The phrase "as a single dataset" is correct and usable in written English.
It can be used when referring to the combination or treatment of multiple data points or sources as one cohesive unit for analysis or processing.
Example: "The researchers decided to analyze the collected information as a single dataset to ensure consistency in their findings."
Alternatives: "as one dataset" or "as a unified dataset".
Dave Boxall, head of information security, Guardian News & Media Diverse storage would on the face of it seem sensible but I would argue the common attack point isn't the data store but the logic that retrieves the data which would allow diversely stored data to be retrieved as a single dataset.
This was the case when analysed separately or as a single dataset of down-regulated genes, perhaps partially attributed to the relatively small size of the datasets.
Data from the three independent trials were statistically analyzed (see section 2.6), and after ANOVA determined that the three trials were statistically similar the data were merged and presented in the results section as a single dataset.
Sequences of Pvama1 from the original survey region from 1997 and those from Koshirowetheri in 1997 were subsequently compared by tests of departure from neutrality and analysis of within-population diversity to identify any significant differences between them that would preclude all Pvama1 sequences obtained in the 1997 survey being treated as a single dataset.
Therefore, the data was treated as a single dataset, except during subgroup analyses.
Alternatively, they could be combined as a single dataset and be used as input for a single source-based random forest algorithm.
These massive calculations were performed on a 64 GB RAM, four Intel Xeon 2.33 GHz CPU machine, as processing of a single dataset required about 15 GB of main memory.
This would be a more useful Hi-C data set than the ES cells data from Dixon et al. I do realize this may be difficult given the amount of material that this may require, but it would be a very interesting dataset as it may reveal the stage-specific sub-domains as well as invariant larger domains in a single dataset, with potential changes in the larger domains in limb.
In addition, we introduce cancer-specific compendia, as an intermediate step between a single dataset and a complete human cancer compendium.
Although most of these gene expression data were generated using the same microarray platform, and could in principle be merged in a single dataset as recently described [13], we evaluated the DM signature on the individual datasets.
Figure 3 shows the mean classification accuracy of single trial power (blue diamonds) and rank spectra (green squares) in a single dataset as a function of the number of frequency bins (features) used.
