Robust Probabilistic Averaging (RPA) is a Bioconductor R package for probe-level preprocessing and analysis of short oligonucleotide arrays. The tools are generic but special wrappers are available for Affymetrix gene expression arrays as well as phylogenetic microarrays (HITChip in particular).
This Github repository is the home for the latest development version. For the release version, see RPA Bioconductor page
The installation instructions and working examples are in RPA wiki.
This directory contains the following:
- The R package structure (development version)
- inst/extras/misc Miscellaneous development and test code
- inst/extras/NAR2013 Some scripts used for the NAR 2013 paper
The work has been documented in these two publications. Kindly cite if appropriate:
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A fully scalable online pre-processing algorithm for short oligonucleotide microarray atlases Leo Lahti, Aurora Torrente, Laura L Elo, Alvis Brazma, Johan Rung. Nucleic Acids Research' 41(10):e110, 2013.
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Probabilistic analysis of probe reliability in differential gene expression studies with short oligonucleotide arrays Leo Lahti, Laura L. Elo, Tero Aittokallio, and Samuel Kaski. IEEE/ACM Transactions on Computational Biology and Bioinformatics 8(1):217-25, 2011.
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Robust Probabilistic Analysis (RPA). Bioconductor package. Leo Lahti, 2013. URL: http://bioconductor.org/packages/release/bioc/html/RPA.html
RPA has also been used in the context of phylogenetic microarrays, see for instance: