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A) Average expression threshold can be raised to get rid of low expression features with abnormal error terms, circled in blue
B) Six low expression features (circled in blue) account for a very sharp increase in the trend which can have an unduly large effect on overall results |
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[1] Auer, 2011, A two-stage Poisson model for testing RNA-Seq.
[2] Burnham, Anderson, 2010, Model selection and multimodel inference.
[3] Dillies et al, 2012, A comprehensive evaluation of normalization methods.
[4] Storey, 2002, A direct approach to false discovery rates.
[5] Law et al, 2014, Voom: precision weights unlock linear model analysis. Note that this paper introduces both "limma trend" and "limma voom", but the present implementation in GSA corresponds to "limma trend".
[6] Love et al, 2014, Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2.
[7] Bioconductor support forum. Accessed last: 4/12/16. {+}https://support.bioconductor.org/p/80745/#80758+
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