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Last data update: 2014.03.03

R: collect genewise best scoring eQTL

best.cis.eQTLs

R Documentation

collect genewise best scoring eQTL

Description

collect genewise best scoring eQTL

Usage

best.cis.eQTLs(smpack = "GGdata", rhs = ~1, 
  folderstem = "cisScratch", radius = 50000, 
  shortfac = 100,
  chrnames = as.character(1:22), 
  smchrpref = "", gchrpref = "", schrpref = "ch", 
  geneApply = lapply, geneannopk = "illuminaHumanv1.db", 
  snpannopk = snplocsDefault(),
  smFilter = function(x) nsFilter(MAFfilter(x, lower = 0.05), var.cutoff = 0.97), nperm = 2,
  useME=FALSE, excludeRadius=NULL, exFilter=function(x)x, 
  keepMapCache=FALSE, getDFFITS=FALSE, SSgen = GGBase::getSS)

All.cis.eQTLs(maxfdr = 0.05, inbestcis = NULL, smpack = "GGdata", 
    rhs = ~1, folderstem = "cisScratch", radius = 50000, 
    shortfac = 100,
    chrnames = as.character(1:22), 
    smchrpref = "", gchrpref = "", schrpref = "ch", 
    geneApply = lapply, geneannopk = "illuminaHumanv1.db", 
    snpannopk = snplocsDefault(),
    smFilter4cis = function(x) nsFilter(MAFfilter(clipPCs(x, 
        1:10), lower = 0.05), var.cutoff = 0.85), 
    smFilter4all = function(x) MAFfilter(clipPCs(x, 
        1:10), lower = 0.05), 
    nperm = 2, excludeRadius=NULL, exFilter=function(x)x,
    SSgen = GGBase::getSS)

meta.best.cis.eQTLs(smpackvec = c("GGdata", "hmyriB36"), rhslist = list(~1, 
    ~1), folderstem = "cisScratch", radius = 50000, shortfac = 100, 
    chrnames = as.character(1:22), smchrpref = "", gchrpref = "", 
    schrpref = "ch", geneApply = lapply, geneannopk = "illuminaHumanv1.db", 
    snpannopk = snplocsDefault(), SMFilterList = list( 
   function(x) nsFilter(MAFfilter(x, lower = 0.05), var.cutoff = 0.97), 
   function(x) nsFilter(MAFfilter(x, lower = 0.05), var.cutoff = 0.97) ),
    exFilterList = list(function(x)x, function(x)x),
   nperm = 2, excludeRadius=NULL) 

meta.All.cis.eQTLs(minchisq, smpackvec = c("GGdata", "hmyriB36"),
  rhslist = list(~1, ~1), folderstem = "cisScratch",
  radius = 50000, shortfac=100, chrnames = as.character(1:22), smchrpref = "",
  gchrpref = "", schrpref = "ch", geneApply = lapply,
  geneannopk = "illuminaHumanv1.db",
  snpannopk = snplocsDefault(),
  SMFilterList = list(function(x) nsFilter(MAFfilter(x,
                 lower = 0.05), var.cutoff = 0.97), function(x)
                 nsFilter(MAFfilter(x, lower = 0.05), var.cutoff =
                 0.97)), 
  exFilterList = list(function(x) x, function(x)
                 x),
  nperm = 2)


chromsUsed(x)

fdr(x)

fullreport(x, type, ...)

getAll(x)

getBest(x)

getCall(x)

Arguments

`smpack`	character string naming a package to which `getSS` can be applied to extract `smlSet-class` instances
`smpackvec`	vector of character strings naming packages that can be used as `smpack` values in a series of `best.cis.eQTLs` calls, one per population for meta-analysis
`rhs`	R model formula, with no dependent variable, that will be used with `snp.rhs.tests` to adjust GWAS tests for each expression probe
`rhslist`	a list of model formulae to be used as `rhs` in a series of `best.cis.eQTLs` calls, one per population for meta-analysis
`folderstem`	prefix of the folder name to be used to hold ff archives of test results
`radius`	coding extent of each gene will be extended in both directions by `radius` bases, and only SNP within these limits are used for selecting best hits for the gene
`shortfac`	a numeric that will scale up the chi-squared statistic before it is converted to short integer for storage in ff array
`chrnames`	character vector of chromosome identifiers, to be manipulated for certain query resolutions by the following parameters
`smchrpref`	prefix to convert `chrnames` into appropriate tokens for indexing `smlSet` elements as collected from the package named by parameter `smpack`
`gchrpref`	prefix to convert `chrnames` into appropriate tokens for obtaining gene metadata; in future this may need to be a string transformation function
`schrpref`	prefix to convert `chrnames` into appropriate tokens for use with `snplocs` for the SNP location information package identified in `snpannopack` parameter below
`geneApply`	an lapply like function, defaults to `lapply`
`geneannopk`	character string, name of a .db annotation package that annotates probe identifiers; or see `getCisMap` for additional possibilities concerning FDb. complex token values for newer annotation formats
`snpannopk`	character string, name of SNPlocs.Hsapiens.dbSNP.* package for obtaining; global function snplocsDefault() can be used to get a nominally current package name
`smFilter`	function accepting and returning an `smlSet-class` instance
`SMFilterList`	list of functions, one element per smlSet package used in meta analysis, accepting and returning an `smlSet-class` instance
`minchisq`	threshold on test statistic value that must be met to include records on SNPs in the All.cis.eQTLs report
`nperm`	number of permutations to be used for plug-in FDR computation
`useME`	logical; if TRUE, use the rudimentary interface to the MatrixEQTL package from A. Shabalin on CRAN
`maxfdr`	Used in `All.cis.eQTLs`. The process of identifying “best” cis eQTL per probe leads to a probe-specific FDR. In `All.cis.eQTLs` we enumerate all probes and all SNP with FDR at most `maxfdr`, not just the best scoring SNP per probe.
`inbestcis`	Used in `All.cis.eQTLs`. An instance of `mcwBestCis` that can be used to speed up the extraction of All.cis eQTL.
`smFilter4cis`	Used in `All.cis.eQTLs`. A function accepting and returning an smlSet instance. When `inbestcis` parameter is NULL, this filter will be used for identifying the best SNP per probe.
`smFilter4all`	Used in `All.cis.eQTLs`. A function accepting and returning an smlSet instance. This filter will be used for identifying the best SNP per probe. This filter should not affect the number of probes.
`x`	instance of `mcwBestCis`
`type`	character, either 'data.frame' or 'GRanges'
`excludeRadius`	numeric, defaulting to NULL; if non-null, defines radius around gene region that is excluded for cis SNP scoring; must be less than radius
`keepMapCache`	logical, if TRUE, returned `mcwBestCis` object will include an environment loaded with chromosome-specific lists of maps from genes to cis SNP names; if FALSE, the mapCache environment returned will be empty – NB, this feature has been found to add too much volume to returned objects and is suspended...
`exFilter`	this function is passed to `getSS`; see Details
`exFilterList`	for metaanalytic applications, a list of functions in correspondence with the elements of `smpackvec` to be passed to `getSS`; see Details
`getDFFITS`	logical; a component storing max DFFITS value for each gene will be retained if this argument TRUE
`...`	not used
`SSgen`	function to be used to create smlSet instance for testing – in general, GGBase::getSS has been used to pull the ExpressionSet and SnpMatrix data from a named package, but in some cases a specialize task is needed to create the desired smlSet. Whatever is passed to SSgen must return an smlSet instance.

Details

geneApply can be set to parallel::mclapply, for example, in a multicore context.

mcwBestCis stands for 'multi-chromosome-wide best cis' eQTL report container.

It is possible that the filtering processes should be broken into genotype filtering and expression probe filtering.

fdr(x) will return a numeric vector of plug-in FDR estimates corresponding to probe:association tests as ordered in the fullreport of a *Cis container. More metadata should be attached to the output of this function.

exFilter may seem redundant with smFilter, but its existence allows simpler management of multitissue expression archives (which may have several records per individual) with germ line genotype data (which will have only one record per individual). In this setting, use exFilter to select records for the tissue of interest; this will occur early in the smlSet generation process.

Value

an instance of mcwBestCis

Author(s)

VJ Carey <stvjc@channing.harvard.edu>

Examples

getClass("mcwBestCis")
## Not run: 
best.cis.eQTLs(chrnames="20")

## End(Not run)

Results


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> library(GGtools)
Loading required package: GGBase
Loading required package: snpStats
Loading required package: survival
Loading required package: Matrix
Loading required package: data.table
Loading required package: parallel
Loading required package: Homo.sapiens
Loading required package: AnnotationDbi
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Loading required package: Biobase
Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Loading required package: IRanges
Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following objects are masked from 'package:Matrix':

    colMeans, colSums, expand, rowMeans, rowSums

The following objects are masked from 'package:base':

    colMeans, colSums, expand.grid, rowMeans, rowSums


Attaching package: 'IRanges'

The following object is masked from 'package:data.table':

    shift

Loading required package: OrganismDbi
Loading required package: GenomicFeatures
Loading required package: GenomeInfoDb
Loading required package: GenomicRanges
Loading required package: GO.db

Loading required package: org.Hs.eg.db

Loading required package: TxDb.Hsapiens.UCSC.hg19.knownGene

Attaching package: 'GGtools'

The following object is masked from 'package:stats':

    getCall

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/GGtools/best.cis.eQTLs.Rd_%03d_medium.png", width=480, height=480)
> ### Name: best.cis.eQTLs
> ### Title: collect genewise best scoring eQTL
> ### Aliases: best.cis.eQTLs meta.best.cis.eQTLs meta.All.cis.eQTLs
> ###   All.cis.eQTLs mcwBestCis-class allSigCis-class show,allSigCis-method
> ###   show,mcwBestCis-method show,cwBestCis-method show,allCigCis-method
> ###   chromsUsed fdr chromsUsed,mcwBestCis-method fullreport
> ###   fullreport,mcwBestCis,missing-method
> ###   fullreport,mcwBestCis,character-method getAll getBest getCall
> ### Keywords: models
> 
> ### ** Examples
> 
> getClass("mcwBestCis")
Class "mcwBestCis" [package "GGtools"]

Slots:
                                                                              
Name:      scoregr     allperm       extra   chromUsed     theCall    smFilter
Class:     GRanges     numeric         ANY         ANY        call    function
                                          
Name:        nperm   globalMap   testCount
Class:     numeric environment     numeric
> ## Not run: 
> ##D best.cis.eQTLs(chrnames="20")
> ## End(Not run)
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>