Multiplex Manager 1.0 is a user-friendly cross-platform program that designs efficient combinations of existing genetic marker loci into multiplex polymerase chain reactions and optimizes using prior marker information. The program has the flexibility to solve two design problems: combining all markers into the smallest number of reactions, or alternatively, selecting a subset from many available markers to design an efficient and robust multiplex. Our program minimizes the number of reactions, the genetic linkage, and the difference in annealing temperature. At the same time it maximizes the spacing between markers, the heterozygosity, and the number of alleles. The final output provides easily interpreted and informative graphical representations of reactions, as well as the option of manually editing final reactions. Multiplex Manager 1.0 is freely available at www.multiplexmanager.com.

BackgroundAs genome-wide sequence analyses for complex human disease determinants are expanding, it is increasingly necessary to develop strategies to promote discovery and validation of potential disease-gene associations.FindingsHere we present a dynamic web-based platform – GWATCH – that automates and facilitates four steps in genetic epidemiological discovery: 1) Rapid gene association search and discovery analysis of large genome-wide datasets; 2) Expanded visual display of gene associations for genome-wide variants (SNPs, indels, CNVs), including Manhattan plots, 2D and 3D snapshots of any gene region, and a dynamic genome browser illustrating gene association chromosomal regions; 3) Real-time validation/replication of candidate or putative genes suggested from other sources, limiting Bonferroni genome-wide association study (GWAS) penalties; 4) Open data release and sharing by eliminating privacy constraints (The National Human Genome Research Institute (NHGRI) Institutional Review Board (IRB), informed consent, The Health Insurance Portability and Accountability Act (HIPAA) of 1996 etc.) on unabridged results, which allows for open access comparative and meta-analysis.ConclusionsGWATCH is suitable for both GWAS and whole genome sequence association datasets. We illustrate the utility of GWATCH with three large genome-wide association studies for HIV-AIDS resistance genes screened in large multicenter cohorts; however, association datasets from any study can be uploaded and analyzed by GWATCH.

As genome wide association studies plus whole genome sequence analyses for complex human disease determinants are expanding, it seems useful to develop strategies to facilitate large data sharing, rapid replication and validation of provocative statistical associations that straddle the threshold for genome wide significance. At this conference, we shall announce GWATCH, (Genome Wide Association Tracks Chromosome Highway) a web based data release platform that can freely display and inspect unabridged genome tracked association data without compromising privacy or Informed Consent constrictions, allowing for rapid discovery and replication opportunities. We illustrate the utility with HIV-AIDS resistance genes screened in combined large multicenter cohort studies GWAS (MACS, HGDS, MHGS, ALLIVE, LSOCA HOMER) developed and studied over the last decades.