ddiR

An R package to obtain data from the Omics Discovery Index (OmicsDI. It uses its RESTful Web Services at OmicsDI WS for that purpose.

Currently, the following domain entities are supported:

• Dataset as S4 objects, including methods to get them from OmicsDI by accession and as.data.frame
• Publication as S4 objects, including methods to get them from OmicsDI by accession and as.data.frame
• Term as S4 objects, including methods to get them from OmicsDI by term and as.data.frame

Installation

First, we need to install devtools:

install.packages("devtools")
library(devtools)

Then we just call

install_github("enriquea/ddiR")
library(ddiR)

Examples

• This example retrives all dataset details given accession and database identifier

library(ddiR)

dataset = get.DatasetDetail(accession="PXD000210", database="pride")

# print dataset full name
get.dataset.name(dataset)

# print dataset omics type
get.dataset.omics(dataset)

• Access to all datasets for NOTCH1 gene

datasets <- search.DatasetsSummary(query = "NOTCH1")

sink("outfile.txt")
for(datasetCount in seq(from = 0, to = datasets@count, by = 100)){

    datasets <- search.DatasetsSummary(query = "NOTCH1", start = datasetCount, size = 100)

    for(dataset in datasets@datasets){
             dataset = get.DatasetDetail(accession=dataset.id(dataset), database=database(dataset))
             print(paste(dataset.id(dataset), get.dataset.omics(dataset), get.dataset.link(dataset)))
            }
    }
}
sink()

• Getting the dataset IDs and full link of 20 Genomics studies in Cancer

datasets <- search.DatasetsSummary(query = "Cancer AND Genomics")

for(dataset in datasets@datasets){
    dataset = get.DatasetDetail(accession=dataset.id(dataset), database=database(dataset))
    print(paste(dataset.id(dataset), get.dataset.link(dataset), sep = ' '))
}

• Print the dataset IDs and short description of 20 Proteomics studies for tumor supressor p53

datasets <- search.DatasetsSummary(query = "p53 AND Proteomics")

for(dataset in datasets@datasets){
    dataset = get.DatasetDetail(accession=dataset.id(dataset), database=database(dataset))
    print(paste(dataset.id(dataset), get.dataset.name(dataset), sep = ' '))
}

• Getting Proteomics studies in Heart tissue from PRIDE database

datasets <- search.DatasetsSummary(query = "Heart")

for(dataset in datasets@datasets){
    dataset = get.DatasetDetail(accession=dataset.id(dataset), database=database(dataset))
    if(database(dataset)=='pride')
    print(paste(dataset.id(dataset), get.dataset.tissues(dataset), get.dataset.omics(dataset), sep = ' '))
}

• This exmaple shows how retrieve all the metadata similarity scores by using the R-package ddiR.

datasets <- search.DatasetsSummary(query = "*:*")
i  = 0
sink("outfile.txt")
for(datasetCount in seq(from = 0, to = datasets@count, by = 100)){

    datasets <- search.DatasetsSummary(query = "*:*", start = datasetCount, size = 100)

    for(dataset in datasets@datasets){
            Similar = get.MetadataSimilars(accession = dataset@dataset.id, database = dataset@database)
            rank = 0
            for(similarDataset in Similar@datasets){
                print(paste(dataset@dataset.id, similarDataset@dataset.id, similarDataset@score, dataset@omics.type, rank))
                rank = rank + 1
            }
    }
}
sink()

Maintainers

Yasset Perez-Riverol
Ariana Barbera Betancourt
Enrique Audain