JMP® Genomics
Advanced genomic data analysis software that helps you visualize your data and discover more
JMP Genomics provides a unique integrated analysis solution for biological experiments. Whether you need to detect differential expression patterns, find signals in next-generation sequencing data, discover reliable biomarker profiles, perform single-cell sequencing analysis or increase genetic diversity for plant traits in silico, JMP Genomics takes you from data to understanding faster.
Have a minute? See JMP Genomics in action.
Crop scientists
Using cutting-edge algorithms based on the lastest agronomic research, high-paced breeding cycles executed in JMP Genomics allow plant breeders and crop scientists to drive the selection of healthier crops by modeling genetic variability, optimizing breeding choices, simulating multiple-trait breeding programs and balancing trade-offs across key desirable traits.
Translational scientists
Cellular composition analysis using bulk genomics data enables translational scientists to visually explore complex and rare cell populations, detect differential gene expression patterns across cell types through clustering analysis, profile transcriptional changes in immune cells to help develop vaccines or treatment, and uncover the evolutionary dynamics of tumor progression, metastasis and treatment resistance.
Biomarker scientists
Biomarker scientists gather more data on drug response and disease biology than ever before. But extracting statistically valid insights from all that data has never been more challenging. JMP Genomics helps you design and analyze complex experiments, apply cutting-edge predictive modeling and machine learning algorithms to large genomic datasets and associate biological signals with clinical outcomes.
Quantitative geneticists
With the increasing accessibility of sequenced genomes, quantitative geneticists are now flooded with rich data to investigate the genetic basis of disease. JMP Genomics lets you analyze genome-wide association studies (GWAS), explore genetic variability and structure with advanced statistical association models and build complex genetic risk models to understand the biological underpinnings of disease and health outcomes.
The Core Capabilities of JMP Genomics®
Genomic Selection for Crop Improvement
Explore genotype-environment interactions, and uncover optimal combinations of markers to produce desirable traits and simulate the progeny of potential crosses.
Pharmacogenomics
Analyze integrated genomic patterns from DNA, RNA, metabolite and protein expression to discover the biological roles in disease and drug response.
Expression
Analyze microarray or RNA-seq studies through point-and-click workflows tailored to quality control, normalization and ANOVA modeling for differential gene and exon expression.
Statistical Genetics
Examine associations with comprehensive GWAS capabilities. Apply techniques from simple case-control association to complex mixed models, and easily control for population structure and cryptic relatedness.
Next-Gen Sequencing
Streamline the statistical analysis of next-gen data through a variety of tailored modeling methods and workflows.
Linkage Mapping
Create optimal linkage maps for experimental populations, visualize marker maps and perform extensive QTL analyses.
Predictive Modeling
Identify biomarkers from high-dimensional data sets. Build and compare multiple models for multiple traits through cross-validated predictive modeling reviews with extensive predictor screening capabilities.