Normalisation parameters (play with it to find a nice fit for the game)

Introns are the non-coding parts of the gene (represented as the holes), which we could classify in 5 different classes for the game:

small_intron is smaller than bps and normalized value is:units. With this type of intron we could say the avatar could easily jump.
medium_intron is smaller than bps and normalized value is:units. With this type of intron we could say there are 1, 2 splicies (rocks) that the avatar need to jump on top to traverse the holw
large_intron is smaller than bps and normalized value is:units. With this type of intron we could say that there is a spliceosome that moves
big_intron is smaller than bps and normalized value is:units. With this type of intron we could say that there is a spliceosome that moves and it is more complicated
huge_intron is equal or bigger than bps and normalized value is:units. With this type of intron there could be an SR protein before and the avatar would be propulsated (I think it is easy for the avatar)

Exons (includes stop_codon, snp, start_codon) are relatively smallers (average is 500bps) compared to the introns (10000bps) and a continous normalisation approach was adopted:

Division factor The length of the exons will be divided by this factor
Minimal unit: The exons will have in minimum this unit
Maximal unit: The exons will have in maximum this unit

Notes

Up / Down / Obstacles are not defined in this JSON, as agreed we leave that up to you to make sure the game is fun.
Intron are much bigger than exons in reality (if possible in the drawing of introns could be a wrapped RNA like in the picture to seem bigger and maybe thiner, to discuss...)

There is not a hole below the start, snp stop codon (it is a limitation of the library in use for the schema). It should be a walkable exon with different color: from exon to utr (untranslated region)
For SIB: Double Check aa length (does not seem correct for GJB2 counts 234aa but Ensembl counts 226aa)

Normalisation parameters (play with it to find a nice fit for the game)

Notes

Genes and corresponding JSON