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Utilizing GC Content to Differentiate Phytophthora from Tomato Sequences

Calculate and analyze the GC content of Phytophthora-tomato interactome sequences using Perl and R scripts, followed by creating a histogram for visualization. Follow step-by-step instructions to complete the mission successfully.

pmarvin
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Utilizing GC Content to Differentiate Phytophthora from Tomato Sequences

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  1. Using GC content to distinguish Phytophthora sequences from tomato sequences

  2. Mission #1 Calculate the GC content of each sequence in the Phytophthora-tomato interactome We will use a perl script to accomplish the mission.

  3. Preparation • Download the perl script (gc.pl) from the class web site and store it in C:/BioDownload folder

  4. Running the script • Open cygwin, or command prompt (Vista users), or terminal (Mac users) • Change directory (cd) to the BioDownload folder • perl<space>gc.pl<space>PhytophSeq1.txt<space>phyto_gc.out

  5. Results In cygwin (Windows users) or terminal (Mac users) grep<space>--perl-regexp<space>”\t”<space>-c<space>phytoph_gc.out grep<space>”>”<space>-c<space>PhytophSeq1.txt You should get the same number from the two commands. The number should be 3921.

  6. The output file Name column GC content column

  7. Mission #2 Build a histogram of the values of GC content We will use R program to accomplish this mission.

  8. http://www.r-project.org

  9. Mac users

  10. All Windows users

  11. XP users Vista users

  12. getwd() to know which folder you are in now

  13. setwd(“c:/BioDownload”) to change the working directory to C:/BioDownload setwd(“/path/to/biodownload”) for Mac users

  14. data<-read.table(“phytoph_gc.out”,sep=“\t”,header=FALSE)data<-read.table(“phytoph_gc.out”,sep=“\t”,header=FALSE) to read in the data in the file phytoph_gc.out (your file name may be different)

  15. data[1:10,] to see the first 10 lines of the vector “data”

  16. gc<-data[,2] to assign the values from the 2nd column of “data” to a new vector “gc”

  17. summary(gc) to get the summary of the values in the vector “gc”

  18. hist(gc,breaks=58) to draw a histogram of the values in “gc” vector Breaks indicates how many cells you want for the histogram. It was calculated as 78.7 (max) - 21.2 (min). It means the bin of the histogram is ~ 1 GC value

  19. hist(gc,breaks=58,xlab=“GC content”,ylim=range(c(0,400)),main=“Histogram of GC content of sequences\ninPhytophthora-tomato interactome”) to make the histogram look better

  20. >pdf(“gc_histogram.pdf”) >hist(gc,breaks=58,xlab=“GC content”,ylim=range(c(0,400)),main=“Histogram of GC content of sequences\ninPhytophthora-tomato interactome”) >dev.off() To output the histogram to a PDF file.

  21. location file

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