Bioinformatics for geneticists essay

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Bioinformatics for geneticists essay

Detailed feedback about statistics in a critical review Michael McCarthy says: This paper by Amrhein et al. The example concerns a woman who is carrying twins, both male as determined by sonogram and we ignore the possibility that gender has been observed incorrectly.

The parents-to-be ask Efron to tell them the probability that the twins are identical. Read full report This paper by Amrhein et al.

But given that there appears to be errors in both Efron b and the paper under review, I am sorry to say that my review might actually be longer than the article by Efron athe primary focus of the critique, and the critique itself.

I apologize in advance for this. To start, I will outline the problem being discussed for the sake of readers. This problem has various parameters of interest. The bone of contention in the Efron papers and the critique by Amrhein et al.

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The paper by Amrhein et al. Apparently, the doctor knows that one third of twins are identical 2. In contrast, Amrhein et al. No one is violating logic — they are merely expressing ignorance by specifying equal probabilities to all states of nature.

Bioinformatics for geneticists essay

Whether this is philosophically valid is debatable Colyvanbut this example does not lend much weight to that question, and it is well beyond the scope of this review. Now the problem has two aspects that are uncertain.

Uncertainty in the state of x refers to uncertainty about this particular set of twins. A key point is that the state of one particular set of twins is a different parameter from the frequency of occurrence of identical twins in the population.

Alternatively, Efron b notes another alternative for an uninformative prior: Here I disagree with Amrhein et al. Although there is one data point a couple is due to be parents of twin boys, and the twins are fraternalEfron does not use it to update prior knowledge.

The data about the twin boys is not useful by itself for this purpose — they are a biased sample the data have come to light because their gender is the same; they are not a random sample of twins.

Bioinformatics for geneticists essay

Further, a sample of size one, especially if biased, is not a firm basis for inference about a population parameter. While the data are biased, the claim by Amrheim et al.Bioinformatics for Geneticists: A Bioinformatics Primer for the Analysis of Genetic Data Andrew D.

Johnson PhDFramingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Mass.

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Bioinformatics for Geneticists: A Bioinformatics Primer for the Analysis of Genetic Data Amazon Praise from the reviews: "Without reservation, I endorse this text as the best resource I've encountered that neatly introduces and summarizes many points I've learned through years of experience.

Bioinformatics for Geneticists: A Bioinformatics Primer for the Analysis of Genetic Data Andrew D. Johnson PhDFramingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, Mass. Bioinformatics. By. Thanh Nguyen. Grace Duncan. Genetics Lab Section #1. Abstract: In this lab investigation, an unknown sequence is given and by using specific techniques, the sequence can be identified and to which organism it belongs without laying a hand on a pipette/5(13).

Bioinformatics for geneticists describes the key bioinformatics and genetic analysis processes that are needed to identify human genetic determinants. Including SNP .

Compare and Contrast the Genomics Revolution with the Molecular Revolution. free essay