Molecular Diagnostics
bROC: Analysis of gene expression in microarray and RNA-seq high throughput experiments
bROC (Bootstrapped ROC) is a novel algorithm is used in the discovery of differentially expressed probes/genes
in differential expression experiments. It is available as a plugin for CLC bio Main Workbench and Genomics Workbench.
The algorithm has been tested on Affymetrix GeneChip and Illumina Genome Analyzer data.
The algorithm should be applicable to data from all expression platforms that produce measurements for a large number of molecular entities.
DNA microarray and next generation sequencing (RNA-seq) technologies enable simultaneous profiling of thousands of transcripts and/or genes in cells or tissues.
Their current applications include gene profiling, gene regulation studies, disease biomarker discovery,
toxicogenomics, pharmacogenomics, and clinical diagnostics and prognosis.
Benefits of the bROC algorithm include:
- Works particularly well for experiments with a small number of experimental/biological replicates.
- Non-parametric approach is applicable to all platforms producing expression data for a large number of features (transcripts, genes).
- Includes data normalization (for RNA-seq, mainly).
- When combined with RNA-seq Analysis (CLC bio), provides complete differential expression analysis workflow for RNA-seq data.
- Graphical outputs facilitate interpretation of results.
- With no user-selectable parameters, the algorithm is easy to use.
White paper, microarray analysis (PDF)
RNA-seq Application Note (PDF)
Poster presentation (PDF) - 2010 Meeting of the American Society of Human Genetics.