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29 During the last two decades, multiple statistical approaches have been proposed for differential expression testing.
We have collected replicates for both D. yakuba and D. simulans, contributing to the greater power in differential expression testing.
Cufflinks assemblies from all samples were merged using Cuffmerge and Cuffdiff was employed for differential expression testing.
The effective reduction of candidates by differential expression testing after adjustment was 63.2%, 69.5%, and 59.8%, respectively, i.e., 64% on average.
We have sequenced samples to extremely high coverage, generating transcript annotations with 5′ and 3′ UTRs with empirically supported intron-exon structures, improving accuracy in differential expression testing.
These represent 29%, 22.6%, and 33.2% of genes in the chromosomes 2, 11, and 17 donor regions, which were excluded from differential expression testing.
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The TMM method was used to normalise read counts and differential expression tested for using a paired generalized linear model design with the Bioconductor version 2.11 edgeR package [ 24].
That is, the ranking order of betweenness scores was almost completely uncorrelated with the results of differential expression test, and the differentially expressed tests only provide a low accuracy for the prioritization of genes.
We also compared naiveLu, a simple method for identifying differentially expressed genes by simply applying a differential expression test directly without accounting for sample heterogeneity.
Differential expression: Differential expression tests were performed using the Reproducible Optimized Test Statistic (ROTS 82 with FDR < 0.05.
Moreover, normalization for the differential expression test expects equivalent expression levels for several co-expressed genes [ 14].
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