read.HapMap.data {chopsticks} | R Documentation

## function to import HapMap genotype data as snp.matrix

### Description

Given a URL for HapMap genotype data, `read.HapMap.data`, download and convert the genotype data into a `snp.matrix` class object, and saving snp support infomation into an associated data.frame.

### Usage

    read.HapMap.data(url, verbose=FALSE, save=NULL, ...)

### Arguments

`url` | URL for HapMap data. Web data is to be specified with prefix "http://", ftp data with prefix "ftp://", and local file as "file://"
`verbose` | Where the dnSNPalleles annotation is ambiguous, output more details information about how/why assignment is made. See Notes below.
`save` | filename to save the download - if unspecified, a temporary file will be created but removed afterwards.
`...` | Place-holder for further switches - currently ignored.

### Details

During the conversion, if the dbSNPAlleles entry is exactly of the form "X/Y", where X, Y = A or C or G or T, then it is used directly for assigning allele 1 and allele 2.

However, about 1 in 1000 entries are more complicated e.g. may involving deletion, e.g. "-/A/G" or "-/A/AGT/G/T". Some heuristics are used in such cases, in which the observed genotypes in the specific snp of the current batch are examined in two passes. The first time to see which bases are present, excluding "N".

If more than 2 bases are observed in the batch specified in the url, the routine aborts, but so far this possibility has not arisen in tests. If there is exactly two, then allele 1 and 2 are assigned in alphabatical order (dbSNPAlleles entries seems to be always in dictionary order, so the assignment made should agree with a shorten version of the dbSNPAlleles entry). Likewise, if only "A" or "T" is observed, then we know automatically it is the first (assigned as "A/.") or the last allele (assigned as "./T") of a hypothetical pair, without looking at the dbSNPAlleles entry. For other observed cases of 1 base, the routine goes further and look at the dnSNPAlleles entry and see if it begins with "-/X/" or ends with "/X", as a single base, and compare it with the single base observed to see if it should be allele 1 (same as the beginning, or different from the end) and allele 2 (same as the end, or different from the beginning). If no decision can be made for a particular snp entry, the routine aborts with an appropriate message. (For zero observed bases, assignment is "./.", and of course, all observed genotypes of that snp are therefore converted to the equivalent of NA.)

(This heuristics does not cover all grounds, but practically it seems to work. See Notes below.)

### Value

Returns a list containing these two items when successful, otherwise returns NULL:

`snp.data` | A `snp.matrix-class` object containing the snp data
`snp.support` | A data.frame, containing the `dbSNPalleles`, `Chromosome`, `Position`, `Strand` entries from the hapmap genotype file, together with the actual `Assignment` used for allele 1 and allele 2 during the conversion (See Details above and Note below).

### Note

Using both "file://" for `url` and `save` duplicates the file. (i.e. by default, the routine make a copy of the url in any case, but tidy up afterwards if run without `save`).

Sometimes the assignment may not be unique e.g. dnSNPAlleles entry "A/C/T" and only "C" is observed - this can be assigned "A/C" or "C/T". (currently it does the former). One needs to be especially careful when joining two sets of snp data and it is imperative to compare the assigment supplementary data to see they are compatible. (e.g. for an "A/C/T" entry, one data set may have "C" only and thus have assignment "A/C" and have all of it assigned Allele 2 homozygotes, whereas another data set contains both "C" and "T" and thus the first set needs to be modified before joining).

A typical run, chromosome 1 for CEU, contains about ~400,000 snps and ~100 samples, and the snp.matrix object is about ~60MB (40 million bytes for snps plus overhead) and similiar for the support data (i.e. ~ 2x), takes about 30 seconds, and at peak memory usage requires ~ 4x . The actual download is ~20MB, which is compressed from ~200MB.

### Author(s)

Hin-Tak Leung htl10@users.sourceforge.net

### References

http://www.hapmap.org/genotypes

### See Also

`snp.matrix-class`

### Examples

    ## Not run:

    ## ** Please be aware that the HapMap project generates new builds from
    ## ** time to time and the build number in the URL changes.

    > library(snpMatrix)
    > testurl <- paste0("http://www.hapmap.org/genotypes/latest/fwd_strand/",
                        "non-redundant/genotypes_chr1_CEU_r21_nr_fwd.txt.gz")
    > result1 <- read.HapMap.data(testurl)
    > sum1 <- summary(result1$snp.data)

    > head(sum1[is.finite(sum1$z.HWE),], n=10)
               Calls Call.rate         MAF      P.AA       P.AB      P.BB      z.HWE
    rs1933024     87 0.9666667 0.005747126 0.0000000 0.01149425 0.9885057 0.05391549
    rs11497407    89 0.9888889 0.005617978 0.0000000 0.01123596 0.9887640 0.05329933
    rs12565286    88 0.9777778 0.056818182 0.0000000 0.11363636 0.8863636 0.56511033
    rs11804171    83 0.9222222 0.030120482 0.0000000 0.06024096 0.9397590 0.28293272
    rs2977656     90 1.0000000 0.005555556 0.9888889 0.01111111 0.0000000 0.05299907
    rs12138618    89 0.9888889 0.050561798 0.0000000 0.10112360 0.8988764 0.50240136
    rs3094315     88 0.9777778 0.136363636 0.7272727 0.27272727 0.0000000 1.48118392
    rs17160906    89 0.9888889 0.106741573 0.0000000 0.21348315 0.7865169 1.12733108
    rs2519016     85 0.9444444 0.047058824 0.0000000 0.09411765 0.9058824 0.45528615
    rs12562034    90 1.0000000 0.088888889 0.0000000 0.17777778 0.8222222 0.92554468

    ## ** Please be aware that the HapMap project generates new builds from
    ## ** to time and the build number in the URL changes.

    ## This URL is broken up into two to fit the width of
    ## the paper. There is no need in actual usage:
    > testurl2 <- paste0("http://www.hapmap.org/genotypes/latest/",
             "fwd_strand/non-redundant/genotypes_chr1_JPT_r21_nr_fwd.txt.gz")
    > result2 <- read.HapMap.data(testurl2)

    > head(result2$snp.support)
               dbSNPalleles Assignment Chromosome Position Strand
    rs10399749          C/T        C/T       chr1    45162      +
    rs2949420           A/T        A/T       chr1    45257      +
    rs4030303           A/G        A/G       chr1    72434      +
    rs4030300           A/C        A/C       chr1    72515      +
    rs3855952           A/G        A/G       chr1    77689      +
    rs940550            C/T        C/T       chr1    78032      +

    ## End(Not run)

[Package chopsticks version 1.48.0 Index]