May 15, 2009, 2:38:58 PM (13 years ago)
Jari Häkkinen

Addresses #118. Added documentation for qQuantiler.

1 edited


  • plugins/base2/net.sf.basedb.normalizers/trunk/README

    r1065 r1074  
    66plug-in set is a compilation of normalisers for expression data. See
    77``Documentation`` below for further information about the different
    8 plug-ins in this package. Common to the plug-ins provided with this
    9 package is that they work on bioassay set with either 1-channel or
    10 2-channel. The algorithms are working on expression values, that is
    11 for 2-channel data, ratios ch1/ch2 are used.
     8plug-ins in this package. Common to most of the plug-ins provided with
     9this package is that they work on bioassay sets with either 1-channel
     10and 2-channel data. The algorithms are working on expression values,
     11that is for 2-channel data, ratio ch1/ch2 are used.
    1313`Normalization package for BASE` is free software. See the file
    5050== qQuantile normalization ==
    52 Write me.
     52The current implementation of qQuantile normalization supports only
     531-channel arrays.
    5455The qQuantile normalization is inspired by the 'Cubic Spline'
    5556normalization in Illumina Beadstudio and the work by Workman et al.,
     59In qQuantile normalization, all assays (including the target) are
     60sorted in increasing intensity. The sorted list of probe intensities
     61are partitioned into q groups, and each of theses q groups are
     62adjusted (normalized) with the corresponding target group. After
     63normalization the intensity distribution of each assay will be
     64approximately the same as the target distribution. q is calculated as
     65q=max(10,min(100,target_size/10)). The program will stop if the number
     66of well defined expression values in the target or any of the assays
     67in the set is smaller than q.
     69The target is defined by selecting a subset of the assays in the
     70bioassay set, and the target expression values are the medians of
     71probe intensities over the bioassay set. Probes with no well defined
     72measurements in the bioassay set are simply ignored in target
     75Since the normalization calculations are based on geometric means and
     76performed in log space the intensities must be positive and larger
     77than 0. Rather than expecting the user of qQuantile normalization to
     78remove such intensity the underlying algorithm silently ignores zero
     79and negative intensities.
     81Background subtraction and proper filtration should be done on the
     82bioassay set before running this plug-in.
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