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An approximate confidence interval for sequence saturation is derived using a binomial probability model and is given by μ ± 2 μ 1 − μ n, where μ is a given standard methylation ratio, and n is the number of sequenced reads covering the region of interest.
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To test whether the sex ratios among the Norwegian-Indian births were significantly different from the average sex ratio of all Norwegian births we used a binomial probability model analysing each period and each birth order separately.
For each site an unambiguous base was called if the bases present were identical or if the polymorphism of that site could be explained as sequencing error, assuming a binomial probability model with the probability of error equal to 0.1 and alpha equal to 0.05.
Using a conventional binomial probability model, several genes were found mutated significantly.
A binomial probability model was used to evaluate whether the excess of replacement (R) mutations in CDR or their scarcity in FR was due to chance.
In order to reduce the influence of missing data, we excluded pathways whose members were not significantly detected by GPL96 platform by using the binomial probability model.
Utilising a binomial probability model we tested whether the observed sex differences among Indian-born women were significantly different from sex differences among all births.
To compute the tract-level likelihoods P(c i | H0, G, M) and P(c i | H1, G, M, r), BARD employs the binomial probability model (see [ 3, 10] for more details).
The empirical calculations are compared to confidence intervals based on the binomial probability model; for a standard methylation ratio of 0.5, the binomial-based confidence interval reduces to 0.5 ± 1 n.
Similar to zero-inflated models, hurdle models are two part models which estimate both a binomial probability and a count model (McDowell, 2003).
*Adjusted difference and its 95%CI are calculated from a generalized linear model with a binomial probability function and an identity link.
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