CNV identification software tools | Genomic array data analysis
Copy number variants (CNVs) create a major source of variation among individuals and populations. Array-based comparative genomic hybridisation (aCGH) is a powerful method used to detect and compare the copy numbers of DNA sequences at high resolution along the genome.
Detects copy number variations (CNVs) with high resolution. PennCNV is an integrated hidden Markov model (HMM) method that incorporates the population allele frequency for each single nucleotide polymorphism (SNP) and the distance between adjacent SNPs. This application was developed specifically for data generated on the Illumina Infinium platform, but it can be extended to other similar SNP genotyping platforms.
A package for the automatic detection of breakpoints from array CGH profile, and the assignment of a status to each chromosomal region. The breakpoint detection step of GLAD is based on the Adaptive Weights Smoothing (AWS) procedure and provides highly convincing results: our algorithm detects 97, 100 and 94% of breakpoints in simulated data, karyotyping results and manually analyzed profiles, respectively. The percentage of correctly assigned statuses ranges from 98.9 to 99.8% for simulated data and is 100% for karyotyping results.
A comprehensive analysis platform for the processing, analysis and visualization of structural variation based on sequencing data or genomic microarrays, enabling the rapid identification of disease loci or genes. Vivar allows you to scale your analysis with your work load over multiple (cloud) servers, has user access control to keep your data safe but still easy to share, and is easy expandable as analysis techniques advance.
Implements a multilevel model adjusting for batch effects and providing allele-specific estimates of copy number. The CRLMM algorithm estimates genotypes through a hierarchical model for the log ratios of A:B intensities that accounts for the dependency on intensity strength, batch effects, and the uncertainty of parameters estimated from the training step. For each platform design supported by CRLMM, we provide one annotation package that contains parameters estimated from the training data for every SNP-genotype combination.
A fully open-source set of tools to detect and report SNP genotypes, common Copy-Number Polymorphisms (CNPs), and novel, rare, or de novo CNVs in samples processed with the Affymetrix platform. While most of the components of the suite can be run individually (for instance, to only do SNP genotyping), the Birdsuite is especially intended for integrated analysis of SNPs and CNVs.
Allows the mapping of 500K Affymetrix products. BRLMM leans on an extension of the RLMM model combined with a Bayesian step dedicated to cluster centers and variances assessment. This application aims to improve the efficiency of call rates and had been designed to equalize the performance on both homozygous and heterozygous genotypes.