Methods for Present/Absent Calls are meant to provide means of assessing whether or not each of the (PM) intensities are compatible with observations generated by background probes.
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paCalls(object, method, ..., verbose=TRUE) ## S4 method for signature 'ExonFeatureSet' paCalls(object, method, verbose = TRUE) ## S4 method for signature 'GeneFeatureSet' paCalls(object, method, verbose = TRUE) ## S4 method for signature 'ExpressionFeatureSet' paCalls(object, method, ..., verbose = TRUE)
String defining what method to use. See 'Details'.
Additional arguments passed to MAS5. See 'Details'
Logical flag for verbosity.
For Whole Transcript arrays (Exon/Gene) the valid options for
method are 'DABG' (p-values for each probe) and 'PSDABG'
(p-values for each probeset). For Expression arrays, the only option
currently available for
method is 'MAS5'.
ABOUT MAS5 CALLS:
The additional arguments that can be passed to MAS5 are:
alpha1: a significance threshold in (0, alpha2);
alpha2: a significance threshold in (alpha1, 0.5);
tau: a small positive constant;
ignore.saturated: if TRUE, do the saturation correction described in
the paper, with a saturation level of 46000;
This function performs the hypothesis test:
H0: median(Ri) = tau, corresponding to absence of transcript H1: median(Ri) > tau, corresponding to presence of transcript
where Ri = (PMi - MMi) / (PMi + MMi) for each i a probe-pair in the probe-set represented by data.
The p-value that is returned estimates the usual quantity:
Pr(observing a more "present looking" probe-set than data | data is absent)
So that small p-values imply presence while large ones imply absence of transcript. The detection call is computed by thresholding the p-value as in:
call "P" if p-value < alpha1 call "M" if alpha1 <= p-value < alpha2 call "A" if alpha2 <= p-value
A matrix (of dimension dim(PM) if method="DABG" or "MAS5"; of dimension length(unique(probeNames(object))) x ncol(object) if method="PSDABG") with p-values for P/A Calls.
Clark et al. Discovery of tissue-specific exons using comprehensive human exon microarrays. Genome Biol (2007) vol. 8 (4) pp. R64
Liu, W. M. and Mei, R. and Di, X. and Ryder, T. B. and Hubbell, E. and Dee, S. and Webster, T. A. and Harrington, C. A. and Ho, M. H. and Baid, J. and Smeekens, S. P. (2002) Analysis of high density expression microarrays with signed-rank call algorithms, Bioinformatics, 18(12), pp. 1593–1599.
Liu, W. and Mei, R. and Bartell, D. M. and Di, X. and Webster, T. A. and Ryder, T. (2001) Rank-based algorithms for analysis of microarrays, Proceedings of SPIE, Microarrays: Optical Technologies and Informatics, 4266.
Affymetrix (2002) Statistical Algorithms Description Document, Affymetrix Inc., Santa Clara, CA, whitepaper. http://www.affymetrix.com/support/technical/whitepapers/sadd_whitepaper.pdf
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