Cargando…
Shambhala: a platform-agnostic data harmonizer for gene expression data
BACKGROUND: Harmonization 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 p...
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366102/ https://www.ncbi.nlm.nih.gov/pubmed/30727942 http://dx.doi.org/10.1186/s12859-019-2641-8 |
_version_ | 1783393546754064384 |
---|---|
author | Borisov, Nicolas Shabalina, Irina Tkachev, Victor Sorokin, Maxim Garazha, Andrew Pulin, Andrey Eremin, Ilya I. Buzdin, Anton |
author_facet | Borisov, Nicolas Shabalina, Irina Tkachev, Victor Sorokin, Maxim Garazha, Andrew Pulin, Andrey Eremin, Ilya I. Buzdin, Anton |
author_sort | Borisov, Nicolas |
collection | PubMed |
description | BACKGROUND: Harmonization 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. RESULTS: Unlike 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. CONCLUSION: Our 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2641-8) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-6366102 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-63661022019-02-15 Shambhala: a platform-agnostic data harmonizer for gene expression data Borisov, Nicolas Shabalina, Irina Tkachev, Victor Sorokin, Maxim Garazha, Andrew Pulin, Andrey Eremin, Ilya I. Buzdin, Anton BMC Bioinformatics Research Article BACKGROUND: Harmonization 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. RESULTS: Unlike 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. CONCLUSION: Our 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. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12859-019-2641-8) contains supplementary material, which is available to authorized users. BioMed Central 2019-02-06 /pmc/articles/PMC6366102/ /pubmed/30727942 http://dx.doi.org/10.1186/s12859-019-2641-8 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Borisov, Nicolas Shabalina, Irina Tkachev, Victor Sorokin, Maxim Garazha, Andrew Pulin, Andrey Eremin, Ilya I. Buzdin, Anton Shambhala: a platform-agnostic data harmonizer for gene expression data |
title | Shambhala: a platform-agnostic data harmonizer for gene expression data |
title_full | Shambhala: a platform-agnostic data harmonizer for gene expression data |
title_fullStr | Shambhala: a platform-agnostic data harmonizer for gene expression data |
title_full_unstemmed | Shambhala: a platform-agnostic data harmonizer for gene expression data |
title_short | Shambhala: a platform-agnostic data harmonizer for gene expression data |
title_sort | shambhala: a platform-agnostic data harmonizer for gene expression data |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6366102/ https://www.ncbi.nlm.nih.gov/pubmed/30727942 http://dx.doi.org/10.1186/s12859-019-2641-8 |
work_keys_str_mv | AT borisovnicolas shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT shabalinairina shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT tkachevvictor shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT sorokinmaxim shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT garazhaandrew shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT pulinandrey shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT ereminilyai shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata AT buzdinanton shambhalaaplatformagnosticdataharmonizerforgeneexpressiondata |