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poisson distribution
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the function of poisson distribution in paired end sequencing
the function of poisson distribution in paired end sequencing
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Please do not post duplicate questions to multiple forums as this becomes confusing when responding (which thread do I choose?).Originally posted by tinacai View Post
Could you please be more specific in your question? -
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 itComment
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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.Originally posted by tinacai View PostComment
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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.--
Senthil PalanisamiComment
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...06-18-2026, 07:11 AM -
Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
...06-02-2026, 10:05 AM
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