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MCPerm (version 1.1.4)

PermMeta.Hist: histplot for the result of 'meta.MCPerm' or 'meta.TradPerm'

Description

histplot for the result of 'meta.MCPerm' or 'meta.TradPerm'.

Usage

PermMeta.Hist(PermMeta, plot = "Qp", fill_col = NULL, border_col = "black", arrows_col = "red", main = "Hist plot for heterogeneity Q p_vlaue", xlab = "Q p_value", ylab = "Density", digits = 3)

Arguments

PermMeta
the result of function 'meta.TradPerm' or 'meta.MCPerm'.
plot
a character string indicating which return value of function 'meta.TradPerm' or 'meta.MCPerm' to be plot. The value can be "Qp"(default), "I2", "merged_LnOR", "merged_LnOR_VAR" or "merged_LnOR_p". And the value must be simulation data. 'Qp', "I2", "merged_LnOR", "merged_LnOR_VAR" and "merged_LnOR_p" separetly plots the return value 'perm_Qp', 'perm_I2', 'perm_merged_LnOR', 'perm_merged_VARLnOR', 'perm_merged_p'.
fill_col
the filled color(default NULL) for the body of histplot.
border_col
the color(default 'black') for the border of histplot.
arrows_col
the color(default 'red') of arrows which mark the place of the observed value.
main
the main title (on top), default value is "Hist plot for heterogeneity Q p_vlaue".
xlab,ylab
X axis label, default value is 'Q p_value'. Y axis label, default value is 'Density'.
digits
integer(default 3) indicating the number of decimal places.

Details

Histplot for the return value('perm_Qp','perm_I2','perm_merged_LnOR','perm_merged_VARLnOR', 'perm_merged_p') of 'meta.MCPerm' or 'meta.TradPerm'. And through arrows and legend to mark the observed value.

The symbols in the legend: 'Q_stat' is the Q statistic for meta data heterogeneity; 'Q_p' is the p value of Q value(chi square distribution,the number of studies in meta analysis minus one is degree of freedom of Q value.); 'p.corrected' is the corrected p value by permutation; 'I2_stat' is the statistic I2(calculated by formula max(Q-d.f./Q, 0)) for meta data heterogeneity; 'merged_LnOR' is the merged log odd ratio of observed data; 'merged_LnOR_VAR' is the variance of log odd ratio for observed data; 'merged_LnOR_p' is the p value of log odd ratio of observed data which obey normal distribution.

MCPerm details see chisq.MCPerm. TradPerm details see chisq.TradPerm.

See Also

meta.MCPerm, meta.TradPerm, chisq.MCPerm, chisq.TradPerm, VS.Hist, VS.KS, VS.Genotype.Hist, VS.Allele.Hist, PermMeta.LnOR.Hist, PermMeta.LnOR.CDC, PermMeta.LnOR.boxplot, PermMeta.LnOR.qqnorm, PermMeta.boxplot

Examples

Run this code
## import data
# data(MetaGenotypeCount)
## delete first line
# temp=MetaGenotypeCount[-1,];
# result=meta.MCPerm(case_11=as.numeric(temp[,14]),case_12=as.numeric(temp[,16]),
	 # case_22=as.numeric(temp[,18]),control_11=as.numeric(temp[,15]),
	 # control_12=as.numeric(temp[,17]),control_22=as.numeric(temp[,19]),
	 # model="allele",fixed_method="MH",random_method="DL",repeatNum=1000)
## set working directory to save the plots.
# setwd("D:\")
# pdf("PermMeta.Hist.pdf",height=6,width=6)
# PermMeta.Hist(result,plot="Qp",fill_col=NULL,border_col='black',
    # arrows_col='red',main="Hist plot for heterogeneity Q p_vlaue",xlab="Q p_value")
# PermMeta.Hist(result,plot="I2",fill_col=NULL,border_col='black',
    # arrows_col='red',main="Hist plot for heterogeneity I2",xlab="I2")
# PermMeta.Hist(result,plot="merged_LnOR",fill_col=NULL,border_col='black',
    # arrows_col='red',main="Hist plot for merged_LnOR",xlab="merged_LnOR")
# PermMeta.Hist(result,plot="merged_LnOR_VAR",fill_col=NULL,border_col='black',
    # arrows_col='red',main="Hist plot for merged_LnOR_VAR",xlab="merged_LnOR_Variance")
# PermMeta.Hist(result,plot="merged_LnOR_p",fill_col=NULL,border_col='black',
    # arrows_col='red',main="Hist plot for merged_LnOR_p",xlab="merged_LnOR_p.value")
# dev.off()

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