Data description




Working plan

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).



How many variants do you detect for each scenario?

A. Individual filters

  1. Total number of variants without filters
  2. Recessive heritage
  3. Dominant heritage (father is affected).
  4. For this region: 1:1000-50000
  5. For this gene: BRD9
  6. For these genes at the same time: BRD9,CDK11A,RET
  7. Description of variants. How many SNVs and INDELs can you search?
  8. Variants with MAF (Minimum Allelic Frequency) < 0.1 for all populations in 1000 Genomes phase 3
  9. Variants with MAF (Minimum Allelic Frequency) < 0.01 for all populations in 1000 Genomes phase 3
  10. Variants with MAF (Minimum Allelic Frequency) < 0.001 for all populations in 1000 Genomes phase 3


B. Progressive selection

  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 “synonymous variant”
    • 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 “synonymous variant”
    • How many variants do you have including both characteristics?
    • Download these final results in a csv file