BioNumerics
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Application data |
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| Biological application domain(s) | Workflows, Comparative genomics, Quality control, Data handling, Sequence assembly, Epidemiology, Microbial Surveillance, Genotyping, Whole genome resequencing, Sequence analysis |
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| Principal bioinformatics method(s) | Sequence assembly, Read mapping, Annotation, Variant calling, Comparative genomics, Workflows, Sequence alignment, Genome visualisation |
| Technology | Sanger, Illumina, Ion Torrent, PacBio |
| Created at | Applied Maths NV |
| Maintained? | Yes |
| Input format(s) | .ab1, (C)FAST(A/Q), .bam, FNAQual, Compressed fastq, And many others. |
| Software version | 7.5 |
| Interface type(s) | Desktop GUI |
| Resource type(s) | Desktop application |
| Licence | Commercial |
| Operating system(s) | Windows 7 or Higher |
| Contact: | info@applied-maths.com |
Summary: BioNumerics can be used for the analysis of all major applications in bioinformatics
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Description
BioNumerics is a suite of bioinformatics software applications developed by the company Applied Maths NV. BioNumerics can be used for the analysis of all major applications in bioinformatics: 1D electrophoresis gels, chromatographic and spectrometric profiles, phenotype characters, microarrays, sequences, etc. BioNumerics is able to combine information from various genomic and phenotypic sources into one global database and conduct conclusive analyses
BioNumerics was released in 1996 and is still today a platform for the management, storage and (statistical) analysis of all types of biological data. BioNumerics is used by several networks around the globe to share and identify strain information. Pulsenet, a network run by the Centers for Disease Control and Prevention (CDC), uses BioNumerics to distinguish pulsed field gel electrophoresis (PFGE) patterns from different strains of organisms. Applied Maths NV is also intricately involved in the development of PulseNet Next (http://www.cdc.gov/pulsenet/next-generation.html), where next generation sequencing is being used for real-time microbial surveillance.
BioNumerics offers an all in one solution for molecular typing of microorganisms. It is the only software platform that offers integrated analysis of all major applications in Bioinformatics: 1D electrophoresis gels, all kinds of chromatographic and spectrometric profiles, phenotype characters, microarrays, and sequences (Sanger and NGS). The unique power of BioNumerics lies in its ability to combine information from various genomic and phenotypic sources into one global database and conduct conclusive analyses.
The functionalities on next generation sequencing include both the processing of next generation reads as well as extensive follow up analysis:
- The raw read files can be demultiplexed and trimmed, either according to default pipelines with user adaptable parameters or with custom pipelines. All details on an executed pipeline are stored together with the samples in the database.
- The cleaned up reads can be used for de novo assembly with several algorithms, reference based assembly, mapping to a reference, annotation,... Again default pipelines are available as well as the option to define custom pipeline. Detailed reports on the performance and results of the algorithms are also available.
- Whole genome sequences, either in draft or complete can be compared and aligned to each other using a seed based approach. This allows the user to analyse the organization and functional behavior of genomes. The relatedness of isolates can be investigated with different methods including SNP analysis and whole genome MLST (wgMLST http://www.applied-maths.com/applications/wgmlst). A wgMLST analysis will call alleles of all loci present in the pan genome of an organism. This allele calling can be performed on the unassembled reads as well as on the de novo assembled draft or complete genome. This approach provides a much higher resolution when comparing closely related isolates compared to a core genome MLST. If available, the analysis can be easily limited to a defined core genome scheme, to allow a faster comparison of more distantly related isolates. The comparison of the wgMLST profile of thousands of isolates takes only a few minutes on a regular PC. It is therefore a very useful technique for outbreak detection and surveillance.
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