The phrase "a very small dataset" is correct and usable in written English.
You can use it when discussing the size of a dataset in contexts such as data analysis, research, or statistics.
Example: "The results of the experiment were inconclusive due to the limitations of a very small dataset."
Alternatives: "a tiny dataset" or "a minimal dataset."
Unfortunately, the method has only been tested on a very small dataset, and no further applications are known to us.
Authors' response 6: The dataset used in Table 5 is very small (4 pairs of peptides) and we agree with the reviewer that validating any method on a very small dataset doesn't ensure the reliability of the method.
You can also specify each cell individually, up to 255 cells, as in "=MODE(A1, A2, A3)," but this is not advisable unless you have only a very small dataset and do not plan to add to it.
However, to avoid the problem of dimensionality (ie, large number of parameters with very small dataset), SCARVA models the effect of rare alleles using a single parameter with the well-developed approach of identifying variants that show positive as well as negative associations.
A: Very small quantities, and we stopped.
The results obtained by RAREVATOR on this very small dataset emphasize the importance of our tool for reanalyzing the huge amount of HTS data generated in the last few years and aligned against the human reference genome GRCh37 for complementing the results obtained with classical variant callers in HTS-based studies.
It should be noted that Visscher and colleagues [ 23] were unable to identify any correlations between EGFR and HRG expression in their primary tumour specimens; however, this may simply reflect the very small dataset (34 samples) used in the study [ 23].
Even at 50 or 100 K reads, the sum of deviations was rather moderate, opening the perspective that even very small datasets will still guarantee a reasonable quantification result for the main sample ingredients.
The feasibility of modeling very small datasets by means of the bootstrap aggregating technique is explored.
This is the case even with very small datasets, strongly unbalanced designs and non-Gaussian errors.
Beta1AR, beta3AR, and HIVi are very small datasets in our comparison; thus, it seems probable that the poor results of the Bayesian approach (a poor approximation of the (mathcal {S}) value) were caused by the high internal variance in the dataset rather than because the Bayesian approach was actually worse than the grid search method.
