README.md

In lgatto/ProteomicsAnnotationHubData: Transform public proteomics data resources into Bioconductor Data Structures

AnnotationHub for proteomics

The aim of this package is to offer access to mass spectrometry and proteomics data throught the AnnotationHub infrastructure.

library("AnnotationHub")
#> Loading required package: BiocGenerics
#> Loading required package: methods
#> Loading required package: parallel
#> 
#> Attaching package: 'BiocGenerics'
#> 
#> The following objects are masked from 'package:parallel':
#> 
#>     clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
#>     clusterExport, clusterMap, parApply, parCapply, parLapply,
#>     parLapplyLB, parRapply, parSapply, parSapplyLB
#> 
#> The following objects are masked from 'package:stats':
#> 
#>     IQR, mad, xtabs
#> 
#> The following objects are masked from 'package:base':
#> 
#>     anyDuplicated, append, as.data.frame, as.vector, cbind,
#>     colnames, do.call, duplicated, eval, evalq, Filter, Find, get,
#>     grep, grepl, intersect, is.unsorted, lapply, lengths, Map,
#>     mapply, match, mget, order, paste, pmax, pmax.int, pmin,
#>     pmin.int, Position, rank, rbind, Reduce, rownames, sapply,
#>     setdiff, sort, table, tapply, union, unique, unlist, unsplit
ah <- AnnotationHub()
#> snapshotDate(): 2015-11-19
ah
#> AnnotationHub with 35372 records
#> # snapshotDate(): 2015-11-19 
#> # $dataprovider: BroadInstitute, UCSC, Ensembl, ftp://ftp.ncbi.nlm.nih....
#> # $species: Homo sapiens, Mus musculus, Bos taurus, Pan troglodytes, Da...
#> # $rdataclass: GRanges, BigWigFile, FaFile, ChainFile, OrgDb, Inparanoi...
#> # additional mcols(): taxonomyid, genome, description, tags,
#> #   sourceurl, sourcetype 
#> # retrieve records with, e.g., 'object[["AH2"]]' 
#> 
#>             title                                               
#>   AH2     | Ailuropoda_melanoleuca.ailMel1.69.dna.toplevel.fa   
#>   AH3     | Ailuropoda_melanoleuca.ailMel1.69.dna_rm.toplevel.fa
#>   AH4     | Ailuropoda_melanoleuca.ailMel1.69.dna_sm.toplevel.fa
#>   AH5     | Ailuropoda_melanoleuca.ailMel1.69.ncrna.fa          
#>   AH6     | Ailuropoda_melanoleuca.ailMel1.69.pep.all.fa        
#>   ...       ...                                                 
#>   AH49587 | org.Ce.eg.db.sqlite                                 
#>   AH49588 | org.Xl.eg.db.sqlite                                 
#>   AH49589 | org.Sc.sgd.db.sqlite                                
#>   AH49590 | org.Dr.eg.db.sqlite                                 
#>   AH49591 | org.Pf.plasmo.db.sqlite

Let's start by querying the entries that originate from the PRIDE database:

query(ah, "PRIDE")
#> AnnotationHub with 4 records
#> # snapshotDate(): 2015-11-19 
#> # $dataprovider: PRIDE
#> # $species: Erwinia carotovora
#> # $rdataclass: AAStringSet, MSnSet, mzRident, mzRpwiz
#> # additional mcols(): taxonomyid, genome, description, tags,
#> #   sourceurl, sourcetype 
#> # retrieve records with, e.g., 'object[["AH49006"]]' 
#> 
#>             title                                                         
#>   AH49006 | PXD000001: Erwinia carotovora and spiked-in protein fasta file
#>   AH49007 | PXD000001: Peptide-level quantitation data                    
#>   AH49008 | PXD000001: raw mass spectrometry data                         
#>   AH49009 | PXD000001: MS-GF+ identiciation data

Or those of a specific project

ah[grep("PXD000001", ah$title)]
#> AnnotationHub with 4 records
#> # snapshotDate(): 2015-11-19 
#> # $dataprovider: PRIDE
#> # $species: Erwinia carotovora
#> # $rdataclass: AAStringSet, MSnSet, mzRident, mzRpwiz
#> # additional mcols(): taxonomyid, genome, description, tags,
#> #   sourceurl, sourcetype 
#> # retrieve records with, e.g., 'object[["AH49006"]]' 
#> 
#>             title                                                         
#>   AH49006 | PXD000001: Erwinia carotovora and spiked-in protein fasta file
#>   AH49007 | PXD000001: Peptide-level quantitation data                    
#>   AH49008 | PXD000001: raw mass spectrometry data                         
#>   AH49009 | PXD000001: MS-GF+ identiciation data

To see the metadata of a specific entry, we use its AnnotationHub entry number inside single [

ah["AH49008"]
#> AnnotationHub with 1 record
#> # snapshotDate(): 2015-11-19 
#> # names(): AH49008
#> # $dataprovider: PRIDE
#> # $species: Erwinia carotovora
#> # $rdataclass: mzRpwiz
#> # $title: PXD000001: raw mass spectrometry data
#> # $description: Four human TMT spliked-in proteins in an Erwinia caroto...
#> # $taxonomyid: 554
#> # $genome: NA
#> # $sourcetype: mzML
#> # $sourceurl: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2012/03/PXD0...
#> # $sourcelastmodifieddate: NA
#> # $sourcesize: NA
#> # $tags: Proteomics, TMT6, LTQ Orbitrap Velos, PMID:23692960 
#> # retrieve record with 'object[["AH49008"]]'

To access the actual data, raw mass spectrometry data in this case, we double the [[

library("mzR")
#> Loading required package: Rcpp
rw <- ah[["AH49008"]]
#> loading from cache '/home/lg390/.AnnotationHub/55314'
rw
#> Mass Spectrometry file handle.
#> Filename:  55314 
#> Number of scans:  7534

In this case, we have an instance of class mzRpwiz, that can be processed as anticipated.

In the short demonstration above, we had direct and standardised access to the raw data, without a need to manually open this raw data or worry about the file format. The data was prepared and converted into a standard Bioconductor data types for immediate consumption by the user. This is also valid for other relevant data types such as identification results, fasta files or protein of peptide quantitation data.

See the ProteomicsAnnotationHubData vignette for details on available data and how to add new proteomics data to AnnotationHub.

lgatto/ProteomicsAnnotationHubData documentation built on Jan. 11, 2022, 3:41 a.m.