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As part of the FIRMA method, the first two preprocessing steps of the microarrays were performed according to the robust multi-array average (RMA) approach, involving background correction of perfect match probes and inter-chip quantile normalization [ 30].
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When it comes to the most sensitive methods FIRMA, ARH and KLAS fulfill the task best.
In parallel, we also tried three published methods: FIRMA [ 15], ARH [ 16] and COSIE [ 17].
The performance of the three approaches, ESLiMa, ESLiMc and ESLiMt, was compared with three other methods: FIRMA [ 15], ARH [ 16] and COSIE [ 17].
FIRMA is a robust method that can detect splicing chances not necessarily consistent within replicate sets and so does not explain how to summarize from exon-sample scores to overall gene-level scores or whether it is recommended to do so.
A thorough benchmarking of ANOSVA, FIRMA and several other methods for detecting differential splicing can be found in [ 41].
In addition to the synthetic data sets, we evaluated all methods including FIRMA on two well studied cancer data sets.
We applied all 9 methods - including FIRMA - to two partly RT-PCR validated data sets, one from colon cancer and one from lung cancer.
SplicingCompass, ANOSVA, KLAS, FIRMA, and ARH were the methods performing best.
In [ 44] and in [ 45], ANOSVA and FIRMA are compared with other methods, respectively, but not with each other.
When considering only the validated results ARH and FIRMA appeared as the most accurate methods (see Figure 4) closely followed by MIDAS.
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