Genetic analysis of human disorders

1. Genetic analysis ofhuman disorders Tom Scerri Answers to Exercise 5

2. Exercise 5 • Results in the folder “answers”.

3. Exercise 5a: Results • Running Merlin with the command “--error” produces this output file: FAMILY PERSON MARKER RATIO 6631 311010_5 rs917235 0.0220 • This tells you there is one individual with one unlikely genotype, specifically for marker rs917235. For this genotype to be true, a double recombination event would have had to occurred which is unlikely given the flanking markers are physically close together on the chromosome.

4. Exercise 5b: Results • QTDT example output file 1: The following models will be evaluated... NULL MODEL Means = Mu Variances = Ve + Vg + Va FULL MODEL Means = Mu + X Variances = Ve + Vg + Va Testing trait: trait1 ============================================= Testing marker: rs1000585 --------------------------------------------- Allele df(0) -LnLk(0) df(X) -LnLk(X) ChiSq p 1 556 2262.93 555 2262.44 0.98 (560 probands) 2 556 2262.93 555 2262.44 0.98 (560 probands) Testing marker: rs917235 --------------------------------------------- Allele df(0) -LnLk(0) df(X) -LnLk(X) ChiSq p 1 545 2220.00 544 2219.05 1.90 (549 probands) 2 545 2220.00 544 2219.05 1.90 (549 probands) Testing marker: rs714939 --------------------------------------------- Allele df(0) -LnLk(0) df(X) -LnLk(X) ChiSq p 1 544 2213.57 543 2212.55 2.03 (548 probands) 2 544 2213.57 543 2212.55 2.03 (548 probands) This shows you the test that is being conducted - the X in the FULL model is the major gene effect. P-values would be in this column, but by default are absent if > 0.1

5. Exercise 5b: Results • QTDT example output file 2, the “regress.tbl” file: Trait: trait1 Marker: rs1000585 Allele: 1 ================================================================ Total Probands: 560 Family #1 Phenotypes - scores : 121.000 117.000 NULL HYPOTHESIS --------------- Family #1 var-covar matrix terms [3]...[[Ve]][[Vg]][[Va]] Family #1 regression matrix... [linear] = [2 x 1] Mu 661.11010_3 1.000 661.11010_4 1.000 Some useful information... df : 556 log(likelihood) : 2262.93 variances : 170.275 19.462 0.000 means : 115.145 FULL HYPOTHESIS --------------- Family #1 var-covar matrix terms [3]...[[Ve]][[Vg]][[Va]] Family #1 regression matrix... [linear] = [2 x 2] Mu X 661.11010_3 1.000 0.000 661.11010_4 1.000 0.000 Some useful information... df : 555 log(likelihood) : 2262.44 variances : 170.872 18.557 0.006 means : 114.902 0.864 This shows the derived values for the environmental, polygenic and major gene effects for each trait and each allele tested. Trait Allele Missing value for “null” hypothesis as is set to zero. Value present here in “full” hypothesis, and represents the effect size and trend for this allele

6. Exercise 5c: Results Columns: • Example qseq file: No sequence present because bad quality (“B”).

7. Exercise 5c: Results • Example fastq file: Unique identifier/name for each sequence read. Sequence The plus (+) symbol, plus any optional descriptions. The quality for the above sequence This information can be derived from the qseq file.

8. Exercise 5c: Results • After following all the commands, you should get something like this… …type “?” for help. Reference sequence Lots of short read sequences

9. Exercise 5c: Results …type “.” to toggle the sequences…

10. Exercise 5c: Results …type “c” to toggle the nucleotide colours…

11. Exercise 5c: Results …type “z” to toggle the quality score colours…

12. Exercise 5c: Results …type “q” to quit.