Manages microsatellite projects.  Creates 96-well maps,
genotyping submission forms, rerun management, and import into
statistical software.
Manages DNA fragment analysis projects.  Creates 96-well
maps, genotyping submission forms, rerun management, and import
to statistical software.

'Plot genome wide values for all chromosomes'
Plot values of markers(SNPs, expression, genes, RNA,...) for all chromosomes.

Models Dealing with Spatial Dependency in Genomic Data
c(person("Chris", "Wallace", email = "cew54@cam.ac.uk", role = c("aut", "cre")),
person("Oliver", "Burren", email = "ob219@cam.ac.uk", role = c("aut")))
Local structure in genomic data often induces dependence between observations taken at different genomic locations.  Ignoring this dependence leads to underestimation of the standard error of parameter estimates.  This package uses block bootstrapping to estimate asymptotically correct standard errors of parameters from any standard generalised linear model that may be fit by the glm() function.
Chris Wallace [aut, cre],
Oliver Burren [aut]

Circular Genomic Permutation using GWAS p-values of association
Circular genomic permutation approach uses GWAS results to
establish the significance of pathway/gene-set associations
whilst accounting for genomic structure. All SNPs in the GWAS
are placed in a 'circular genome' according to their location.
Then the complete set of SNP association p-values are permuted
by rotation with respect to the SNPs' genomic locations

Circular Genomic Permutation using Gwas p-Values of Association
Claudia P. Cabrera, Pau Navarro, Chris S.Haley
Circular genomic permutation approach uses GWAS results to establish the significance of pathway/gene-set associations whilst accounting for genomic structure. All SNPs in the GWAS are placed in a 'circular genome' according to their location. Then the complete set of SNP association p-values are permuted by rotation with respect to the SNPs' genomic locations. Two testing frameworks are available: permutations at the gene level, and permutations at the SNP level. The permutation at the gene level uses fisher's combination test to calculate a single gene p-value, followed by the hypergeometric test. The SNP count methodology maps each SNP to pathways/gene-sets and calculates the proportion of SNPs for the real and the permutated datasets above a pre-defined threshold. Genomicper requires a matrix of GWAS association p-values. The SNPs annotation and pathways annotations can be performed within the package or provided by the user.