Genomics Proteomics & BioinformaticsBioinformaticsPeer-reviewed journal article
rePROBE: Workflow for Revised Probe Assignment and Updated Probe-Set Annotation in Microarrays
Frieder HadlichiD, Henry ReyeriD, Michael OsteriD, Nares TrakooljuliD, Eduard MurániiD, Siriluck PonsuksiliiD, Klaus WimmersiD
Abstract
Commercial and customized microarrays are valuable tools for the analysis of holistic expression patterns, but require the integration of the latest genomic information. This study provides a comprehensive workflow implemented in an R package (rePROBE) to assign the entire probes and to annotate the probe sets based on up-to-date genomic and transcriptomic information. The rePROBE R package is freely available at https://github.com/friederhadlich/rePROBE. It can be applied to available gene expression microarray platforms and addresses both public and custom databases. The revised probe assignment and updated probe-set annotation were applied to commercial microarrays available for different livestock species, i.e. ChiGene-1_0-st (Gallus gallus, 443,579 probes; 18,530 probe sets), PorGene-1_1-st (Sus scrofa, 592,005; 25,779) and BovGene-1_0-st (Bos taurus, 530,717; 24,759) as well as human (Homo sapiens, HuGene-1_0-st) and mouse (Mus musculus, HT_MG-430_PM) microarrays. Using current specie-specific transcriptomic information (RefSeq, Ensembl and partially non-redundant nucleotide sequences) and genomic information, the applied workflow revealed 297,574 probes for chickens (pig: 384,715; cattle: 363,077; human: 481,168; mouse: 324,942) assigned to 15,689 probe sets (pig: 21,673; cattle: 21,238; human: 23,495; mouse: 32,494). These are representative of 12,641 unique genes that were both annotated and positioned (pig: 15,758; cattle: 18,046; human: 20,167; mouse: 16,335). Additionally, the workflow collects information on the number of single nucleotide polymorphisms (SNPs) within respective targeted genomic regions and thus provides a detailed basis for comprehensive analyses such as quantitative trait locus (eQTL) expression studies to identify quantitative and functional traits.
- organism: human
- organism: mouse
- organism: rat
- assay: bulk RNA-seq
- research focus: database / resource
- research focus: variant effect prediction
- research focus: eQTL / molecular QTL mapping
- approach: statistical model
- Citations
- 8
- FWCI
- 0.39
- Field percentile
- 50th percentile
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