Bar charts with error bars
This collection of screenshots provides a sampling of capabilities and features from each of the products in the JMP family.
The Nonlinear platform can fit curved data without the need to pre-impute a formula or starting values. Simply select from one of the models in a rich library, which includes popular bioassay or pharmacokinetic models, and data is fit automatically.
Fit Curve (Nonlinear platform)
Send data to MATLAB, execute code and return data to JMP for visualization and analysis. The interface lets JMP seamlessly integrate with MATLAB to extend JMP further for even greater analytic power and flexibility.
Interface to MATLAB
The advanced neural network capabilities in JMP Pro include the choice of three activation functions and two layers, a choice of validation methods, as well as gradient boosting.
Advanced neural modeling
Advanced features for partial least squares (PLS) regression in the Fit Model platform. Model effects can include categorical factors, as well as crossed and polynomial terms.
Advanced partial least squares (PLS)
A Hierarchical Cluster report with two-way clustering identifies relationships between individual subjects and the events, findings and interventions included in the safety analyses for the study.
The industry-standard Hy’s Law display in JMP Clinical is interactive for selection of subjects. A dashboard containing a scatterplot matrix of transaminases and bilirubin; mosaic plot of days until bilirubin elevation and missing lab tests report tab.
Hy's Law Dashboard
Use paired RNA expression and DNA hybridization data to screen for indications of allele-specific expression with the new Allele Specific Expression Filter process. Examine a summary volcano plot, then drill down to display detailed information for specific SNPs.
Allele Specific Expression Filter process
Overlay continuous variables such as p-values, intensities, counts or fold changes on simple and complex genomes to identify interesting regions, then drill down to view detailed statistical results and tracks.
Significant enhancements to copy number partitioning let users display segment means, shade segments relative to a referencevalue, and filter results to display segmentsthat meet a pre-specified cutoff.
Copy number partitioning
Overlay continuous variables such as p-values, intensities, counts or fold changes on simple and complex genomes, with the option to display single chromosomes as circular. Identify interesting regions, then drill down to view detailed results and tracks.
Display singular chromosomes as singular
Create, compress, and incorporate genetic distance matrices into association tests that simultaneously correct for relatedness and population structure. Distance matrices may also be created to display relationships between continuous measures, or custom distance matrices clustered and visualized.
Genetic distance matrices
Scale count data across samples using TMM normalization, compare TMM factors between samples, and view kernel density plots of normalized data.
Kernel Density MA Plot by Sample after TMM Normalization
Display summaries of your statistical analyses in genome context to identify interesting regions with pre-built settings for commonly used genomes, or by creating custom genome views. Then drill down to overlay gene, histogram, SNP and heat plot tracks on statistical results. Here, p-values across a genomic region are overlaid with co-localized genes and a histogram track that summarizes raw exon-level data for two samples of particular interest.
Summarize statistical analyses in genome context
Visualize shared patterns with multiway Venn diagrams. Overlay statistical findingsand annotation categories to drill down on the most important gene sets.
Visualize shared patterns with multiway Venn diagrams
Examine a summary volcano plot to identify pathways that are over- or under-represented in your significant gene list, using a variety of enrichment tests.
Volcano plot to visualize Analysis of Variance