Sentence examples for moderate number of samples from inspiring English sources

Thus, a technique for the optimal selection of a moderate number of samples effectively representing the entire space of sample realizations is of paramount importance.

Amplification of microsatellite loci was performed following the single-reaction, nested PCR method of Schuelke (2000), a cost-efficient method best suited for projects with a small to moderate number of samples (Blacket et al., 2012).

This is similar to the phenomenon that the precision of f-statistics does not improve appreciably with more than a moderate number of samples and is due to the inherent variability in genetic drift among different loci.

The CEGS population has a moderate number of samples (n = 75) and while RNA-seq data are based on counts, after log transformation and upper quartile normalization the genes in the sex hierarchy in the CEGS data are also approximately normal (Additional file 1: Table S3B).

Some of the AIMs identified in this study may be limited by the small to moderate number of samples in the HapMap II project; therefore, the generality of the identified AIMs should be further examined by using more independent samples and confirmed by biological verifications such as real-time reverse-transcription polymerase chain reaction before the AIMs applying to practical studies.

Third, the eQTL identified in this study might be limited by the small to moderate number of samples and ethnic populations available in the HapMapII project; therefore, the results should be further examined using additional samples from additional populations and require increased biological verifications.

These results suggest that this approach can meet a need in the clinical lab where moderate numbers of samples can be tested against specific clinically relevant panels of SNP targets.

Based on these efforts, we could finally obtain this moderate number of patient samples.

This subjectivity may have contributed to the low κ-scores because of the relatively high number of negative and low to moderate number of positive samples examined.

It is particularly valuable for applications requiring the detection of a moderate number of transcripts in thousands of samples.

According to the method developers, it can be applied to data with at least moderate numbers of replicate samples (∼10 or more).