dupGet {rCNV}

Detect deviants from SNPs; classify SNPs

Description

Detect deviant SNPs using excess of heterozygotes (alleles that do not follow HWE) and allelic-ratio deviations (alleles with ratios that do not follow a normal Z-score or chi-square distribution). See details.

Usage

dupGet(
  data,
  test = c("z.het", "z.05", "z.all", "chi.het", "chi.05", "chi.all"),
  intersection = FALSE,
  method = c("fisher", "chi.sq"),
  plot = TRUE,
  verbose = TRUE,
  ...
)

Arguments

data

data frame of the output of allele.info

test

character. type of test to be used for significance. See details

intersection

logical, whether to use the intersection of the methods specified in test (if more than one)

method

character. method for testing excess of heterozygotes. Fisher exact test (fisher) or Chi-square test (chi.sq)

plot

logical. whether to plot the detected singlets and duplicates on allele ratio vs. proportion of heterozygotes plot.

verbose

logical. show progress

...

additional parameters passed on to plot

Details

SNP deviants are detected with both excess of heterozygosity according to HWE and deviant SNPs where depth values fall outside of the normal distribution are detected using the following methods:

• Z-score test Z_{x} = \sum_{i=1}^{n} Z_{i}; Z_{i} = \frac{\left ( (N_{i}\times p)- N_{Ai} \right )}{\sqrt{N_{i}\times p(1-p)}}

• chi-square test X_{x}^{2} = \sum_{i-1}^{n} X_{i}^{2}; X_{i}^{2} = (\frac{(N_{i}\times p - N_{Ai})^2}{N_{i}\times p} + \frac{(N_{i}\times (1 - p)- (N_{i} - N_{Ai}))^2}{N_{i}\times (1-p)})

See references for more details on the methods

Users can pick among Z-score for heterozygotes (z.het, chi.het), all allele combinations (z.all, chi.all) and the assumption of no probe bias p=0.5 (z.05, chi.05)

Value

Returns a data frame of snps/alleles with their duplication status

Author(s)

Piyal Karunarathne

Examples

## Not run: data(alleleINF)
DD<-dupGet(alleleINF)
## End(Not run)