Package: SNPhood
Title: SNPhood: Investigate, quantify and visualise the epigenomic
        neighbourhood of SNPs using NGS data
Version: 1.4.1
Authors@R: c(person("Christian", "Arnold", email =
        "christian.arnold@embl.de", role = c("cre","aut")),
        person("Pooja", "Bhat", email = "pooja.bhat@embl.de", role =
        "aut"), person("Judith", "Zaugg", email =
        "judith.zaugg@embl.de", role = "aut"))
Author: Christian Arnold [aut, cre], Pooja Bhat [aut], Judith Zaugg
    [aut]
Maintainer: Christian Arnold <christian.arnold@embl.de>
Description: 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.
Imports: DESeq2, cluster, ggplot2, lattice, GenomeInfoDb, BiocParallel,
        VariantAnnotation, BiocGenerics, IRanges, methods,
        SummarizedExperiment, RColorBrewer, Biostrings,
        grDevices,gridExtra,stats,grid,utils, graphics, reshape2,
        scales, S4Vectors
Depends: R (>= 3.2), GenomicRanges, Rsamtools, data.table, checkmate
Suggests: BiocStyle, knitr, rmarkdown, SNPhoodData, corrplot, pryr
VignetteBuilder: knitr
biocViews: Software
License: LGPL (>= 3)
LazyData: true
BugReports: christian.arnold@embl.de
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-11-10 01:22:51 UTC; biocbuild
Built: R 3.3.1; ; 2016-11-10 05:49:31 UTC; windows
