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Our experiments and comparisons were implemented in Matlab R2010b on an Intel i7 4600 laptop with 8 GB of memory, running Windows 8. To compare the performance with the matrices Φ t), we measured the rate of convergence and the probability of an exact reconstruction for different sparsity values k and for different numbers of measurements.
Functional comparisons were implemented using the SEED genome viewer v2 [ 86, 87].
All comparisons were implemented in BLAST2GO, which uses a Fisher's exact test to determine significance after controlling for multiple tests with a false discovery rate (FDR) = 0.05.
For these two groups, between group and within group comparisons were implemented using Mann Whitney U and Wilcoxon signed rank respectively.
We compared the six test libraries with the control, two treatments during the same stage, and the same treatment during different stages, so that 15 pairs of comparisons were implemented.
MicroRNA families were downloaded from miRBase and ID conversion and matching code automated in R. When comparisons were implemented between differentially expressed sets of genes from distinct species (i.e., mouse vs. human), the human gene symbols were first converted into mouse symbols based on homology matching.
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Performance comparisons are implemented among several kinds of multi-class decision machines, by which the effectiveness of the proposed approach is proved.
The Benjamini-Hochberg method [14] for controlling the false discovery rate in multiple comparisons was implemented at the α = 0.05 level.
No correction for multiple comparisons was implemented.
An adjustment for multiple comparisons is implemented to limit false positive discoveries.
The differential expression test on seventy comparisons was implemented in the edgeR [ 46] software.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com