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r_test [2021/05/16 15:19] – [Question 2] adminr_test [2021/10/14 20:08] (current) – [Question 3] admin
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 **An R test** \\ **An R test** \\
-These simple questions are designed to test the applicants on their expertise in R, self learning, working under pressure, presenting their results, and explaining their work.+These simple questions are designed to test the applicants on their expertise in R, self learning, working under pressure, presenting their results, and explaining their work. If you get help from people and internet, please include the person's name and the link to the webpage in your answers.
  
 ==== Question 1 ==== ==== Question 1 ====
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 +==== Question 3 ====
  
-==== Question 3: ==== +**A)** Using the [[https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html|maftools]] and [[http://bioconductor.org/packages/release/bioc/html/TCGAbiolinks.html|TCGAbiolinks]] packages, determine the 3 most frequently mutated genes in liver cancer. Which of these 3 mutations is more predictive of survival? To answer this question, write a function that takes as input a gene name, and save KM plots in png format. Add the p-value as a legend in the plot. Deliverables are similar to question 2.
- +
-**A)** Using the [[https://bioconductor.org/packages/release/bioc/vignettes/maftools/inst/doc/maftools.html|maftools]] and [[http://bioconductor.org/packages/release/bioc/html/TCGAbiolinks.html|TCGAbiolinks]] packages, determine the 3 most frequently mutated genes in liver cancer. Which of these 3 mutations is more predictive of survival? To answer this question, write a function that takes as input a gene name, and save KM plots in png format. Add the p-value as a legend in the plot. Deliverables are similar to question 1.+
  
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 Write a function ''most.impact()'' that takes as input two ''k1'' and ''n1'' integers, and in the list of ''n1'' most mutated genes, finds the names of the ''k1'' genes with the best impact. Your function should return the names of the best ''k1'' genes (i.e., the set of genes with the best log-rank p-value), and also their impact. Run your function for ''k1=3'', and ''n1=3'', ''10'', and ''100''. What is the biological interpretation of your results? Write a function ''most.impact()'' that takes as input two ''k1'' and ''n1'' integers, and in the list of ''n1'' most mutated genes, finds the names of the ''k1'' genes with the best impact. Your function should return the names of the best ''k1'' genes (i.e., the set of genes with the best log-rank p-value), and also their impact. Run your function for ''k1=3'', and ''n1=3'', ''10'', and ''100''. What is the biological interpretation of your results?
  
-__Hint:__ Use the ''utils::c?m?n()'' function, where you need to guess the question marks.+__Hint:__ Solution 1: Use the ''utils::c?m?n()'' function, where you need to guess the question marks.\\ 
 +Solution 2: Use another R function that uses ''utils::c?m?n()''. 
 + 
 +Deliverables are similar to question 2 plus you need to guess the above question marks and copy the line of the code on which ''c?m?n()'' is used in a short paragraph titled “Question marks”.
  
 **Bonus**: Implement the ''utils::c?m?n()'' function yourself using dynamic programming. Compare the running time of your implementation vs. the utils implementations using large inputs that require at least a couple of minutes. **Bonus**: Implement the ''utils::c?m?n()'' function yourself using dynamic programming. Compare the running time of your implementation vs. the utils implementations using large inputs that require at least a couple of minutes.