knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) options(crayon.enabled=F)
CNAqc Input/Output
CNAqc requires in input
CNAqc uses chromosome coordinates the to map mutations to segments. The conversion of relative to absolute genome coordinates requires to fix a reference genome build; supported references are GRCh38/hg17 and hg19/GRCh37, but custom references can also be built.
The tool can elaborate a number of analysis to assess the consistency among mutations, CNAs and tumour purity (see Articles).
CNAqc can be used to:
The following concepts are used to develop CNAqc.
Expected VAF peaks for mutations mapped to diploid heterozygous and triploid clonal CNAs (at purity $\pi=1$).
Consider:
Since the proportion of all reads from the tumour is $\pi(n_A+n_B)$, and from the normal is $2(1-\pi)$. Then, muations present in $m$ copies of the tumour genome should peak at VAF value [ v_m(c) = \dfrac{m \pi c}{ 2 (1 - \pi) + \pi (n_A+n_B) } \, . ]
Consider a mixture of 2 subclones with segments $n_{A,1}:n_{B,1}$ and $n_{A,2}:n_{B,2}$, proportions $\rho_1$ and $\rho_2$ ($\rho_1+\rho_2=1$).
The expected peak for a shared mutation with multiplicity $m_1$/ $m_2$ in the first/ second subclone is [ v_{m_1,m_2} = \dfrac{ (m_1\rho_1 + m_2\rho_2) \pi } { 2 (1 - \pi) + \pi [(n_{A,1}+n_{B,1})\rho_1 + (n_{A,2}+n_{B,2})\rho_2] } \, . ]
The expected peak for a private mutation with multiplicity $m$ in subclone $i$ is [ v_{m_i} = \dfrac{ m\rho_i \pi } { 2 (1 - \pi) + \pi [(n_{A,1}+n_{B,1})\rho_1 + (n_{A,2}+n_{B,2})\rho_2] } \, . ]
Given VAF, tumour purity and CNAs, CCF values can be computed as
[ c = \dfrac{ v[ (n_a+n_B - 2)\pi + 2 ] } { m \pi } ]
Therefore the problem of computing CCFs is essentially linked to computing m
, mutation multiplicity. This type of computation can be done by "phasing" the VAFs against the multiplicity.
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