baySeq: Empirical Bayesian analysis of patterns of dierential expression in count data
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We assume that we have data from a set of sequencing or other high-throughput experiments, arranged in an array such that each column describes a sample and each row describes some genomic event for which data have been acquired. For example, the rows may correspond to the different sequences observed in a sequencing experiment. The data then consists of the number of times each sequence is observed in each sample. We wish to determine which, if any, rows of the data correspond to some patterns of differential expression across the samples.
[1] Thomas J. Hardcastle,et al. baySeq: Empirical Bayesian methods for identifying differential expression in sequence count data , 2010, BMC Bioinformatics.
[2] Thomas J. Hardcastle,et al. Small Silencing RNAs in Plants Are Mobile and Direct Epigenetic Modification in Recipient Cells , 2010, Science.
[3] Thomas J. Hardcastle. Generalised empirical Bayesian methods for discovery of differential data in high-throughput biology , 2015, bioRxiv.