Dear list,
I am analysing a set of quantitative proteomics data from 16 patients
which has a large numbers of missing data, thus some proteins are only
detected once, upto a maximum of 16.
I want to test each protein for normality by the Shapiro Wilk test
(function shapiro.test in package stats), which can only be applied to
data with at least 3 measurements, which is fine. In the case where I
have only 3 observations, and two of those observations are identical,
then the shapiro.test produces negative P-values, which should never
happen.
This occurs for all of the situations that I have tried for 3 values,
where 2 are the same.
Reproducible code below:
# these are the data points that raised the problem
> shapiro.test(c(-0.644, 0.0566, 0.0566))
Shapiro-Wilk normality test
data: c(-0.644, 0.0566, 0.0566)
W = 0.75, p-value < 2.2e-16
> shapiro.test(c(-0.644, 0.0566, 0.0566))$p.value
[1] -7.69e-07
# note the verbose output shows a small, but positive P-value, but
when you extract that P using $p.value, it becomes negative
# various other tests
> shapiro.test(c(1,1,2))$p.value
[1] -8.35e-07
> shapiro.test(c(-1,-1,2))$p.value
[1] -1.03e-06
cheers,
Mark
> sessionInfo()
R version 2.6.1 (2007-11-26)
i386-apple-darwin8.10.1
locale:
en_AU.UTF-8/en_AU.UTF-8/en_AU.UTF-8/C/en_AU.UTF-8/en_AU.UTF-8
attached base packages:
[1] tcltk graphics grDevices datasets utils stats
methods base
other attached packages:
[1] qvalue_1.12.0 Cairo_1.3-5 RSvgDevice_0.6.3
SparseM_0.74 pwbc_0.1
[6] mjcdev_0.1 tigrmev_0.1 slfa_0.1
sage_0.1 qtlreaper_0.1
[11] pajek_0.1 mjcstats_0.1 mjcspot_0.1
mjcgraphics_0.1 mjcaffy_0.1
[16] haselst_0.1 geomi_0.1 geo_0.1
genomics_0.1 cor_0.1
[21] bootstrap_0.1 blat_0.1 bitops_1.0-4
mjcbase_0.1 gdata_2.3.1
[26] gtools_2.4.0
-----------------------------------------------------
Mark Cowley, BSc (Bioinformatics)(Hons)
Peter Wills Bioinformatics Centre
Garvan Institute of Medical Research, Sydney, Australia
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