Facilitating Data Analysis Through Ruby

1
Facilitating Data Analysis Through Ruby R
Interaction

• Rishi Gharpuray, James Woo, Carl Leonard and Jim
  DeLeo
• Scientific Computing Section
• Department of Clinical Research Informatics
• NIH Clinical Center
• National Institutes of Health
• Bethesda, Maryland

2
Objective

• To create and develop a software graphical
  module that uses Ruby code in Smart-MartTM, a
  software environment presently under development
  by the NIHCC Scientific Computing Section. Plots
  produced with this module should facilitate data
  analysis for biomedical research and promote the
  objectives of data mining and translational
  medicine.

3
Ruby Overview

• Ruby is an interactive web development
  language that is a combination of the classic C
  language and Perl, another programming language.
  Ruby is very easy to use compared to the
  syntactically complex and cryptic C and C. For
  Loops, instead of requiring all sorts of
  parentheses and uncommon characters, can simply
  be
• written as
• for..1 in 20 to go through for loops 20 times.

4
Ruby Overview Continued

• Ruby is easily upgradeable with Gems, which
  can conveniently be installed at the Command Line
  with the install name of gem command. Ruby
  Forge, an online website with forums and a
  variety of useful packages has become one of my
  best friends. http//rubyforge.org/

5
R Overview

• R is at first glance a very simple
  statistical language that can be used to plot,
  histograms, pie charts, bar graphs, line graphs,
  and the typical scatter plot with regression
  lines. After delving deeper into the language
  however, contours, density plots, complex
  histograms, and more reveal themselves.

6
Command Line Overview (cmd)-

• Most Windows users will be familiar with the
  command line, which can be called from Run as
  cmd. The two main commands essential to
  navigating with cmd are dir and cd, where dir
  refers to directory, and cd refers to jumping
  into a specific folder within the current
  directory.

7
Problems with Windows

• Installation of Ruby Gems became quite
  complicated on the Windows command line it was
  also unpredictable.
• Installation through windows can get
  mind-boggling and messy at times, and so a
  stronger command line, capable of executing all
  the installations would be much better. This is
  precisely why I turned to the Linux-base Ubuntu!

8
Why Linux and not Windows?

• There are so many software choices when it
  comes to doing any specific task. You could
  search for a text editor on Freshmeat and yield
  hundreds, if not thousands of results. My article
  on 5 Linux text editors you should know about
  explains how there are so many options just for
  editing text on the command-line due to the open
  source nature of Linux. Regular users and
  programmers contribute applications all the time.
  Sometimes its a simple modification or feature
  enhancement of a already existing piece of
  software, sometimes its a brand new application.
  In addition, software on Linux tends to be packed
  with more features and greater usability than
  software on Windows. Best of all, the vast
  majority of Linux software is free and open
  source. Not only are you getting the software for
  no charge, but you have the option to modify the
  source code and add more features if you
  understand the programming language. What more
  could you ask for? Ubuntu Website

9
Using Ubuntu

• Ubuntus webpage describes itself as a
  community developed, Linux-based operating system
  that is perfect for laptops, desktops and
  servers. It contains all the applications you
  need a web browser, presentation, document and
  spreadsheet software, instant messaging and much
  more. In addition, its is easy to download and
  upgrade, and best of all its free!

10
Connecting R and Ruby

• Our project in DCRI, is linked by the unifying
  language Ruby we are using this language to
  implement the SmartMartTM. My tasks here were
  heavily tied into the statistics language R,
  specifically. Hence, I had to find a way to
  connect the languages to maintain consistency.

11
RSRuby Gem

• This is essentially a bridge library that
  gives programmers in Ruby, access to the
  spectacular R environment. RSRuby embeds a full R
  interpreter inside the running Ruby script,
  allowing R methods to be called and data passed
  between the Ruby script and the R interpreter.
  Most data conversion is handled automatically,
  but user-definable conversion routines can also
  be written to handle any R or Ruby class.

12
R from Command Line

• Running R from the command line is a piece of
  cake, and is not difficult to do however, most
  important applications rely on scripts, or
  numerous lines of code, to accomplish a task. It
  is oftentimes more economical to open an editor
  software such as Nano or VI to write and execute
  an R script.

13
Editor Software-Nano

• Nano is a very easy editor to use, and can be
  opened with the simple command nano.
  Unfortunately, Linux protects access to such
  applications with a password. The prefix sudo
  must be inserted to access such applications. So,
  the sudo nano w command opens a save-able
  version of the source code file, which can be of
  any type, but will be either .r or .rb for my
  project.

14
RSRuby Produced Graphs

• The following code is all ruby code, but it
  executes R Commands! My comments, which for the
  non-coders are basically segments of code that
  are not executed and serve to help other
  programmers and viewers to comprehend the
  complexities of code, will help follow the
  complexities of code. Specifically, they are
  marked with a in ruby, as well as R. My task
  of producing these graphs, will be explained
  through these comments.

15
Ruby Code Segment 1

• GNU nano 2.0.7
  File rsrubyplots.rb
  
• The following two lines import two libraries
  into the code so that functions
• and variables defined in these two
  libraries, will be accessible to the code in
• this rsrubyplots.rb file.
• require 'rubygems'
• require 'rsruby'
• create a variable called R, that will be placed
  before R commands, and acts as the instance
  variable for R.
• r RSRuby.instance
• Create two arrays storing data elements!
• array1 r.c(1,2,3,4,5,6,7,7,8,5,4,3,23,2,4,5,6,77
  ,5,4,3,3,4,5,56,12,34,67,89,27)
• array2 r.c(2,3,4,5,6,7,8,8,6,6,5,4,4,3,23,2,4,5,
  6,6,45,4,4,3,5,6,43,3,4,80)

16
Scatter plot Command

• ylabel "Y-Axis (Dependent Variable)"
• xlabel "X-axis (Independent Variable)"
• title "Scatter Plot (Insert Title Here)"
• r.png(r.paste("/home/rgharpuray/scatterplot.png"))
  
• r.plot('x'array1,'y'array2,
• xlab' xlabel, 'ylab' ylabel, 'main'
  title)
• r.eval_R("dev.off()")

17
Pie Graph Command

• Pie graph command
• title "Pie Chart (insert Title Here)"
• r.png(r.paste("/home/rgharpuray/piegraph.png"))
• r.pie('x'array1,'labels'r.c("group1","group2"
  ,"group3","group4","group5","group6","group7","gro
  up8","group9","group10","group11, main
  title)
• r.eval_R("dev.off()")

18
Rnorm Command

• title "Rnorm(insert Title Here)"
• r.png(r.paste("/home/rgharpuray/rnorm.png"))
• data r.rnorm(100)
• r.plot('x'data,'xlab'xlabel,'ylab'ylabel,'m
  ain'title)
• r.eval_R("dev.off()")

19
QQPlot Command

• title "QQPlot Comparison of two
  Distributions(Insert Title here)"
• r.png(r.paste("/home/rgharpuray/qqplot.png"))
• r.qqplot('x'array1,'y'array2,'xlab'xlabel,'
  ylab'ylabel,'main'title)
• r.eval_R("dev.off()")

20
Histogram

• title "Histogram (Insert Title Here)"
• r.png(r.paste("/home/rgharpuray/histogram.png"))
• r.hist('x'array1, 'xlab'xlabel,'ylab'ylabel
  , 'col' "green", 'main' title)
• r.eval_R("dev.off()")

21

Text file,

table, ppt,

data base, etc.
Data from Researcher
Data Acquired
James Woos Module
Data structure and conversion to usable type
(array)
Data Managed, and Organized!
Data Plotted/Graphed!
22
Explanation of Big Picture

• The previous diagram summarizes how all of
  our projects come together to form an effective
  and interesting whole! Data is acquired from the
  biomedical researcher. Data may be in the form of
  a database, excel spreadsheet, text file, or
  more. My coworker James module converts this
  data to a more effective and usable method of
  storage, an array. It is in this form that my
  plotting commands come into play I take the
  reformatted data produced by James, and make
  plots out of them. Through this entire process,
  it is in our hope that the information and data
  acquired, can be more effectively used and
  applied!

23
Results/Conclusions

• Overall, my module has been a success, and
  produced a variety of graphs using a mixture of
  Ruby and R commands! Analyzing the data will be
  much easier and will produce interesting
  insights. Nevertheless, like many science
  experiments and computer programs, my modules
  took quite a while to perfect and make functional!

24
Acknowledgements

• My mentors Carl Leonard and Jim DeLeo, in
  conjunction with my coworker, James Woo, helped
  me complete my tasks and fix errors that
  presented themselves. I am very thankful to them
  for providing me with help this summer.
• Documentation for R in the introduction to
  R.pdf manual also helped me execute these R
  commands
• RSRUBY Documentation helped me recognize how to
  transition from R commands to Ruby commands

25
What I Learned and My Experience

• The internship this summer has taught me very
  much about several aspects of coding, about which
  I was originally oblivious or slightly perplexed.
  It was very entertaining as well as enlightening
  to see how all of our tasks, despite being
  independent, came together to form an amazing
  project! A big thanks to my coworkers, James Woo,
  Simone Campbell, and Morgan Clinton, as well as
  my mentors Carl Leonard and Jim DeLeo!

26
References

• McCown, Frank. "Producing Simple Graphs with R."
  2006-2007. 29 June 2008 ccown/r/.
• "Support." Ruby-Forge. 28 June 2008
  .
• Ubuntu. 05 June 2008 .
• Venables, W. N., and D. M. Smith. "An
  Introduction to R." R Project. 23 June 2008. 1
  July 2008 -intro.pdf.
• Warnes, Gregory R. "RSRuby Documentation." 2 July
  2008 /.

27
THE END

• Any questions, just shoot an email to me at
• rgharpuray_at_gmail.com
• or
• rishig_at_stanford.edu