poisson distribution

[tinacai]

I want to ask a problem
the function of poisson distribution in paired end sequencing

[nilshomer]

I want to ask a problem
the function of poisson distribution in paired end sequencing

Please do not post duplicate questions to multiple forums as this becomes confusing when responding (which thread do I choose?).

Could you please be more specific in your question?

[tinacai]

poisson distribution

the poisson distribution is used by identical number of anomalously mapped read pairs in pair end sequencing
i want to know the result of the poisson distribution and the purpose of it

[nilshomer]

the poisson distribution is used by identical number of anomalously mapped read pairs in pair end sequencing
i want to know the result of the poisson distribution and the purpose of it

Do you want to know if it is reasonable to model the number of reads with the same start position using the Poisson distribution? "...the result of the poisson distribution and the purpose of it" does not make sense to me.

[spenthil]

I think she is referring to using distributions for determining read coverage...

Take a look at Figure. 3 in the Euler-USR paper: http://genome.cshlp.org/content/earl.../gr.079053.108

Figure 3: Choosing the multiplicity threshold for error correction. All k-mers appearing in the reads
are classified as correct if they appear in the genome and incorrect otherwise. For a multiplicity x,
let correct(x)/incorrect(x) be the number of correct/incorrect k-mers with multiplicity x (the plots
are shown for 50 base long Illumina reads from a human BAC and k = 20). As expected, most high-
multiplicity k-mers are correct and most low-multiplicity k-mers are incorrect. A Poisson/Gaussian
mixture model was fit to the distribution of all k-mer multiplicities in order to model the process
of generating incorrect (Poisson) and correct k-mers (Gaussian). To show the fit of the model,
the k-mer multiplicities were generated according to the estimated parameters =0.95, μ=25, and
=9.38, with a mixing parameter ! = 0.95. One may find the multiplicity m with good separation
between correct and incorrect k-mers by estimating the first local minimum from the distribution of
k-mer counts, or the minimum of the sum of the probabilities of the mixture model, a more smooth
distribution. For multiplicity threshold m=5, only 0.6% of correct 20-mers have multiplicity <5
and only 0.3% of incorrect 20-mers have multiplicity ≥5.