Shambhala: a platform-agnostic data harmonizer for gene expression data

BMC Bioinformatics

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[1] 0000 0001 1018 3793, grid.440717.1, Faculty of Mathematics and Information Technologies, Petrozavodsk State University, Anokhina str., 20, 185910, Petrozavodsk, Russia;0000 0001 2288 8774, grid.448878.f, I.M. Sechenov First Moscow State Medical University, Sechenov University, 119991, Moscow, Russia;Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA;0000 0001 2288 8774, grid.448878.f, I.M. Sechenov First Moscow State Medical University, Sechenov University, 119991, Moscow, Russia;Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA;0000 0004 0440 1573, grid.418853.3, Group for Genomic Regulation of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997, Moscow, Russia;Department for Regenerative Medicine, JSC Generium, Moscow, Russia;Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA;Department of bioinformatics and molecular networks, OmicsWay Corporation, Walnut, CA, USA;Laboratory of Bioinformatics, Oncology and Immunology, D. Rogachyov Federal Research Center of Pediatric Hematology, 117198, Moscow, Russia;Laboratory for Cell Biology and Developmental Pathology, Federal State Institution “Institute of General Pathology and Pathophysiology”, FSBSI “IGPP”, Moscow, Russia;

关键词: Transcriptome;    Gene expression;    Microarray hybridization;    Next-generation sequencing;    Harmonization of transcriptional profiles;    Comparison of multiple datasets;   

DOI  :  10.1186/s12859-019-2641-8

来源: publisher

【 摘 要 】

BackgroundHarmonization techniques make different gene expression profiles and their sets compatible and ready for comparisons. Here we present a new bioinformatic tool termed Shambhala for harmonization of multiple human gene expression datasets obtained using different experimental methods and platforms of microarray hybridization and RNA sequencing.ResultsUnlike previously published methods enabling good quality data harmonization for only two datasets, Shambhala allows conversion of multiple datasets into the universal form suitable for further comparisons. Shambhala harmonization is based on the calibration of gene expression profiles using the auxiliary standardization dataset. Each profile is transformed to make it similar to the output of microarray hybridization platform Affymetrix Human Gene. This platform was chosen because it has the biggest number of human gene expression profiles deposited in public databases. We evaluated Shambhala ability to retain biologically important features after harmonization. The same four biological samples taken in multiple replicates were profiled independently using three and four different experimental platforms, respectively, then Shambhala-harmonized and investigated by hierarchical clustering.ConclusionOur results showed that unlike other frequently used methods: quantile normalization and DESeq/DESeq2 normalization, Shambhala harmonization was the only method supporting sample-specific and platform-independent biologically meaningful clustering for the data obtained from multiple experimental platforms.

【 授权许可】

CC BY