Identifies single nucleotide variants in next-generation sequencing data by estimating their local false discovery rates. For more details, see Karimnezhad, A. and Perkins, T. J. (2024)
Empirical Bayes Single Nucleotide Variant Calling for Next Generation Sequencing Data
Identifies single nucleotide variants in next-generation sequencing data by estimating their local false discovery rates. For more details, see https://doi.org/10.1038/s41598-024-51958-z.
The package can be installed from the GitHub repository
devtools::install_github("empiricalbayes/SNVLFDR")
You can load SNVLFDR as follows:
library(SNVLFDR)
bam_input <- system.file("extdata", "bam_input.csv", package="SNVLFDR")
bedfile <- system.file("extdata", "regions.bed", package="SNVLFDR")
BQ.T=20
MQ.T=20
pi0.initial=0.95
AF.T=0.01
DP.T=10
LFDR.T=0.01
error=NULL
method='empirical'
epsilon=0.01
output=get_LFDRs(bam_input,bedfile,BQ.T,MQ.T,pi0.initial,AF.T,DP.T,LFDR.T,error,method,epsilon)
#Estimated LFDRs
output$estimated.LFDRs
#Estimated proportion on non-mutant sites
output$estimated.pi0
#Filtered Bam matrix that includes estimated LFDRs
output$filtered.bam
## How to run SNVLFDR to prioritize variants called by another variant caller
bam_path <- system.file("extdata", "bam_input.csv", package="SNVLFDR")
calls_path <- system.file("extdata", "calls.vcf", package="SNVLFDR")
output=get_LFDRs_given_caller(bam_input=bam_path,calls=calls_path,LFDR.T=0.01,error=NULL)
#Updated VCF file that includes estimated LFDRs
output$updated.vcf
Karimnezhad, A and Perkins, T.J. (2024) Empirical Bayes single nucleotide variant-calling for next-generation sequencing data. Scientific Reports 14, 1550, https://doi.org/10.1038/s41598-024-51958-z