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- TSP
- __builtin__.object
-
- DoubleVector
- IntVector
- tsp_PySwigIterator
class TSP |
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Top Scoring Pairs class.
This class runs the top scoring pairs algorithm described in The ordering
of expression among a few genes can provide simple cancer biomarkers
and signal BRCA I mutations by Lin et al in BMC Bioinformatics 2009, 10:256
http://www.biomedcentral.com/1471-2105/10/256
TSP was originally introduces by Geman,D. et al. (2004) Classifying
gene expression proles from pairwise mRNA comparisons.
Statistical Applications in Genetics and Molecular Biology Vol 3
[2004], Issue 1 Article 19.
This code uses slightly modified code from
https://jshare.johnshopkins.edu/dnaiman1/public_html/rxa/ which is
the code described in the above mentioned paper. |
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Methods defined here:
- __init__(self, data, numGenes, classSizes, filter)
- Initializes the object.
data is an IntVector containing the microarray data and should be
generated by the dataPackager class.
numGenes is an integer containing the number of genes/probes per sample
in the data table
classSizes is an intvector containing the size of the 2 classes,
class 1 and class 2 respectively.
filter (a two item IntVector) causes only the genes with the wilcoxon scores >=
the the filterth best wilcoxon scores to be considered
- addUnclassified(self, unclassifiedVector)
- classify(self)
- crossValidate(self, k=10)
- Runs the C-based cross validation
K-fold testing of the given data, returns the Matthews correlation coefficient [-1.0, 1.0].
- getMaxScores(self)
- Returns a list of the top scoring pairs indices
- train(self)
- Trains on the given data.
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