ld.snp {chopsticks} | R Documentation

## Function to calculate pairwise D', $r^2$

### Description

`ld.snp` takes an object of `snp.matrix` class and suitable range and depth and calculation the pairwise D', $r^2$, LOD and return the result as a `snp.dprime` object.

### Usage

    ld.snp(snpdata, depth = 100, start = 1, end = dim(snpdata)[2], signed.r=FALSE)

### Arguments

`snpdata` | An object of `snp.matrix` class with M samples of N snps
`depth` | The depth or lag of pair-wise calculation. Should be between 1 and N-1; default 100. Using 0 (an invalid value) is the same as picking the maximum
`start` | The index of the start of the range of interest. Should be between 1 and (N-1); default 1
`end` | The index of the end of the range of interest. Should be between 2 and N. default N.
`signed.r` | Boolean for whether to returned signed $r$ values instead of $r^2$

### Details

The cubic equation and quadratic equation solver code is borrowed from GSL (GNU Scientific Library).

### Value

return a `snp.dprime` object, which is a list of 3 named matrices `dprime`, `rsq2` (or `r` depending on the input), `lod`, and an attribute `snp.names` for the list of snps involved. (Note that if $x$ snps are involved, the row numbers of the 3 matrices are $(x-1)$). Only one of `rsq2` or `r` is present.

`dprime` | D'
`rsq2` | $r^2$
`r` | signed $r$
`lod` | Log of Odd's

All the matrices are defined such that the ($n, m$)th entry is the pair-wise value between the ($n$)th snp and the $(n+m)$th snp. Hence the lower right triangles are always filled with zeros. (See example section for the actual layout)

Invalid values are represented by an out-of-range value - currently we use -1 for D', $r^2$ (both of which are between 0 and 1), and -2 for $r$ (valid values are between -1 and +1). lod is set to zero in most of these invalid cases. (lod can be any value so it is not indicative).

### Note

The output `snp.dprime` object is suitable for input to `plot.snp.dprime` for drawing.

The speed of “ld.snp” LD calculation, on a single-processor opteron 2.2GHz box:

unsigned $r^2$, 13191 snps, depth 100 = 36.4 s (~ 1.3 mil pairs)

signed r , 13191 snps, depth 100 = 40.94s (~ 1.3 mil pairs)

signed r , 13191 snps, depth 1500 = 582s (~ 18.5 mil pairs)

For depth=1500, it uses 500MB just for the three matrices. So I actually cannot do the full depth at ~13,000; full depth should be under 50 minutes for 87 mil pairs, even in the signed-r version.

The LD code can be ran outside of R - mainly for debugging:

        gcc -DWITHOUT_R -o /tmp/hello pairwise_linkage.c solve_cubic.c \
           solve_quadratic.c -lm

When used in this form, it takes 9 numbers:

      $/tmp/hello 4 0 0 0 30 0 0 0 23
      case 3               <- internal code for which cases it falls in
      root count 1         <- how many roots
      trying 1.000000
      p = 1.000000
      4      0       0       6.333333        0.000000        0.000000
      0      30      0       0.000000        25.333333       0.000000
      0      0       23      0.000000        0.000000        25.333333
      57 8 38.000000 38 38
      8 0 0 46 30, 38 38 76 76
      0.333333 0.000000 0.000000 0.666667
      d' = 1.000000 , r2 = 1.000000, lod= 22.482643

### Author(s)

Hin-Tak Leung htl10@users.sourceforge.net

### References

Clayton, D.G. and Leung, Hin-Tak (2007) An R package for analysis of whole-genome association studies. Human Heredity 64:45-51.
GSL (GNU Scientific Library) http://www.gnu.org/software/gsl/

### See Also

`snp.dprime-class`, `plot.snp.dprime`, `ld.with`

### Examples

    # LD stats between 500 SNPs at a depth of 50
    data(testdata)
    ldinfo <- ld.snp(Autosomes, start=1, end=500, depth=50)

[Package chopsticks version 1.60.0 Index]