vcfPIC R Package

Overview

The PIC Calculator R package is designed to calculate Polymorphism Information Content (PIC) values for Single Nucleotide Polymorphisms (SNPs) from a VCF (Variant Call Format) , HapMap (Haplotype Map) or Genetic Binary Table file. PIC values provide a measure of the informativeness of genetic markers for linkage and association studies.

$$PIC = 1 - \sum_{i=1}^{n} P_{ij}^2$$

where (P_{ij}) is the frequency of the (j^{th}) allele for the (i^{th}) SNP, and (n) is the number of alleles for the SNP.

Features

Calculate PIC Values: Compute PIC values for each SNP in a given VCF / HapMap / Genetic Binary Table file.
Efficient Processing: Handle large files efficiently using optimized R functions coded using C.
Easy Integration: Seamlessly integrate with other bioinformatics tools and pipelines in R.

Installation

You can install the package directly from GitHub using the devtools package:

# Install devtools if you haven't already
install.packages("devtools")

# Install the PIC Calculator package from GitHub
devtools::install_github("AlsammanAlsamman/vcfPIC")

Usage

Load the Package

library(vcfPIC)

Calculate PIC from different file formats

from HapMap file

data("sheep_genotypes_hapmap")

PIC.hapmap <- calculatePIC(sheep_genotypes_hapmap, "hapmap")
head(PIC.hapmap)

from VCF file

data("sheep_genotypes_vcf")

PIC.vcf <- calculatePIC(sheep_genotypes_vcf, "vcf")
head(PIC.vcf)

from Genetic Binary Table file

The Genetic Binary Table file is a tab-delimited text file with the following format:

| rs  | alleles | chr | pos | sample1 | sample2 | sample3 | sample4 | sample5 | sample6 | sample7 |
|-----|---------|-----|-----|---------|---------|---------|---------|---------|---------|---------|
| rs1 | A/T     | 1   | 100 | 2       | 0       | 1       | 1       | -1      | 1       | 0       |
| rs2 | C/G     | 1   | 200 | 0       | 2       | 0       | 1       | 2       | 0       | 1       |
| rs3 | A/C     | 1   | 300 | 2       | 0       | 1       | 0       | 1       | 2       | 0       |

* rs: SNP ID
* alleles: Alleles of the SNP (The value can be "-" if not available)
* chr: Chromosome number of the SNP (The value can be "-" if not available)
* pos: Position of the SNP on the chromosome (The value can be "-" if not available)

data("sheep_genotypes_binary")
PIC.binary <- calculatePIC(sheep_genotypes_binary, "binary")

Calculate PIC step by step

library(vcfPIC)

# The path to the package data, where the VCF , HapMap and Binary files are stored
vcfPICpath <- system.file(package="vcfPIC")

###### VCF

# Step 1: Read the VCF data

vcfData <- readVCF(paste(vcfPICpath,"/data/sheep_genotypes.vcf",sep="") )
head(vcfData)

# Step 2: Calculate allele frequencies from VCF data
freqVCF <- calculateAlleleFreqVCF(vcfData)
head(freqVCF)

# Step 3: Calculate PIC from allele frequencies of VCF data
PIC.vcf <- calculatePICByFreq(freqVCF)
head(PIC.vcf)

###### HapMap
# Step 1: Read the HapMap data
hapmapData <- readHapmap(paste(vcfPICpath,"/data/sheep_genotypes.hmp",sep=""))

# Step 1: Convert HapMap genotypes to binary numeric format
hapmapData.Binary <- convertGenoBi2Numeric(hapmapData)
head(hapmapData.Binary)

# Step 2: Calculate PIC directly from a VCF file
PIC <- calculatePIC("data/sheep_genotypes.vcf", "vcf")
head(PIC)

###### Binary
# Step 1: Read the binary genetic data
binaryData <- readGeneticBinaryTable(paste(vcfPICpath,"/data/sheep_genotypes_binary.tsv",sep=""), header=TRUE, sep="\t")
head(binaryData)

# Step 2: Calculate allele frequencies from binary data
TableBinarFreq <- calculateAlleleFreqBinary(binaryData)
head(TableBinarFreq)

# Step 3: Calculate PIC from allele frequencies of binary data
PIC.vcf <- calculatePICByFreq(TableBinarFreq)
head(PIC.vcf)

Contact

For any questions or inquiries, please contact Alsamman at a.alsamman[useAandT]cgiar.org.