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MutSpec: a Galaxy toolbox for streamlined analyses of somatic mutation spectra in human and mouse cancer genomes.

Ardin M, Cahais V, Castells X, Bouaoun L, Byrnes G, Herceg Z, Zavadil J, Olivier M - BMC Bioinformatics (2016)

Bottom Line: Results are provided in various formats including rich graphical outputs.An example is presented to illustrate the package functionalities, the straightforward workflow analysis and the richness of the statistics and publication-grade graphics produced by the tool.MutSpec can thus effectively assist in the discovery of complex mutational processes resulting from exogenous and endogenous carcinogenic insults.

View Article: PubMed Central - PubMed

Affiliation: Molecular Mechanisms and Biomarkers Group, International Agency for Research on Cancer, F69372, Lyon, France.

ABSTRACT

Background: The nature of somatic mutations observed in human tumors at single gene or genome-wide levels can reveal information on past carcinogenic exposures and mutational processes contributing to tumor development. While large amounts of sequencing data are being generated, the associated analysis and interpretation of mutation patterns that may reveal clues about the natural history of cancer present complex and challenging tasks that require advanced bioinformatics skills. To make such analyses accessible to a wider community of researchers with no programming expertise, we have developed within the web-based user-friendly platform Galaxy a first-of-its-kind package called MutSpec.

Results: MutSpec includes a set of tools that perform variant annotation and use advanced statistics for the identification of mutation signatures present in cancer genomes and for comparing the obtained signatures with those published in the COSMIC database and other sources. MutSpec offers an accessible framework for building reproducible analysis pipelines, integrating existing methods and scripts developed in-house with publicly available R packages. MutSpec may be used to analyse data from whole-exome, whole-genome or targeted sequencing experiments performed on human or mouse genomes. Results are provided in various formats including rich graphical outputs. An example is presented to illustrate the package functionalities, the straightforward workflow analysis and the richness of the statistics and publication-grade graphics produced by the tool.

Conclusions: MutSpec offers an easy-to-use graphical interface embedded in the popular Galaxy platform that can be used by researchers with limited programming or bioinformatics expertise to analyse mutation signatures present in cancer genomes. MutSpec can thus effectively assist in the discovery of complex mutational processes resulting from exogenous and endogenous carcinogenic insults.

No MeSH data available.


Related in: MedlinePlus

Overview of MutSpec tools and workflow. List of variants identified in a set of cancer samples may be imported as a single VCF files that contains all samples (identified by a sample ID) or as multiple VCFs (one for each sample). The first tool to use is MutSpec_Annot for annotating variants with structural and functional information. These annotations may be used to filter out variants that are known polymorphisms or located in segmental duplication regions with the MutSpec-Filter tool. If a single VCF file containing several samples is uploaded, the MutSpec-Split tool should be used to split data by sample using the sample ID. This tool generates automatically a dataset collection. If multiple VCFs are uploaded, MutSpec-Split should not be run but the annotated VCF should be grouped in a dataset collection. MutSpec-Stat can then be run on the dataset collection to generate various statistics on variants characteristics. These statistics may be visualized as graphs on html pages or downloaded as a single Excel file. The report generated by MutSpec-Stat can then be used as input of MutSpec-NMF to extract mutation signatures present in the sample set. MutSpec-NMF generates plots showing the identified signatures and the contribution of each signature to the mutation load of each sample. Finally, MutSpec-Compare can be used to calculate cosine similarity values between the obtained signatures and a set of reference signatures (published or user-defined). These results are shown as a heatmap
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Fig1: Overview of MutSpec tools and workflow. List of variants identified in a set of cancer samples may be imported as a single VCF files that contains all samples (identified by a sample ID) or as multiple VCFs (one for each sample). The first tool to use is MutSpec_Annot for annotating variants with structural and functional information. These annotations may be used to filter out variants that are known polymorphisms or located in segmental duplication regions with the MutSpec-Filter tool. If a single VCF file containing several samples is uploaded, the MutSpec-Split tool should be used to split data by sample using the sample ID. This tool generates automatically a dataset collection. If multiple VCFs are uploaded, MutSpec-Split should not be run but the annotated VCF should be grouped in a dataset collection. MutSpec-Stat can then be run on the dataset collection to generate various statistics on variants characteristics. These statistics may be visualized as graphs on html pages or downloaded as a single Excel file. The report generated by MutSpec-Stat can then be used as input of MutSpec-NMF to extract mutation signatures present in the sample set. MutSpec-NMF generates plots showing the identified signatures and the contribution of each signature to the mutation load of each sample. Finally, MutSpec-Compare can be used to calculate cosine similarity values between the obtained signatures and a set of reference signatures (published or user-defined). These results are shown as a heatmap

Mentions: MutSpec is an implementation of Perl and R scripts or packages into several Galaxy tools designed to (1) annotate genome variations (MutSpec-Annot), (2) filter and parse list of variants (MutSpec-Filter and MutSpec-Split respectively), (3) compute various statistics describing mutation spectra features (MutSpec-Stat), (4) extract mutation signatures defined by the six types of single base substitutions (SBS) in their trinucleotide sequence context (MutSpec-NMF), (5) compare the obtained signatures with published ones (MutSpec-Compare). The tools are designed to work in a logical sequence, using as input the outputs of each preceding tool. A typical analysis workflow is shown in Fig. 1. The public packages used and the Perl scripts that support each tool are described in Table 1. The tools produce simple tab-delimited text files or content-rich html pages with graphical representations of the data and hyperlinks to underlying data. All figures and tables that are produced by the different tools can be downloaded as individual files. Format requirements and details on the produced outputs are described below.Fig. 1


MutSpec: a Galaxy toolbox for streamlined analyses of somatic mutation spectra in human and mouse cancer genomes.

Ardin M, Cahais V, Castells X, Bouaoun L, Byrnes G, Herceg Z, Zavadil J, Olivier M - BMC Bioinformatics (2016)

Overview of MutSpec tools and workflow. List of variants identified in a set of cancer samples may be imported as a single VCF files that contains all samples (identified by a sample ID) or as multiple VCFs (one for each sample). The first tool to use is MutSpec_Annot for annotating variants with structural and functional information. These annotations may be used to filter out variants that are known polymorphisms or located in segmental duplication regions with the MutSpec-Filter tool. If a single VCF file containing several samples is uploaded, the MutSpec-Split tool should be used to split data by sample using the sample ID. This tool generates automatically a dataset collection. If multiple VCFs are uploaded, MutSpec-Split should not be run but the annotated VCF should be grouped in a dataset collection. MutSpec-Stat can then be run on the dataset collection to generate various statistics on variants characteristics. These statistics may be visualized as graphs on html pages or downloaded as a single Excel file. The report generated by MutSpec-Stat can then be used as input of MutSpec-NMF to extract mutation signatures present in the sample set. MutSpec-NMF generates plots showing the identified signatures and the contribution of each signature to the mutation load of each sample. Finally, MutSpec-Compare can be used to calculate cosine similarity values between the obtained signatures and a set of reference signatures (published or user-defined). These results are shown as a heatmap
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
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getmorefigures.php?uid=PMC4835840&req=5

Fig1: Overview of MutSpec tools and workflow. List of variants identified in a set of cancer samples may be imported as a single VCF files that contains all samples (identified by a sample ID) or as multiple VCFs (one for each sample). The first tool to use is MutSpec_Annot for annotating variants with structural and functional information. These annotations may be used to filter out variants that are known polymorphisms or located in segmental duplication regions with the MutSpec-Filter tool. If a single VCF file containing several samples is uploaded, the MutSpec-Split tool should be used to split data by sample using the sample ID. This tool generates automatically a dataset collection. If multiple VCFs are uploaded, MutSpec-Split should not be run but the annotated VCF should be grouped in a dataset collection. MutSpec-Stat can then be run on the dataset collection to generate various statistics on variants characteristics. These statistics may be visualized as graphs on html pages or downloaded as a single Excel file. The report generated by MutSpec-Stat can then be used as input of MutSpec-NMF to extract mutation signatures present in the sample set. MutSpec-NMF generates plots showing the identified signatures and the contribution of each signature to the mutation load of each sample. Finally, MutSpec-Compare can be used to calculate cosine similarity values between the obtained signatures and a set of reference signatures (published or user-defined). These results are shown as a heatmap
Mentions: MutSpec is an implementation of Perl and R scripts or packages into several Galaxy tools designed to (1) annotate genome variations (MutSpec-Annot), (2) filter and parse list of variants (MutSpec-Filter and MutSpec-Split respectively), (3) compute various statistics describing mutation spectra features (MutSpec-Stat), (4) extract mutation signatures defined by the six types of single base substitutions (SBS) in their trinucleotide sequence context (MutSpec-NMF), (5) compare the obtained signatures with published ones (MutSpec-Compare). The tools are designed to work in a logical sequence, using as input the outputs of each preceding tool. A typical analysis workflow is shown in Fig. 1. The public packages used and the Perl scripts that support each tool are described in Table 1. The tools produce simple tab-delimited text files or content-rich html pages with graphical representations of the data and hyperlinks to underlying data. All figures and tables that are produced by the different tools can be downloaded as individual files. Format requirements and details on the produced outputs are described below.Fig. 1

Bottom Line: Results are provided in various formats including rich graphical outputs.An example is presented to illustrate the package functionalities, the straightforward workflow analysis and the richness of the statistics and publication-grade graphics produced by the tool.MutSpec can thus effectively assist in the discovery of complex mutational processes resulting from exogenous and endogenous carcinogenic insults.

View Article: PubMed Central - PubMed

Affiliation: Molecular Mechanisms and Biomarkers Group, International Agency for Research on Cancer, F69372, Lyon, France.

ABSTRACT

Background: The nature of somatic mutations observed in human tumors at single gene or genome-wide levels can reveal information on past carcinogenic exposures and mutational processes contributing to tumor development. While large amounts of sequencing data are being generated, the associated analysis and interpretation of mutation patterns that may reveal clues about the natural history of cancer present complex and challenging tasks that require advanced bioinformatics skills. To make such analyses accessible to a wider community of researchers with no programming expertise, we have developed within the web-based user-friendly platform Galaxy a first-of-its-kind package called MutSpec.

Results: MutSpec includes a set of tools that perform variant annotation and use advanced statistics for the identification of mutation signatures present in cancer genomes and for comparing the obtained signatures with those published in the COSMIC database and other sources. MutSpec offers an accessible framework for building reproducible analysis pipelines, integrating existing methods and scripts developed in-house with publicly available R packages. MutSpec may be used to analyse data from whole-exome, whole-genome or targeted sequencing experiments performed on human or mouse genomes. Results are provided in various formats including rich graphical outputs. An example is presented to illustrate the package functionalities, the straightforward workflow analysis and the richness of the statistics and publication-grade graphics produced by the tool.

Conclusions: MutSpec offers an easy-to-use graphical interface embedded in the popular Galaxy platform that can be used by researchers with limited programming or bioinformatics expertise to analyse mutation signatures present in cancer genomes. MutSpec can thus effectively assist in the discovery of complex mutational processes resulting from exogenous and endogenous carcinogenic insults.

No MeSH data available.


Related in: MedlinePlus