IFP (version 0.2.4)

Identifying Functional Polymorphisms

Description

A suite for identifying causal models using relative concordances and identifying causal polymorphisms in case-control genetic association data, especially with large controls re-sequenced data.

Copy Link

Version

Install

install.packages('IFP')

Monthly Downloads

178

Version

0.2.4

License

GPL (>= 2)

Maintainer

Leeyoung Park

Last Published

November 26th, 2020

Functions in IFP (0.2.4)

drgen

causal models with G*E

lrtG

Likelihood Ratio Tests for Identifying Disease Polymorphisms with Same Effects

iter.mcmc

mcmc inference of causal models with all possible causal factors: G, G*G, G*E and E

drgene

causal models with G*E and E

allele.freq

Allele Frequency Computation from Genotype Data

allele.freq.G

Allele Frequency Computation from the sequencing data with a vcf type of the 1000 Genomes Project

drgegggne

causal models with all possible causal factors: G, G*G, G*E and E

drgn

causal models with G

drggn

causal models with G*G

drgegne

causal models with three possible causal factors: G, G*E and E

error.rates

Error Rates Estimation for Likelihood Ratio Tests Designed for Identifying Number of Functional Polymorphisms

lrt

Likelihood Ratio Tests for Identifying Number of Functional Polymorphisms

geno.freq

Genotype Frequency Computation from the sequencing data with a vcf type of the 1000 Genomes Project

apoe

Genetic data of APOE gene region

apoeG

Sequencing data of APOE gene region from the 1000 Genomes Project

genotype

Conversion to Genotypes from Alleles using the sequencing data with a vcf type of the 1000 Genomes Project

hap.freq

Estimation of Haplotype Frequencies with Two SNPs