Cloud Computing Enabled Big Multi-Omics Data
Analytics

Saraswati Koppad; Annappa B; Georgios V Gkoutos; Animesh Acharjee

doi:10.1177/11779322211035921

PMC full text:

Bioinform Biol Insights. 2021; 15: 11779322211035921.

Published online 2021 Jul 28. doi: 10.1177/11779322211035921

Copyright/LicenseRequest permission to reuse

Table 2.

The platforms available to provide global multi-omics profiling information in the cloud framework.

Omics type	Platform	Size of each data type can accommodate (approximately)	Cost of analyzing omics data in cloud (approximately)
Genome^12,13	DNA sequencing	>100 GB (BAM and VCF files)	Per GB storage and transfer rate ranges from $40/test to $66/test
	DNA methylation (array based)
	SNP based
Transcriptome¹⁴ (Total RNA)	RNA-seq	>2000 samples	US$1.30 per sample
Transcriptome¹⁴ (Total RNA)	microRNA sequencing (miRNA)	>2000 samples	US$1.30 per sample
Proteome¹⁵	Protein mass spectrometry	Standard mix proteomic data set	Cost of database search using virtual system over cloud is >US$1
Proteome¹⁵	RPPA	Standard mix proteomic data set
Metabolite¹⁶	Metabolite mass spectrometry	~1 GB	Resources to process ~1GB of 13 C-MFA data are $11
Microbiome^17,18	Ribosome RNA (rRNA) gene sequencing and shotgun MGS	>90 GB (FASTQ data)	Library preparation ~$400 sequencing costs ~$8 per GB

Open in a separate window

Abbreviations: BAM, Binary Alignment/Map; MFA, Metabolic Flux Analysis; MGS, metagenomics sequencing; RPPA, Reverse Phase Protein Array; rRNA, ribosome RNA; SNP, single nucleotide polymorphism.