HIVmix

trueSNVs


Two .bam alignments as example data sets are downloaded remotely via http. Sequenced were a 1,512 nt fragment of the HIV genome and a mixture (90% + 10%) with another variants.
The two sequences were confirmed by Sanger sequencing and stored in the table trueSNVs.


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.

trueSNVs function

Two .bam alignments as example data sets are downloaded remotely via http. Sequenced were a 1,512 nt fragment of the HIV genome and a mixture (90% + 10%) with another variants.
The two sequences were confirmed by Sanger sequencing and stored in the table trueSNVs.

trueSNVs: Example .bam data and true SNVs.

Description

Arguments

Examples