landscapefast.Rd
Interactive 3-D association landscape for many phenotypes
landscapefast(
d,
sliceval = 7,
chromosome = FALSE,
pop = "GBR",
R2 = 0.75,
D = 0.75,
calculateLD = FALSE,
mutualLD = FALSE,
phenos,
genemap = FALSE,
geneview = FALSE,
levelsdown = 0
)
DataFrame output from processphegwas
Integer to indicate value of -log10(p) to do the sectionalcut. Usually value > -log10 6 is considered to be significant
Integer to indicate the chromosome number thats interested, If not given entire chromosome is given
The population to select for calculation the LD (default GB)
The value to set to calculate LD
THe value to set to calcualte LD
This shoudld be set to true if the calcualte LD logic needed to be added to the plot
Calcualte the mutual LD SNP between the phenotypes
Vector of names of dataframes that need to do PheGWAS on. Arrange the dataframe in the order how the the phenotypes should align in y axis chromosome view the max peak is selected
if true it map SNP's to gene. This takes time as its using BioMart package to map genes.
This checks for the common genes across the section
Used to find the independant signals
if (FALSE) {
# here y is output from function fastprocessphegwas
# 3D landscape-viz of all the phenos across the base pair positions(threshold > -log10(p) 7.5)
# Without iPheGWAS you get output in the order you pass phenos
landscapefast(y,sliceval = 10,phenos =phenos)
# 3D landscape visualization after applying iPheGWAS
# Passing the order from the iPheGWAS function
landscapefast(y,sliceval = 10,phenos = iphegwas(phenos))
#3D landscape visualization of chromosome number 19 (above a threshold of -log10 (p) 7.5)
landscapefast(y,sliceval = 7.5,chromosome = 19,phenos =phenos)
# 3D landscape-viz of chromosome 19, gene view active(threshold > -log10(p) 7.5)
landscape(y,sliceval = 7.5,chromosome = 19, geneview = TRUE,phenos =phenos)
# 3D landscape-viz with calculate-LD and mutual-LD functionality active
landscapefast(y, sliceval = 30, chromosome = 19,calculateLD= TRUE,mutualLD = TRUE,phenos =phenos)
}