1) Write a R program to create a sequence of numbers from 20 to 50 and find the mean of
numbers from 20 to 60 and sum of numbers from 51 to 91
2) Write a R program to get the first 10 Fibonacci numbers
3) Write a R program to get all prime numbers up to a given numbe
4) Write a R program to print the numbers from 1 to 100 and print "Fizz" for multiples of 3, print
"Buzz" for multiples of 5, and print "FizzBuzz" for multiples of both
5) The below table shows the results of RNA-Seq on cancer samples being treated with three
different types of treatment (A, B, and P). You have a total of 12 samples, with four replicates
per treatment:
Sex Stage Treatment Myc
sample1 M I A 2343
sample2 F II A 457
sample3 M II A 4593
sample4 F I A 9035
sample5 M II B 3450
sample6 F II B 3524
sample7 M I B 958
sample8 F II B 1053
sample9 M II P 8674
sample10 F I P 3424
sample11 M II P 463
sample12 F II P 5105
− Transfer this table to excel and create a .xlsx file in your working directory.
− From the R program, import and read the created excel file (with any command you
think better suite your needs) and then save it in a data frame with the name
“RNA_Seq_Results”
− Using the RNA_Seq_Results data frame, write out the R code to perform the following
operations:
a. Define another data frame with the name “M_Data” that only includes the data in
columns two to four of RNA_Seq_Results data frame
. Use if and for commands only to extract all data in the M_Data data frame for those
samples receiving treatment P
c. Remove the treatment column from the RNA_Seq_Results data frame (hint: use [])
d. Add a column called pre_treatment to the beginning of the RNA_Seq_Results with
the values [T, F, F, F, T, T, F, T, F, F, T, T] (Hint: use cbind())
e. Use if and for commands only to calculate the minimum, maximum, and mean of the
numbers in the “Myc” column. DO NOT use ready functions such as min(), max(),
mean().
f. We want to write a program that can provide us with information about the Stage.
Cu
ently, our study only includes 12 samples, and it is easy to look at column 3 (i.e.,
stage column) to obtain the total number of samples that are in Stage I (4) or Stage II
(8). You agree that if the size of this table increases to include XXXXXXXXXXcases
instead of 12, then it is not as easy to do this task manually. Write an R script to
extract the total number of samples in Stage I or II.