1. Computational Biology
Dr. Jens Allmer
MBG404 Lecture Slides Week 3

2. Reminder Practice

3. Output Redirection (Win,nix)
Stores the output in a file
Creates a new file ‘> file path’
Appens to an existing or new file ‘>> file path’
Example
C:\ipconfig /all > res.txt
C:\route print >> res.txt
Output from ipconfig and route will now be in c:\res.txt
Pipes
Standard out (stdout) 1>
Standard error (stderr) 2>
B | A redirects stdout of B to stdin of A

4. Absolute Addressing
Specify the complete path starting with the drive letter
Example
C:\windows\system32\ipconfig.exe
?>ipconfig /all >> “C:\Documents and Settings\jens\res.txt”

5. Relative Addressing Specify directions to reach the file
Current directory is specified before >
Example
C:\Documents and Settings\jens> (abbrev. to ?> where ‘?’ can be any path)
Directions
Start from current directory
../ go to parent directory
/dir go into a child directory
?>ipconfig /all >> “../New Folder/test.txt”

6. Addressing
You can mix
Relative addressing
Absolute addressing
Make sure to quote parameters that contain whitespace
E.g.: “C:\Documents and Settings”
The redirection of output (pipe) can be anywhere on the commandline
E.g.: ipconfig /all >> res.txt
E.g.: ipconfig >> res.txt /all

7. Running JAVA Programs JAVA programs are not executed directly
They need the Java Virtual Machine (JVM)
Thus Java needs to be started instead of the program
Java programs often come as jar files
This can be passed to the JVM as a parameter
Example
Java.exe –jar DNATranslator.jar
Download from bioinformatics.allmer.de/tools
Programs available in JAVA
Many in all areas of biology

8. Running JAVA Programs Java jar files sometimes don’t have a main class
Then they can be run using class paths
Java –cp test
Java –cp FastaEditor.jar fastaeditor.FastaEditorFrm

9. | Forward the information from one command to the next (piping)
dir | find /I «searchstring»
Create two text files with some small differences
fc t1.txt t2.txt | find «searchstring»

10. Console Commands
<, >, >>
Pipe character: |
PATH variable

11. Batch Files Use notepad to write a text file
Change the text file to the extension .bat
How?
On the console using rename
Open the file in notepad and just type: dir
Save and close the file
Execute the file by double clicking
Execute the file from the console
Write a script that
Clears the screen
creates a new folder
Stores the output of ipconfig in the new folder
Searches for «10.» in the output file

12. End of Practice I
15 min break

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14. Median, Quartiles, Inter-Quartile Range and Box Plots.
Measures of Spread
Remember: The range is the measure of spread that goes with the mean.
Example 1. Two dice were thrown 10 times and their scores were added together and recorded. Find the mean and range for this data.
7, 5, 2, 7, 6, 12, 10, 4, 8, 9
Mean = 10
= 70 10
= 7
Range = 12 – 2 = 10

15. A reminder about the median
Median, Quartiles, Inter-Quartile Range and Box Plots.
Measures of Spread
The range is not a good measure of spread because one extreme, (very high or very low value) can have a big affect. The measure of spread that goes with the median is called the inter-quartile range and is generally a better measure of spread because it is not affected by extreme values.
A reminder about the median

16. Averages (The Median) Single middle value Ordered data
The median is the middle value of a set of data once the data has been ordered.
Example 1. Robert hit 11 balls at Grimsby driving range. The recorded distances of his drives, measured in yards, are given below. Find the median distance for his drives.
85, 125, 130, 65, 100, 70, 75, 50, 140, 95, 70
50, 65, 70, 70, 75, 85, 95, 100, 125, 130, 140
Ordered data
Single middle value
Median drive = 85 yards

17. Two middle values so take the mean.
Averages (The Median)
The median is the middle value of a set of data once the data has been ordered.
Example 1. Robert hit 12 balls at Grimsby driving range. The recorded distances of his drives, measured in yards, are given below. Find the median distance for his drives.
85, 125, 130, 65, 100, 70, 75, 50, 140, 135, 95, 70
50, 65, 70, 70, 75, 85, 95, 100, 125, 130, 135, 140
Ordered data
Two middle values so take the mean.
Median drive = 90 yards

18. Inter-Quartile Range = 9 - 5½ = 3½
Finding the median, quartiles and inter-quartile range.
Example 1: Find the median and quartiles for the data below.
12, 6, 4, 9, 8, 4, 9, 8, 5, 9, 8, 10
Order the data
Lower Quartile = 5½ Q1
Median = 8 Q2
Upper Quartile = 9 Q3
4, 4, 5, 6, 8, 8, 8, 9, 9, 9, 10, 12
Inter-Quartile Range = 9 - 5½ = 3½

19. Inter-Quartile Range = 10 - 4 = 6
Finding the median, quartiles and inter-quartile range.
Example 2: Find the median and quartiles for the data below.
6, 3, 9, 8, 4, 10, 8, 4, 15, 8, 10
Order the data
Lower Quartile = 4 Q1
Median = 8 Q2
Upper Quartile = 10 Q3
3, 4, 4, 6, 8, 8, 8, 9, , 10, 15,
Inter-Quartile Range = = 6

20. Discuss the calculations below.
2, 5, 6, 6, 7, 8, 8, 8, 9, 9, 10, 15
Median = 8 hours and the inter-quartile range = 9 – 6 = 3 hours.
Battery Life: The life of 12 batteries recorded in hours is:
Mean = 93/12 = 7.75 hours and the range = 15 – 2 = 13 hours.
Discuss the calculations below.
The averages are similar but the measures of spread are significantly different since the extreme values of 2 and 15 are not included in the inter-quartile range.

21. Boys Girls Box Plots Box and Whisker Diagrams. 4 5 6 7 8 9 10 11 12
130
140
150
160
170
180
190
Boys
Girls cm
Box and Whisker Diagrams.
Box plots are useful for comparing two or more sets of data like that shown below for heights of boys and girls in a class.
Anatomy of a Box and Whisker Diagram.
Lowest Value
Lower Quartile
Upper Quartile
Highest Value
Median
Whisker
Box 4 5 6 7 8 9 10 11 12
Box Plots

22. 4, 4, 5, 6, 8, 8, 8, 9, 9, 9, 10, 12
Example 1: Draw a Box plot for the data below
Drawing a Box Plot.
Lower Quartile = 5½ Q1
Upper Quartile = 9 Q3
Median = 8 Q2 4 5 6 7 8 9 10 11 12

23. 3, 4, 4, 6, 8, 8, 8, 9, , 10, 15,
Example 2: Draw a Box plot for the data below
Drawing a Box Plot.
Upper Quartile = 10 Q3
Lower Quartile = 4 Q1
Median = 8 Q2 3 4 5 6 7 8 9 10 11 12 13 14 15

24. Question: Stuart recorded the heights in cm of boys in his class as shown below. Draw a box plot for this data.
Drawing a Box Plot.
137, 148, 155, 158, 165, 166, 166, 171, 171, 173, 175, 180, 184, 186, 186
Upper Quartile = 180 Qu
Lower Quartile = 158 QL
Median = 171 Q2
130
140
150
160
170
180
190 cm

25. Drawing a Box Plot. Boys Girls
2. The boys are taller on average.
Question: Gemma recorded the heights in cm of girls in the same class and constructed a box plot from the data. The box plots for both boys and girls are shown below. Use the box plots to choose some correct statements comparing heights of boys and girls in the class. Justify your answers.
Drawing a Box Plot.
130
140
150
160
170
180
190
Boys
Girls cm
1. The girls are taller on average.
3. The girls show less variability in height.
4. The boys show less variability in height.
5. The smallest person is a girl.
6. The tallest person is a boy.

26. End of Theory I
Mind map 5 min
Break 10 min

27. Practice II

28. Konstanz Information Miner
We will use the Workflow Management and Data Analytics Platform
First we need to find out how to get our data into KNIME

29. Create Data Use Excel to create two colums Girls, boys
Make a few hundred random numbers (randbetween)
for girls
for boys
Copy the table
Paste into Notepad++
Save as Distribution.txt

30. KNIME Data Import Open Knime
Select the folder containing the data as workspace
Right click LOCAL
Select new workflow
Name it HeightAnalysis
Drag and Drop Distribution.txt into the workflow

31. Box Plot Type box to find box plot node Double click
Right click Box Plot node
Select Execute and open views
Done

32. Workflow