Sentence examples for binomial distribution model and from inspiring English sources
P values were estimated using a negative binomial distribution model and local regression to estimate the relationship between the dispersion and the mean of each miRNA.
edgeR finds changes between two or more groups when either or both groups contain replicates, by using a negative binomial distribution model and estimating genewise dispersions based on conditional maximum likelihood [ 48- 50].
These packages are based on a negative binomial distribution model of read counts [ 39] and include edgeR [ 32], DESeq [ 25] and NBPSeq [ 33].
The R (version 2.15.2) Bioconductor package EdgeR (v2.4.6) (Robinson et al. 2010), which uses a negative binomial distribution model to account for both biological and technical variability, was applied to identify statistically significant differentially expressed (DE) genes.
Size factors for each dataset were calculated to normalize library sizes across replicates, and overall means and variances were determined using a negative binomial distribution model.
The negative binomial distribution model used in this study showed differences between the observed and expected values within some risk factor categories analyzed.
To further evaluate whether the observed amino acid preference (or depletion) is statistically significant, we set up a binomial distribution model for each amino acid at each position of T4S and non-T4S C-terminal 50 positions.
Separate sequence read datasets were used as inputs into the DESeq package where size factors for each dataset were calculated and overall means and variances were determined based on a negative binomial distribution model.
Distribution of mutations among CDR and FR gene segments was evaluated by the Chang Casali binomial distribution model [46].
The statistical significance in Peptide-to-MS2 scoring for both targeted and decoy peptide models was evaluated by implementing the negative binomial distribution model.
We propose a new collection frequency weighting scheme derived from the negative binomial distribution model of term occurrences.
