User:Timothee Flutre/Notebook/Postdoc/2011/11/16

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(try pkg snpStats)
(Entry title: change page into "about statistical modeling")
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==Entry title==
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==About statistical modeling==
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* try the R/Bioconductor package [http://www.bioconductor.org/packages/devel/bioc/html/snpStats.html snpStats]:
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library(snpStats)
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tmp <- matrix(c(1,3,2,1,3,0,1,3,0,1), ncol=2, dimnames=list(paste("snp", 1:5, sep=""), paste("ind", 1:2, sep="")))
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tmp
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tmp2 <- new("SnpMatrix", t(tmp))
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tmp2
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summary(tmp2)
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print(as(t(tmp2), 'character'))
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print(as(t(tmp2), 'numeric'))
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Unfortunately, it doesn't seem possible to convert a matrix of characters into SnpMatrix, assuming 1=AA, 2=AB, 3=BB and 0=NC:
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tmp <- matrix(c("A/A","B/B","A/B","A/A","B/B","","A/A","B/B","","A/A"), ncol=2, dimnames=list(paste("snp", 1:5, sep=""), paste("ind", 1:2, sep="")))
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tmp
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tmp2 <- new("SnpMatrix", t(tmp))
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Thus, in the case where one has a matrix of genotypes obtained by Illumina (whether we have AA or A/A), we need to convert it first to the 1/2/3/0 encoding:
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tmp <- gsub("A/A", 1, tmp)
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tmp <- gsub("A/B", 2, tmp)
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tmp <- gsub("B/B", 3, tmp)
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tmp <- gsub("^$", 0, tmp)
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tmp <- matrix(as.numeric(tmp), ncol=ncol(tmp), dimnames=list(rownames(tmp), colnames(tmp)))
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tmp
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tmp2 <- new("SnpMatrix", t(tmp))
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tmp2
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summary(tmp2)
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Then, one can easily look at summary statistics, eg. the histogram of minor allele frequencies, of z-score for HWE, etc, and filter data accordingly:
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hist(col.summary(tmp2)$MAF)
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hist(col.summary(tmp2)$z.HWE)
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* visualizing, plotting:
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** "Visualizing uncertainty about the future" by Spiegelhalter, et al. (Science 2011, [http://dx.doi.org/10.1126/science.1191181 DOI])
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** "Let's practice what we preach: turning tables into graphs": Gelman et al (The American Statistician 2002, [http://dx.doi.org/10.1198/000313002317572790 DOI])
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Revision as of 21:34, 27 November 2013

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About statistical modeling

  • visualizing, plotting:
    • "Visualizing uncertainty about the future" by Spiegelhalter, et al. (Science 2011, DOI)
    • "Let's practice what we preach: turning tables into graphs": Gelman et al (The American Statistician 2002, DOI)


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