Mergeomics: a web server for identifying pathological pathways, networks, and key regulators via multidimensional data integrationReport as inadecuate

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BMC Genomics

, 17:722

Human and rodent genomics


BackgroundHuman diseases are commonly the result of multidimensional changes at molecular, cellular, and systemic levels. Recent advances in genomic technologies have enabled an outpour of omics datasets that capture these changes. However, separate analyses of these various data only provide fragmented understanding and do not capture the holistic view of disease mechanisms. To meet the urgent needs for tools that effectively integrate multiple types of omics data to derive biological insights, we have developed Mergeomics, a computational pipeline that integrates multidimensional disease association data with functional genomics and molecular networks to retrieve biological pathways, gene networks, and central regulators critical for disease development.

ResultsTo make the Mergeomics pipeline available to a wider research community, we have implemented an online, user-friendly web server The web server features a modular implementation of the Mergeomics pipeline with detailed tutorials. Additionally, it provides curated genomic resources including tissue-specific expression quantitative trait loci, ENCODE functional annotations, biological pathways, and molecular networks, and offers interactive visualization of analytical results. Multiple computational tools including Marker Dependency Filtering MDF, Marker Set Enrichment Analysis MSEA, Meta-MSEA, and Weighted Key Driver Analysis wKDA can be used separately or in flexible combinations. User-defined summary-level genomic association datasets e.g., genetic, transcriptomic, epigenomic related to a particular disease or phenotype can be uploaded and computed real-time to yield biologically interpretable results, which can be viewed online and downloaded for later use.

ConclusionsOur Mergeomics web server offers researchers flexible and user-friendly tools to facilitate integration of multidimensional data into holistic views of disease mechanisms in the form of tissue-specific key regulators, biological pathways, and gene networks.

KeywordsMultidimensional data integration Omics integration Web server Pathway meta-analysis Network meta-analysis Disease network Key driver GWAS EWAS TWAS AbbreviationsENCODEENCylopedia of DNA Elements

eQTLsExpression quantitative trait loci

EWASEpigenome wide association study

FDRFalse discovery rate

GWASGenome wide association study

HTTPHypertext transfer protocol

KDKey driver

KEGGKyoto encyclopedia of genes and genomes

LDLinkage disequalibrium

LDLLow-density lipoprotein

MDFMarker dependency filtering

Meta-MSEAMeta marker set enrichment analysis

MSEAMarker set enrichment analysis

PHPHypertext preprocessor

PPIProtein-protein interaction

SNPSingle nucleotide polymorphism

TWASTranscritome wide association study

WGCNAWeighted gene coexpression network analysis

wKDAWeighted key driver analysis

Electronic supplementary materialThe online version of this article doi:10.1186-s12864-016-3057-8 contains supplementary material, which is available to authorized users.

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Author: Douglas Arneson - Anindya Bhattacharya - Le Shu - Ville-Petteri Mäkinen - Xia Yang


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