How to apply probabilistic method to call variants in a simple example.
I am trying to understand how the Bayes' theorem is applied on probabilistic methods to infer a variant called from NGS alignment reads. I understand the basics of the Bayes' theorem but not as much I would like because when I tried to applied in a simple example I can't. I mean, I am not able to see how to calculate the probability that the variant called in the following example is T applying the Bayes' theorem
—-----------------T—----------------
—-----------------T—----------------
—-----------------T—----------------
—-----------------C—----------------
—-----------------T—---------------- 7 Aligned Reads
—-----------------C—----------------
—-----------------C—----------------
—-----------------T—---------------- Reference
0 answers
No answers yet.
Log in to answer this question.
More posts like this
-
Why do the same genetic variants sometimes result in different amino acids in the REVEL table?
written by ManuelDB
-
Are not all duplicated reads removed when applying removal duplicated algorithms?
written by ManuelDB
-
How to evaluate which genome reference and alignment tool is "the best" for my pipeline?
written by ManuelDB
-
I can't understand my sam files
written by ManuelDB
-
Diploid vs Haploid calls
written by Ghani •
-
Difference Between GATK, Freebayes and SAMtools mpileup
written by manojkumarbioinfo
-
(samtools) Filtering and interpreting >100 QUAL scores
written by umn_bist •
-
How does GATK PhaseByTransmission define the phasing of Father and Mother?
written by shajib.sust •
-
Conditional Probability Model for a Bacterial Species/Genus
written by anthony.gough •
-
How To Calculate Genotype Likelihood Using Quality Scores For Reads
written by Mcmahanl
