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Gene variance of a bicluster is given by the mean of the variances of all the genes in it, as in equation 10. (10) GeneVar (B ) = 1 | I | · | J | ∑ i = 1 | I | ∑ j = 1 | J | (b ij − μ g i ) 2 Existing biclustering approaches deal with gene variance in different ways.
This was attributed to the high degeneracy in gene variance within the large population, resulting in a futile search.
The 770 genes included in the PanCancer Pathways Panel were selected using a biology-guided, data-driven methodology that provides high confidence that the gene variance within each cancer pathway was captured.
For each normalization method, filtering was based on gene variance across arrays.
Of these sixty predicted expression changes, 25 were significant under both models, 32 were significant under the per- gene variance model only, and 3 were significant under the common gene variance model only.
Figure 4 compares the SWISS scores of the reference and single channel designs when we filter by gene variance across all arrays.
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A correlation was not detected under the per-gene variance model.
Namely, those genes in common between the two analyses (common and per-gene variance assumption) generally demonstrated very large changes in expression levels while having small variances.
We addressed that question by likelihood-ratio test of the model with the among-gene (residual) variance estimated separately for N2 and the MA line with the greatest among-gene variance (MA99) lines vs. a model with a common among-gene variance.
The first model assumed a common variance for all genes, while the second linear model relied on limited biological replication to estimate the individual gene variation (i.e., per-gene variance).
We found that between 6% (common variance ANOVA model) and 15% (per-gene variance ANOVA model) of all genes displayed differential expression between the diploid progenitors (B. rapa line IMB218 and B. oleracea line TO1000).
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com