	Logical value. Decides whether columns of the output data.frame that contain only missing values are removed. Defaults to `TRUE` if `...` contains any subset instructions. Else, defaults to `FALSE`. Specifying the input forces the respective behaviour.

Value

Data.frame in which each row corresponds to a spatial data set stored in a SPATA2 object. The following meta variables provide additional information.

sample_name: Character. Name of the sample and its unique identifier.
comment: Character. Additional comments about the sample.
donor_id: Character. Unique identifier for the donor.
donor_species: Character. Species of the donor.
grade: Character. Grade of the sample in case of histologically classified malignancies.
grade_sub: Character. Sub-grade of the sample.
histo_class: Character. Histological classification.
histo_class_sub: Character. Sub-classification of the histological class.
institution: Character. Institution where the sample was collected.
organ: Character. Organ from which the sample was taken.
organ_part: Character. Specific part of the organ from which the sample was taken.
pathology: Character. Pathological state of the sample.
platform: Character. Platform used for the experiment.
pub_citation: Character. Citation for the publication related to the sample.
pub_doi: Character. DOI of the publication related to the sample.
pub_journal: Character. Journal where the related publication was published.
pub_year: Numeric. Year of publication.
sex: Character. Sex of the donor. Either female or male.
side: Character. Side of the organ from which the sample was taken.
tags: Character. Tags related to the sample.
tissue_age: Numeric. Age of the tissue in years.
workgroup: Character. Workgroup or team responsible for the sample.

Furthermore, there are quality control and file-specific meta variables:

lm_source: Date-time. Last instance when the corresponding SPATA2 object was modified.
mean_counts: Numeric. Mean counts of the measurements.
median_counts: Numeric. Median counts of the measurements.
modality_gene: Logical. Indicates if the modality includes genes.
modality_metabolite: Logical. Indicates if the modality includes metabolites.
modality_protein: Logical. Indicates if the modality includes proteins.
n_obs: Numeric. Number of observations.
n_tissue_sections: Numeric. Number of tissue sections as identified by identifyTissueOutline() with default parameters.
obj_size: Storage size of the object.
obs_unit: Character. Unit of observation.
web_link: Character. Weblinkg with which to download the SPATA2 object.

Examples


library(SPATA2)
library(SPATAData)
library(dplyr)
library(stringr)

sdf <- sourceDataFrame()

#----- example dplyr logic to filter the source data.frame

# 1. obtain glioblastoma samples from the temporal lobe

temporal_gbms <- sourceDataFrame(histo_class == "Glioblastoma" & organ_part == "temporal")

# show results
temporal_gbms

# get sample names
temporal_gbms$sample_names

# downlaod as collection
downloadSpataObjects(sample_names = gbm_samples, folder = "spata_objects/gbm") 

# 2. obtain data from specific publications

sdf_kuppe <- 
 sourceDataFrame(str_detect(pub_citation, pattern = "^Kuppe"))
 
kuppe_samples <- sdf_kuppe$sample_name

print(kuppe_samples)

theMILOlab/SPATAData documentation built on Aug. 27, 2024, 5:04 p.m.