proboscis {MAQCsubset} | R Documentation |
Produce a plot similar to Figure 2 of the Shippy MAQC paper (PMID 16964226).
proboscis(es, site=1, ABp=0.001, CDp=0.01, mmrad=100)
es |
ExpressionSet instance with MAQC assay results |
site |
numeric code – site to be assessed |
ABp |
ABp – p-value threshold to declare concentration of gene in sample A to be different from ehe concentration in sample B |
CDp |
CDp – p-value threshold to declare concentration of gene in sample C to be different from the concentration in sample D |
mmrad |
numeric radius of the moving mean used to smooth the proportions differentially expressed |
Figure 2 of the Shippy paper consists of a collection of plots of estimated probabilities of self-consistent monotone titration – briefly, samples are such that A has 100% USRNA, B has 100% Ambion brain, C has 75% USRNA+25% brain, D has 25% USRNA, 75% brain. Self-consistent monotone titration holds for gene g if microarray measures for that gene satisfy A > C > D > B or B > C > D > A. The estimated probability functions look like a creature sticking its nose over a wall, thus the name of this function.
an instance of proboStruct
, for which a plot and lines method are available.
Vince Carey <stvjc@channing.harvard.edu>
PMID 16964226
data(afxsubRMAES) NN2 = proboscis(afxsubRMAES, site=2) plot(NN2)