OpenCGA provides a set of analysis o compute basic statistics given a variant dataset. In order to get richer statistics, the variant data should comprise annotation and pedigree (samples, phenotypes,...).
Variant stats are calculated for each variant, in addition, you may specify a set of samples (aka, cohort) in order to take into account only those samples.
Variant stats include the following values:
The total number of alleles (it does not include missing alleles)
The number of reference alleles found in this variant
The number of main alternate alleles found in this variant (it does not include secondary alternates)
The reference allele frequency, i.e., the quotient of the number of reference alleles divided by the total number of alleles.
The alternate allele frequency, i.e., the quotient of the number of alternate alleles divided by the total number of alleles.
The number of occurrences for each genotype
The frequency for each genotype
The number of missing alleles
The number of missing genotypes
The minor allele frequency (maf)
The minor genotype frequency (mgf)
The allele with the minor frequency
The genotype with the minor frequency
Pre-calculated stats are useful for filtering variants. This stats are intra-study, calculated within a given cohort.
Sample stats
Sample stats are calculated for each sample. It includes the following information:
The total number of variants.
The number of variants per chromosome.
The number of variants per consequence type.
The number of variants per biotype.
The number of variants per type (SNV, INDEL,...)
The number of variants per genotype.
The Ts/TV ratio or transition-to-transversion ratio.
A heterozigosity score.
A missingness score.
A list of the most affected genes.
Indel length
A list of HPO and genes for loss of function (LoF) variants.
A list of the most frequenct variant traits.
The number of mendelian error per type of error.
Relatedness scores (IBD/IBS scores).
Summary statistics are stored in a JSON format file.