Research
Estimation and correction of non-specific binding in a large-scale spike-in experiment
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* Corresponding author: Eugene F Schuster schuster@ebi.ac.uk
1 European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton Cambridge CB10 1SD, UK
2 MRC Centre for Developmental Neurobiology, King's College London, Guy's Hospital Campus, London SE1 1UL, UK
3 Department of Biology, University College London, Darwin Building, Gower Street, London WC1E 6BT, UK
Genome Biology 2007, 8:R126 doi:10.1186/gb-2007-8-6-r126
Published: 26 June 2007Additional files
Additional data file 1:
Columns represent (in order): Affy, Affymetrix probeset identifier; Clone, the Drosophila Gene Collection clone that aligns to that probeset; C, the concentration pool of that clone in C samples; S, the concentration pool of the clone in S samples; fold, the fold change between S and C samples for the clone; score, alignment score indicating the quality of the alignment (14 = alignment to all 14 probes in probeset); pool, pool number; well, well position in PCR-plate; plate, plate number.
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Additional data file 2:
AUC performance and q-value estimates for low intensity probesets when empty probesets are (a,c) excluded from the analysis and (b,d) included. TPs are FC > 1 probesets and mixed probesets that can be aligned to spiked-in transcripts. True negatives are FC = 1 probesets, empty probesets and mixed probesets that can be aligned only to FC = 1 probesets. Expression values were generated by masking all probes that could not be mapped to the low intensity probesets, re-calculating the probeset expression values and calculating the AUC and q-values. AUC and q-values were also generated from FC = 1 normalizations using all probesets with present transcripts. See legend for coloring of symbols.
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Additional data file 3:
Modified GoldenSpike scripts for use in R with BioConductor
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Additional data file 4:
Scripts to run the alchemy method in R with BioConductor (requires Additional data file 3)
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