Sentence examples for model the read from inspiring English sources

This method was based on a negative binomial distribution model; the read count of gene i in the sample of j was designated Kij.

We used both the negative binomial and the normal distribution to model the read count data.

The Poisson distribution has been widely used to model the read count feature of RNA-seq and ChIP-seq data.

We model the read counts with the negative binomial distribution after correcting for the effect of genomic deadzones.

We expect the observed count for bin i to be distributed around this value times the effective length of the bin l i, and therefore model the read count y i as a Poisson random variable with parameter δ i = l i ∑ j = 1 m U j i θ j.

We use the NBDiff distribution to model the read count difference between the two samples, and employ three-state HMM: where the basal state means these two signals are similar, the second state represents the signal in test sample A is greater than that in the test sample B and the third state represents the opposite case (details given in Supplementary Section S2.1).

Because A. thaliana was known to be most distantly related to the other taxa and should thus be equally related to all of them under a bifurcating speciation model, the reads were mapped to the A. thaliana reference genome.

For our own model the reads were aligned using segemehl.

Our model incorporates the read information in a probabilistic model through base quality scores within each read.

The observed data of the model are the read sequences, which we represent by the R n random variables.

Inferred relative expression is represented by Markov chain Monte Carlo samples from the posterior probability distribution of a generative model of the read data.