Normal Q-Q Plot for DEDS Objects

Description

The function qqnorm.DEDS produces normal Quantile-Quantile plots of statistics for DEDS-class objects. The points corresponding to genes with DEDS q- or adjusted p-values less than a user defined threshold are highlighted.

Usage

## S3 method for class 'DEDS'
qqnorm(y, subset=c(1:nrow(y$stats)),
xlab = "Quantiles of standard normal", thresh = 0.05, col = palette(), pch, ...)

Arguments

Details

The function qqnorm.DEDS implements a S3 method of qqnorm for DEDS. The DEDS class is a simple list-based class to store DEDS results and qqnorm.DEDS is used for a DEDS object that is created by functions deds.stat, deds.stat.linkC. The list contains a "stat" component, which stores statistics from various statistical tests. The function qqnorm.DEDS extracts the "stat" component and produces a normal QQ plot for each type of statistics. qqnorm.DEDS as a default highlights points (corresponding to genes) with DEDS adjusted p- or q-values less than a user defined threshold.

For DEDS objects that are created by the function deds.pval, the "stat" matrix consists of unadjusted p-values from different statistical models. For graphical display of these p values, the user can use hist.DEDS and pairs.DEDS.

Author(s)

Yuanyuan Xiao, yxiao@itsa.ucsf.edu,
Jean Yee Hwa Yang, jean@biostat.ucsf.edu.

See Also

deds.stat, deds.pval, deds.stat.linkC, hist.DEDS, qqnorm.DEDS

Examples

X <- matrix(rnorm(1000,0,0.5), nc=10)
L <- rep(0:1,c(5,5))

# genes 1-10 are differentially expressed
X[1:10,6:10]<-X[1:10,6:10]+1
# DEDS summarizing t, fc and sam
d <- deds.stat.linkC(X, L, B=200)

# qqnorm for t, fc and sam
qqnorm(d)
# change points color
qqnorm(d, col=c(2,3))
# change points type
qqnorm(d, pch=c(1,2))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(DEDS)
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/DEDS/qqnorm.DEDS.Rd_%03d_medium.png", width=480, height=480)
> ### Name: qqnorm-methods
> ### Title: Normal Q-Q Plot for DEDS Objects
> ### Aliases: qqnorm.DEDS qqnorm-methods qqnorm
> ### Keywords: hplot
> 
> ### ** Examples
> 
> X <- matrix(rnorm(1000,0,0.5), nc=10)
> L <- rep(0:1,c(5,5))
> 
> # genes 1-10 are differentially expressed
> X[1:10,6:10]<-X[1:10,6:10]+1
> # DEDS summarizing t, fc and sam
> d <- deds.stat.linkC(X, L, B=200)
We'll do random permutations, B =  200 

Two-sample Statistics:
t 	FC 	SAM 	
E of the orginial data is: 5.828  1.140  2.143  
b=2	b=4	b=6	b=8	b=10	b=12	b=14	b=16	b=18	b=20	
b=22	b=24	b=26	b=28	b=30	b=32	b=34	b=36	b=38	b=40	
b=42	b=44	b=46	b=48	b=50	b=52	b=54	b=56	b=58	b=60	
b=62	b=64	b=66	b=68	b=70	b=72	b=74	b=76	b=78	b=80	
b=82	b=84	b=86	b=88	b=90	b=92	b=94	b=96	b=98	b=100	
b=102	b=104	b=106	b=108	b=110	b=112	b=114	b=116	b=118	b=120	
b=122	b=124	b=126	b=128	b=130	b=132	b=134	b=136	b=138	b=140	
b=142	b=144	b=146	b=148	b=150	b=152	b=154	b=156	b=158	b=160	
b=162	b=164	b=166	b=168	b=170	b=172	b=174	b=176	b=178	b=180	
b=182	b=184	b=186	b=188	b=190	b=192	b=194	b=196	b=198	b=200	

After permutation , E is set at: 8.922  1.284  2.479  

Summarizing DEDS results for 200 permutations and 100 genes, please wait... 
> 
> # qqnorm for t, fc and sam
> qqnorm(d)
> # change points color
> qqnorm(d, col=c(2,3))
> # change points type
> qqnorm(d, pch=c(1,2))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>