Description Usage Arguments Details Author(s) See Also Examples
View source: R/pearson_scatter.R
scatter plot and calculate Pearson correlation coefficient for paired data.
1 2 | pearson_scatter(Trad_data, MC_data, scatter_col = "gray28", line_col = "black",
title = NULL, xlab = "TradPerm P-value", ylab = "MCPerm P-value")
|
Trad_data |
numeric vector, e.g. the result('perm_Qp'/'perm_I2'/'perm_p') of function 'meta.TradPerm'. |
MC_data |
numeric vector, e.g. the result('perm_Qp'/'perm_I2'/'perm_p') of function 'meta.MCPerm'. |
scatter_col |
the color(default 'gray28') of the scatter points. |
line_col |
the color(default 'black') of the line x=y. |
title |
The main title (on top). |
xlab,ylab |
X axis label, default value is 'TradPerm P-value'. Y axis label, default value is 'MCPerm P-value'. |
Scatter plot and Pearson correlation coefficient(two.sided) for 'perm_Qp'/'perm_I2'/'perm_p' of 'meta.TradPerm' and 'meta.MCPerm' are to test the consistency between them.
Lanying Zhang and Yongshuai Jiang <jiangyongshuai@gmail.com>
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.Hist
,
PermMeta.boxplot
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | # Trad=read.table("Trad_result.txt",sep=" ",header=FALSE)
# MC=read.table("MC_result.txt",sep=" ",header=FALSE)
# par(mfrow=c(3,1))
# pearson_scatter(as.numeric(Trad[,4]),as.numeric(MC[,4]),
# title="Q p_value ",
# xlab="TradPerm Qp_value",
# ylab="MCPerm Qp_value")
# pearson_scatter(as.numeric(Trad[,6]),as.numeric(MC[,6]),
# title="I2 p_value",
# xlab="TradPerm I2p_value",
# ylab="MCPerm I2p_value")
# pearson_scatter(as.numeric(Trad[,9]),as.numeric(MC[,9]),
# title="p_value",
# xlab="TradPerm p_value",
# ylab="MCPerm p_value")
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