Cellular_preclustering

<p>The classic output from Schrodinger function</p>

Schrod_cells

<p>This method clusters mutations based on the probability that they are from the same 
distribution.
It first computes the zscore associated with a normalized number of alternative reads and depth.
The "normalized" number of reads is the number of alternative reads expected if the mutation was at a single 
copy in a diploid genome.</p>

Using HTS data, clusters mutations in order to recreate putative
clones from the data provided. It requires genotype at the location of the
variant as well as the depth of coverage and number of reads supporting the
mutation. Additional information may be provided, such as the contamination
in the tumor sample. This package also provides a function QuantumCat() which
simulates data obtained from tumor sequencing.

Paul Deveau

Cellular_preclustering: Preclustering method

Description

Usage

Arguments

Value