Trio datasets include genomic sequence data for a child, their mother, and their father (the "trio"). These data can be used to discover de novo mutation (and incidental genotyping errors).
STRkit includes a Mendelian inheritance (MI) analysis tool, under the sub-command strkit mi.
After genotyping the trio with strkit call, this command can be used to discover loci which:
- Do not respect exact MI
- Do not respect MI allowing for a ±1 repeat unit difference (Note: most true mutation occurs in 1-repeat-unit changes too! See Ellegren, 2004.)
- Do not respect MI under the 95% locus confidence intervals
- Look like de novo mutation at a read count distribution level, via a Mann-Whitney U test (with tie correction). The alternative hypothesis can be specified as either two-sided or looking for expansion in the offspring. The requirements for this test are invalidated in cases of mosaicism.
- Look like de novo mutation at a read count distribution level, via a chi-squared independence test, where the contingency table looks like the following:
| Read distribution \ Copy number | 11 | 12 | 13 |
|---|---|---|---|
| Parent reads (best peak fit) | 20 | 10 | 0 |
| Child reads | 2 | 20 | 10 |
At a trio level, the chi-squared test gives (optionally multiple testing-corrected) loci with a significant chance of containing a de novo mutation.
At a cohort level, multiple downstream analyses are possible from a collection of trio mutation analyses, such as:
- Case-control analysis looking for frequency of de novo mutations in specific loci
- Case-control analysis looking at the incidence rate of de novo mutation
Currently, tools to automatically perform these analyses are not available in STRkit.