If we have a clear profile of mutation, we will have to apply these filters on BiERapp to get directly the possible causal mutation. Sometimes we have several interesting profiles of mutations, not only one. For this case we should explore these different scenarios and decide the best prioritization strategy.

To know better this web tool, we propose you two groups of activities:

• In the part A of this activity, we would have to apply individual filters. This action give us information about the effect of each filter (maybe there are some filters more powerful than other). After each filtering, we have to clear the filter to apply the next one.
• In the part B of this exercise, we have a real selection where we combine several filters at the same time. It is interesting to know how the number of variants is reducing, when applying a progressive group of filters (without deleting the previous filter). We want to know the accumulative effect of several filters (all together).

1. Total number of variants without filters
2. Recessive heritage
3. Dominant heritage (father is affected).
4. “De novo” mutations.
5. For these regions: 1:3000-10000000,20:1000-200000000
6. For these genes related to Charcot-Marie-Tooth disease: PLEKHG5,PARK7,KIF1B,TARDBP,MFN2,YARS,GJB3,DNAJC6,LMNA,DCAF8
7. Is there any variant for this SNPId: rs3138150? Explore this variant and this gene, after clicking direct links to Ensembl website. We like this candidate and we want more detailed information about this change:
   • What do you think about the plot in “Overview”? You download this image as png format.
   • We would like an image of this change from “Genomic context”.
   • What frequencies are there for different EXAC populations? Please, you download this information in a csv file.
   • Why are there different functional effects in “Effect” for the same variant?
8. Description of variants. How many SNVs, INDELs, MNVs, SVs, CNVs?

1. We have several clues about our candidate variants. In addition of knowing the pattern of recessive heritage, we search variants with MAF < 0.1 (for all populations in 1000 Genomes phase 3) because it is a rare disease. Consequence type must be any option of “modifier” description.
   • How many variants do you have including both characteristics?
   • Download these final results in a csv file
2. We have several clues about our candidate variants. In addition of knowing the pattern of dominant heritage (father is affected), we search variants with MAF < 0.1 (for all populations in 1000 Genomes phase 3) because it is a rare disease. Consequence type must be any option of “High” description in “consequence type”.
   • How many variants do you have including both characteristics?
   • Download these final results in a csv file
3. This is a third scenario of interest:
   • Dominant heritage where mother is affected
   • Variants with MAF < 0.1 (for all populations in 1000 Genomes phase 3) because it is a rare disease.
   • Consequence type must be any option of “modifier” in “consequence type”.
     • How many variants do you have including both characteristics?
     • Download these final results in a csv file

Some of these solutions could be different when having updated databases

1. Candidate variants: 39999
2. Candidate variants: 1593
3. Candidate variants: 6265
4. Candidate variants: 88
5. Candidate variants: 1231
6. Candidate variants: 38
7. Candidate variants: 1
8. 36402 SNVs, 3580 INDELs, 13 MNVs, 4 SVs, 0 CNVs

1. Candidate variants: 1593→105→104
2. Candidate variants: 6265→1707→11
3. Candidate variants: 6119→1615→1611