During every release cycle, the JMP Genomics development team adds support for new data types and updates our existing import processes to work with the latest formats. We can bring in many types of raw or summarized data files from next-gen sequencing studies and microarray experiments.
These files are imported into JMP Genomics and saved as SAS data sets that can be examined with quality control, normalization, modeling, pattern discovery and predictive modeling tools. It’s definitely worth a visit to the JMP Life Sciences Resource site to download our updated Step-by-Step Guides that review import of various supported file formats. Detailed documentation is also available for all import processes within the software.
While developing JMP Genomics 6, we’ve been working with customers who are importing larger sets of SAM or BAM files for the purpose of counting aligned reads within genomic features. As a result, we have significantly improved the performance of our counting algorithm for this release. After importing a set of SAM or BAM files, we provide users with raw counts at the feature level, as well as RPM and RPKM values. These summarized data sets can be assessed, normalized and analyzed with our statistical tools for RNA-seq data, including the Basic RNA-seq Workflow.
We’ve enhanced our VCF file import process, adding new filters that allow you to exclude genotypes or variants from your output data set based on depth and genotype quality. We’ve added support for Complete Genomics’ testvariants pipeline output files, while retaining the option introduced in earlier versions of importing and combining multiple individual variant files from ASM folders. JMP Genomics 6 can also import binary Plink files to better support customers who work with both programs or collaborate with Plink users. We’ve imported Plink text files for several versions, but can now bring a set of binary PED/BIM/FAM files into JMP Genomics for further analysis with our extensive suite of genetic analysis tools.
When importing any raw data types, you can take advantage of the new study structure implemented in JMP Genomics 6 that simplifies the organization of related data sets. You can create new studies during import or add newly imported data to existing studies. Working within the study framework significantly streamlines the selection of settings and data sets of different types (e.g., wide or tall data sets, annotation files). You can mix and match data types within a study, working with microarray, RNA-seq count or variant data sets generated for the same samples -- the structure is quite flexible!
For an overview of the data types currently supported by JMP Genomics 6, please see our product brief here. For technical information about new features in this release, please see the release notes here. If you are interested in seeing the software support additional input types in future releases, please feel free to email me at Shannon dot Conners at jmp dot com with your suggestions!