Genetic Variant Analysis

Analyze and visualize genetic variants

Find, analyze, and visualize genetic variants, such as copy number variations (CNVs) and single nucleotide polymorphisms (SNPs).

Functions

`cghcbs`	Perform circular binary segmentation (CBS) on array-based comparative genomic hybridization (aCGH) data
`cghfreqplot`	Display frequency of DNA copy number alterations across multiple samples
`chromosomeplot`	Plot chromosome ideogram with G-banding pattern

`gcrma`	Perform GC Robust Multi-array Average (GCRMA) background adjustment, quantile normalization, and median-polish summarization on Affymetrix microarray probe-level data
`gcrmabackadj`	Perform GC Robust Multi-array Average (GCRMA) background adjustment on Affymetrix microarray probe-level data using sequence information

`mattest`	Two-sample t-test to evaluate differential expression of genes from two experimental conditions or phenotypes
`nbintest`	Unpaired hypothesis test for count data with small sample sizes
`mafdr`	Estimate positive false discovery rate for multiple hypothesis testing

`mavolcanoplot`	Create significance versus gene expression ratio (fold change) scatter plot of microarray data
`mairplot`	Create intensity versus ratio scatter plot of microarray data
`maboxplot`	Create box plot for microarray data
`maloglog`	Create loglog plot of microarray data
`mapcaplot`	Create Principal Component Analysis (PCA) plot of microarray data

`DataMatrix`	Data structure encapsulating data and metadata from microarray experiment
`NegativeBinomialTest`	Unpaired hypothesis test result

Detect DNA copy number alterations in genome-wide array-based comparative genomic hybridization (CGH) data.

Study DNA copy number variants by preprocessing and analyzing data from the Affymetrix® GeneChip® Human Mapping 100k array.