results

SNPhood.o

Character(1). Name of analyses one wants to retrieve the results for. 
Currently supported are "allelicBias", "clustering", "genotype" and "samplesCorrelation".

type

Character. Default NULL. Which elements of the resulting list structure should be returned? 
If set to NULL, all elements will be returned. Otherwise, if names are provided, only the requested subset elements will be returned.
If type equals "allelicBias", valid values are "pValue", "confIntervalMin", "confIntervalMax", "fractionEstimate", "background", "FDR_results", and "parameters".
If type equals "clustering", valid values are the defined read groups in the object.
If type equals "genotype", valid values are "strongGenotypes", "weakGenotypes", and "invariantGenotypes".
If type equals "samplesCorrelation", valid values are "corTable", and "transl".

elements


Return the results of a particular analyis that is stored in the <code>SNPhood</code> object.


To date, thousands of single nucleotide polymorphisms (SNPs) have
been found to be associated with complex traits and diseases. However, the vast
majority of these disease-associated SNPs lie in the non-coding part of the
genome, and are likely to affect regulatory elements, such as enhancers and
promoters, rather than function of a protein. Thus, to understand the molecular
mechanisms underlying genetic traits and diseases, it becomes increasingly
important to study the effect of a SNP on nearby molecular traits such as
chromatin environment or transcription factor (TF) binding. Towards this aim, we
developed SNPhood, a user-friendly *Bioconductor* R package to investigate and
visualize the local neighborhood of a set of SNPs of interest for NGS data such
as chromatin marks or transcription factor binding sites from ChIP-Seq or RNA-
Seq experiments. SNPhood comprises a set of easy-to-use functions to extract,
normalize and summarize reads for a genomic region, perform various data quality
checks, normalize read counts using additional input files, and to cluster
and visualize the regions according to the binding pattern. The regions around
each SNP can be binned in a user-defined fashion to allow for analysis of very
broad patterns as well as a detailed investigation of specific binding shapes.
Furthermore, SNPhood supports the integration with genotype information to
investigate and visualize genotype-specific binding patterns. Finally, SNPhood
can be employed for determining, investigating, and visualizing allele-specific
binding patterns around the SNPs of interest.

results: Get results of various analyses performed with a `SNPhood` object.

Description

Usage

Arguments

Value

Examples