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.

 

Product sheet (PDF)

White paper, microarray analysis (PDF)

RNA-seq Application Note (PDF)

Poster presentation (PDF) - 2010 Meeting of the American Society of Human Genetics.

 

 

BioFormatix is studying the use of proprietary Palladium Catalyzed Chemical Amplification (PdCCA) technology

to develop ultra-sensitive bioassays that can detect very low concentrations of tumor biomarkers in blood.

 

Detection of cancer in the early, asymptomatic stages dramatically improves patients survival, but currently

there are no simple and reliable molecular diagnostic cancer screening tests. Even at early stages, tumors

secrete specific molecular biomarkers, but their concentration in body fluids is typically significantly

below the sensitivity of currently available assays. More sensitive detection platforms will facilitate

the development of simple, non-invasive screening tests for early cancer diagnosis and treatment, leading

to improved patient survival.

 

PdCCA is a generic technology that can be universally applied to different assay platforms. In the standard

ELISA format, PdCCA may provide a factor of 10² to 10³ fold increase in sensitivity in immunoassays for

which a detection antibody of high selectivity is available. This increase in sensitivity will lower

the detection threshold of currently used methods to the desired range of ng-pg/ml, allowing for

development of screening biomarkers for early tumor detection.

 

The current feasibility study, performed in collaboration Fred Hutchinson Cancer Research Center

focuses on early biomarkers related to ovarian cancer and breast cancer.

The research is funded by an SBIR grant from the NIH National Cancer Institute.

 

PdCCA modified sandwich ELISA bioassay