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We have now stated that a binomial test is used for pathway enrichment analysis in the "Pathway analysis features" section and cited a reference (reference 8) for it.
The problem of comparing count data between samples with different read depths while assuming overdispersed Poisson variation is related to that presented by differential expression analysis of RNA-seq data, for which a negative binomial test is used.
To identify REBs from ordered gene expression data, rather then a use an averaging function to evaluate each window span, an approximated binomial test is used to estimate of the probability, in terms of a z-score, that a gene expression bias exists within each span (see Materials and Methods).
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The exact binomial test was used to compare US state-level application use to the mean.
As binary data (ingested or rejected) was collected in the present study, the one-tailed binomial test was used to determine the significance of difference among the treatments.
As the feeding response observed was a binary data (ingested or rejected the TS pellet), binomial test was used for the data statistical analysis.
A binomial test was used to check this assumption.
Repeated measures ANOVAs or a sign test (two-tailed binomial test) were used for statistics.
A one tailed binomial test was used to determine whether the niche model outperformed a random model predicting the vector to be present in the same number of cells [11].
The binomial test was used to compare the observed frequencies of male and female neonates.
The binomial test was used to statistically determine over-representation of PANTHER classification categories [ 33].
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