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For COI and the combined COI-28S dataset, analyses were performed with 1 million generations sampled every 1000 generations while 300000 generations sampled every 300 generations were used for the 28S dataset.
Finally, our asthma expression dataset analyses were performed in immortalized B-cells derived from asthmatics.
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For each dataset, some analyses were performed on the total sampling i.e. simultaneously considering all species, while others were computed within each species separately.
For analyzing the large datasets, bootstrap analyses were performed separately and the bootstrap support was plotted on the respective best tree.
For the three real datasets, differential analyses were performed using a negative binomial model (Anders and Huber, 2010) for unfiltered data and after filtering the data using the techniques described earlier in the text.
Using the set of 1162 genes identified by MDA (Additional File 4) and the similar lists of genes identified from each of the simulated datasets, pathway analyses were performed with Ingenuity Pathway Analysis.
From this dataset, two different analyses were performed: The first made use of the recombination detection algorithms available in RDP3 [ 39] but with a particular set-up so that only re-assortment events with or without CR exchanges were detected as recombination events.
For every expression datasets, differential expression analyses were performed using R package "limma" [ 22].
However it is noteworthy that the majority of the variance in the MAQC dataset was attributable to the intra-chip (inter-array) level and this is the only dataset, for which variance analyses were performed, in which this phenomenon holds.
Dataset implementation and exploratory analyses were performed in R (R Core Team 2016).
The dataset collection and bioinformatics analyses were performed by DCB.
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