README.md

wgsPowerTest

This R package runs power calculations for the discovery of variants in whole genome sequencing data

Install the wgsPowerCalc project in R:

devtools::install_github("stephansanders/wgsPowerTest")
library(wgsPowerCalc)

Set the working directory for where you want the PDFs to be printed

setwd("/path/to/directory/")

Run an example to estimate the power to detect an excess of de novo protein truncating variants (PTVs) in autism spectrum disorder as the relative risk is varied: Maximum relative risk (R) = 25 Sample size (N) = 5000 cases Case to control ratio (r) = 1 P-value threshold (p_thres_denovo_burden) = 0.05 Number of de novo PTVs per person (q) = 0.0996 Proportion of de novo PTVs that mediate risk (f) = 0.05 Prefix for PDF of power (name) = Test1 Color of line in PDF (col) = "#4daf4a"

plotDnBurdenByRelativeRisk(R=25, N=5000, r=1, q=0.0996, f=0.05, p_thres_denovo_burden=0.05, name="Test1", col="#4daf4a") 

Run an example to estimate the power to detect an excess of rare protein truncating variants (PTVs) in autism spectrum disorder as the relative risk is varied: Maximum relative risk (R) = 2.5 Sample size (N) = 20000 cases Case to control ratio (r) = 1 P-value threshold (p_thres_cc_burden) = 0.05 Number of rare PTVs per person (q) = 5.04 Proportion of rare PTVs that mediate risk (f) = 0.05 Prefix for PDF of power (name) = Test2 Color of line in PDF (col) = "#4daf4a"

plotCcBurdenByRelativeRisk(R=2.5, N=20000, r=1, q=5.04, f=0.05, p_thres_cc_burden=0.05, name="Test2", col="#4daf4a")

Run an example to estimate the power to detect a specific locus through an excess of de novo protein truncating variants (PTVs) in autism spectrum disorder as the relative risk is varied: Maximum relative risk (R) = 25 Sample size (N) = 5000 cases Case to control ratio (r) = 1 P-value threshold (p_thres_denovo_locus) = 2.5e-06 Number of de novo PTVs per person (q) = 0.0996 Proportion of de novo PTVs that mediate risk (f) = 0.05 Prefix for PDF of power (name) = Test3 Color of line in PDF (col) = "#4daf4a"

plotDnLocusBySampleSize(R=25, N=5000, r=1, q=0.0996, f=0.05, p_thres_denovo_locus=2.5e-06, name="Test3", col="#4daf4a") 

Run an example to estimate the power to detect a specific locus through an excess of rare protein truncating variants (PTVs) in autism spectrum disorder as the relative risk is varied: Maximum relative risk (R) = 2.5 Sample size (N) = 20000 cases Case to control ratio (r) = 1 Number of possible rare variants per gene (s) = 615 Number of possible rare PTVs per gene (f_gene) = 123 Proportion of rare PTVs that mediate risk (f) = 0.05 Prevalence of autism (K) = 0.01 Mean allele frequency of rare variants (AF_bar) = 0.001 Number of replicate simulations (N_rep) = 50 P-value threshold (p_thres_cc_locus_single) = 1.7e-11 Prefix for PDF of power (name) = Test4 Color of line in PDF (col) = "#4daf4a"

plotCcLocusSingleByRelativeRisk(R=2.5, N=20000, r=1, s=615, f_gene=123, f=0.05, K=0.01, AF_bar=0.001, N_rep=10, p_thres_cc_locus_single=1.7e-11, name="Test4", col="#4daf4a") 

For the analyses used to make the figures in the WGSPD manuscript, please see th vignettes.



stephansanders/wgsPowerTest documentation built on Sept. 10, 2017, 12:25 a.m.