bf2Vcf

array of Bayes factors from <code><a rd-options="" href="/link/bbb?package=deepSNV&version=1.18.3" data-mini-rdoc="deepSNV::bbb">bbb</a></code>.

array of counts from <code><a rd-options="" href="/link/loadAllData?package=deepSNV&version=1.18.3" data-mini-rdoc="deepSNV::loadAllData">loadAllData</a></code>.

counts

<code><a rd-options="" href="/link/GRanges?package=deepSNV&version=1.18.3" data-mini-rdoc="deepSNV::GRanges">GRanges</a></code> with the regions corresponding to counts and BF.

regions

samples

Cutoff for the posterior artifact probability below which a variant is considered to be true (default = 0.05)

cutoff

matrix of prior probabilities for finding a true call, typically from <code><a rd-options="" href="/link/makePrior?package=deepSNV&version=1.18.3" data-mini-rdoc="deepSNV::makePrior">makePrior</a></code>. Alternatively a single fixed number.

prior

boolean flag, if TRUE compute a large VCF with as many genotype columns as samples. Default TRUE. Otherwise use duplicate rows and only one genotype column. The sample is then provided by the info:PD field. Can be inefficient for large sample sizes.

mvcf

Optional matrix of error rates, otherwise recomputed from counts.

Optional matrix of relative frequencies, otherwise recomputed from counts.


This function thresholds the Bayes factors computed by the shearwater algorithm and creates a <code><a rd-options="" href="/link/VCF?package=deepSNV&version=1.18.3" data-mini-rdoc="deepSNV::VCF">VCF</a></code> object as output.


This package provides provides quantitative variant callers for
detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing
experiments. The deepSNV algorithm is used for a comparative setup with a
control experiment of the same loci and uses a beta-binomial model and a
likelihood ratio test to discriminate sequencing errors and subclonal SNVs.
The shearwater algorithm computes a Bayes classifier based on a
beta-binomial model for variant calling with multiple samples for
precisely estimating model parameters such as local error rates and
dispersion and prior knowledge, e.g. from variation data bases such as
COSMIC.

Moritz Gerstung

deepSNV

Detection of subclonal SNVs in deep sequencing data.

bf2Vcf function

array of Bayes factors from <code><a href="bbb" rd-options="">bbb</a></code>.

array of counts from <code><a href="loadAllData" rd-options="">loadAllData</a></code>.

<code><a href="GRanges" rd-options="">GRanges</a></code> with the regions corresponding to counts and BF.

matrix of prior probabilities for finding a true call, typically from <code><a href="makePrior" rd-options="">makePrior</a></code>. Alternatively a single fixed number.

This function thresholds the Bayes factors computed by the shearwater algorithm and creates a <code><a href="VCF" rd-options="">VCF</a></code> object as output.

Function to create a <code><a href="VCF" rd-options="">VCF</a></code> object with variant calls from an array of Bayes factors.

Function to create a <code><a rd-options="" href="/link/VCF?package=deepSNV&version=1.18.3" data-mini-rdoc="deepSNV::VCF">VCF</a></code> object with variant calls from an array of Bayes factors.

bf2Vcf: Function to create a `VCF` object with variant calls from an array of Bayes factors.

Description

Usage

Arguments

Value