VIPR: A probabilistic algorithm for analysis of microbial detection microarrays

ABSTRACT: The development of rapid and sensitive assays capable of detecting a wide range of infectious agents is critical for the effective diagnosis of diseases that have multiple etiologies. In recent years, many microarray-based diagnostics have been developed to identify viruses present in clinical specimens in a highly parallel fashion. Unfortunately, the rate of development of algorithms to interpret data generated from such platforms has not been commensurate. In particular, none of the existing interpretive algorithms is capable of utilizing empirical training data in a Bayesian framework. We have developed an interpretive algorithm, VIPR (Viral Identification using a PRobabilistic algorithm), to capitalize on our ability to generate positive control data for analysis of microbial diagn

ORGANISM(S): unidentified

SUBMITTER: Adam Allred 

PROVIDER: E-GEOD-21407 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress