Compute PI - proportion of observations missing completely at random
eigen_pi(m, toplot = TRUE)
matrix of abundances, numsmaples x numpeptides
TRUE/FALSE plot mean vs protportion missing curve and PI
pi estimate of the proportion of observations missing completely at random
Contributed by Shelley Herbrich & Tom Taverner for Karpievitch et al. 2009
data(mm_peptides) intsCols = 8:13 metaCols = 1:7 m_logInts = make_intencities(mm_peptides, intsCols) m_prot.info = make_meta(mm_peptides, metaCols) m_logInts = convert_log2(m_logInts) my.pi = eigen_pi(m_logInts, toplot=TRUE)
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