Sentence examples for binomial test to identify from inspiring English sources

We carried out a binomial test to identify overrepresentation of GO classes for genes with HCP versus LCP.

We employed a binomial test to identify pathways consistently overrepresented among gene families with positive selection on insertions/deletions of different length in varying secondary structural elements.

Given these discrepancies, to provide additional validation for the use of a multiple span binomial test to identify regional expression biases, REBs were also identified from a set of gene expression data derived from clear cell renal cell carcinomas (ccRCC).

Most of these studies applied the one-tailed binomial test to identify significantly mutated genes, followed by a false discovery rate procedure to control for multiple testing (Benjamini and Hochberg 1995).

For simplicity, we term this approach IR-CGMA, for Improved Resolution-Comparative Genomic Microarray Analysis keeping in mind we have essentially described the application of an unweighted, multiple span, moving binomial test to identify REBs.

For each dataset, we calculated a global average proportion of mismatching reads, and used the binomial test to identify stop codon nucleotides whose individual proportion of mismatches significantly deviated from the corresponding global average.

In an attempt to account for the effects of biological variability within our data, we chose a dispersion value of 0.3, which is between the recommended values as outlined in the edgeR user's guide [ 35] and applied exact negative binomial tests to identify differentially expressed genes.

In contrast, DESeq and edgeR estimate the means and variances of raw read counts under a negative binomial distribution and use exact tests to identify differentially expressed transcripts.

In contrast, DESeq, edgeR and EBSeq estimate the means and variances of raw read counts under a negative binomial distribution and use exact tests to identify differentially expressed transcripts.

This study introduces a formal statistical test known as the "C test" to determine when there is a need to apply the beta-binomial test instead of the binomial test to screen a roadway network.

We used an exact binomial test to examine the significance of overlap between LRES or LREA regions and earlier or later domains.