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Conceptual aspects of large meta-analyses with publicly available microarray data: a case study in oncology.

ABSTRACT: Large public repositories of microarray experiments offer an abundance of biological data. It is of interest to use and to combine the available material to create new biological information and to develop a broader view on biological phenomena.Meta-analyses recombine similar information over a series of experiments to sketch scientific aspects which were not accessible by each of the single experiments. Meta-analysis of high-throughput experiments has to handle methodological as well as technical challenges. Methodological aspects concern the identification of homogeneous material which can be combined by appropriate statistical procedures. Technical challenges come from the data management of large amounts of high-dimensional data, long computation time, as well as the handling of the stored phenotype data.This paper compares in a meta-analysis of a large series of microarray experiments the interaction structure within selected pathways between different tumour entities. The feasibility of such a study is explored and a technical as well as a statistical framework for its completion is presented. Multiple obstacles were met during completion of this project. They are mainly related to the quality of the available data and influence the biological interpretation of the results derived.The sobering experience of our study asks for combined efforts to improve the data quality in public repositories of high-throughput data. The exploration of the available data in large meta-analyses is limited by incomplete documentation of essential aspects of experiments and studies, by technical deficiencies in the data stored, and by careless duplications of data.

SUBMITTER: Schmidberger M

PROVIDER: S-EPMC3045047 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Conceptual aspects of large meta-analyses with publicly available microarray data: a case study in oncology.

Schmidberger Markus M Lennert Sabine S Mansmann Ulrich U

Bioinformatics and biology insights 20110123

Large public repositories of microarray experiments offer an abundance of biological data. It is of interest to use and to combine the available material to create new biological information and to develop a broader view on biological phenomena.Meta-analyses recombine similar information over a series of experiments to sketch scientific aspects which were not accessible by each of the single experiments. Meta-analysis of high-throughput experiments has to handle methodological as well as technic ...[more]

PMID: 21423405

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Project description:Malaria is a deadly disease caused by Apicomplexan parasites of the Plasmodium genus. Several species of the Plasmodium genus are known to be infectious to human, of which P. falciparum is the deadliest. Post-translational modifications (PTMs) of proteins coordinate cell signalling and hence, regulate many biological processes in P. falciparum homeostasis and host infection, of which the most highly studied is phosphorylation. Phosphosites on proteins can be identified by tandem mass spectrometry (MS) performed on enriched samples (phosphoproteomics), followed by downstream computational analyses. We have performed a large-scale meta-analysis of 11 publicly available phosphoproteomics datasets, to build a comprehensive atlas of phosphosites in the P. falciparum proteome, using robust pipelines aimed at strict control of false identifications. We identified a total of 28,495 phosphorylated sites on P. falciparum proteins at 5% false localisation rate (FLR) and, of those, 18,100 at 1% FLR. We identified significant sequence motifs, likely indicative of different groups of kinases, responsible for different groups of phosphosites. Conservation analysis identified clusters of phosphoproteins that are highly conserved, and others that are evolving faster within the Plasmodium genus, and implicated in different pathways. We also explored the structural context of phosphosites, identifying a strong enrichment for phosphosites on fast evolving (low conservation) intrinsically disordered regions (IDRs) of proteins. In other species, IDRs have been shown to have an important role in modulating protein-protein interactions, particularly in signalling, and thus warranting further study for their roles in host-pathogen interactions. All data has made available via UniProt, PRIDE and PeptideAtlas, with visualisation interfaces for exploring phosphosites in the context of other data on Plasmodium proteins.We have re-analysed publicly available mass spectrometry (MS) data sets enriched for phosphopeptides from Asian rice (Oryza sativa). In total we have identified, 15522 phosphosites on Serine, Threonine and Tyrosine residues on rice proteins. The data has been loaded into UniProtKB, enabling researchers to visualise the sites alongside other stored data on rice proteins, including structural models from AlphaFold2, and into PeptideAtlas, enabling visualisation of the source evidence for each site, including scores and source mass spectra. We identified sequence motifs for phosphosites, and link motifs to enrichment of different biological processes, indicating different downstream regulation caused by different kinase groups. We cross-referenced phosphosites against single amino acid variation (SAAV) data sourced from the rice 3000 genomes data, to identify SAAVs within or proximal to phosphosites that could cause loss of a particular site in a given rice variety. The data was further clustered to identify groups of sites with similar patterns across rice family groups, allowing us to identify sites highly conserved in Japonica, but mostly absent in, for example, Aus type rice varieties - known to have different responses to drought. These resources can assist rice researchers to discover alleles with significantly different functional effects across rice varieties.

Dataset Information

Conceptual aspects of large meta-analyses with publicly available microarray data: a case study in oncology.

Publications

Conceptual aspects of large meta-analyses with publicly available microarray data: a case study in oncology.

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