A decade of GigaScience: 10 years of the evolving genomic and biomedical standards landscape

Abstract

Standardization of omics data drives FAIR data practices through community-built genomic data standards and biomedical ontologies. Use of standards has progressed from a foreign concept to a sought-after solution, moving from efforts to coordinate data within individual research projects to research communities coming together to identify solutions to common challenges. Today we are seeing the benefits of this multidecade groundswell to coordinate, exchange, and reuse data; to compare data across studies; and to integrate data across previously siloed resources.

Omics and Multi-Omics Analysis for the Early Identification and Improved Outcome of Patients with Psoriatic Arthritis

“…To benefit from the wealth of methods used to mine multi-omics data, it is essential to align the data and verify their quality before integration. Data should be formatted according to international standards, including standard bioinformatics file formats (such as FASTA, FASTQ, SAM/BAM, VCF and GFF), and “minimum information” standards for omics experiments [ 110 ], including MIGS/MIMS for genomics [ 111 ] and MIAPE for proteomics [ 112 ]. The data must be checked to ensure they include the same annotation references (e.g., genome version, standard gene and protein names).…”