First Morning, Introductions, and Lesson Plans

Your instructors are: Aisha Ellahi, Sara Branco, Melinda Yang, James Hart, and Courtney French.

Your teaching assistants are: Christopher Hann-Soden, Emily Brown, Fernando Racimo, Gavin Schlissel, and Jeffrey Spence.


  • Expectations for the course
  • Navigating the UNIX shell
  • Viewing the content of files
  • How to get help
  • Text editors


Welcome to the QB3 Introduction to Programming for Bioinformatics bootcamp!

Overview for today:

1) Introduce the instructors and TAs.
2) What should you expect to learn from this course.
3) What we are not going to cover.
4) How the class will be organized, including the instructors and TAs, and the main changes for this year.
5) Learn a little about how to function in a UNIX environment.

What are you going to learn?

You are going to learn python :O)

Python is a simple and powerful programming language that is used for many applications, from
simple tasks to large software development projects. It has become popular as both a first language
for beginning students and an everyday one for advanced programmers. Python is used by a range
of companies including Netflix, Google, Microsoft, YouTube, and Industrial Light & Magic.

Our goal is to allow you to apply programming to the problems that you face in the lab. Although we
will only directly cover a couple application areas of programming to biology, our aim is for you to
leave this course with a sufficiently generalized knowledge of programming (and the confidence to
read the manuals) that you will be able to apply your skills to whatever you happen to be working

What are you not going to learn?

Issue 1: Learning to program is a lot like learning a new language. It requires adjusting the way you
think about solving a problem and communicating that solution. Even more confusing, each
programmer develops his/her own style (accent). In practice, this means that there is almost never a
"RIGHT ANSWER," but rather that there are almost infinite ways to solve almost any problem. In the
course of the class, you will be exposed to several styles and see several ways to get to more
complicated solutions. The goal, though, is to give you the tools to begin to develop a style of your
own. Later on, you may also want to read PEP 8, which is a style guide for Python, much like the
vaunted Strunk and White is a style guide for English.

Issue 2: Python is big. Thousands of lab scientists, computer scientists, and programmers have
used it, contributed to it, and extended it to their own sub-fields. And they keep improving, and thus
changing it! We can't get to all of it, even if we had much longer than two weeks. Included in the list
of subjects we will not cover in any depth is object-oriented programming, writing parallel programs,
integrating your code with faster code written in C or C++, or a host of other powerful-but-subtle
methods and topics. We will teach you enough that you should be able to go learn about them if and
when you want.

Issue 3: Python is evolving. At the moment, there are two major versions of Python available: Python
2.7 and Python 3.4. In this course, we'll be using Python 2.7. Why aren't we using the more up-to-
date Python 3? There's a bit of history: For most of Python's lifetime, each new version of the
language would introduce new features, but would try very, very hard to not break any code that
other people had already written; in other words, most changes were backwards compatible. In
about 2006, however, Python's creator and "Benevolent Dictator For Life" Guido van Rossum
decided that there were a number of things that he had gotten wrong in the original Python
specification, and would like to change. Making those changes would break other people's code, so
it was decided to make them all at once. Although that version was released almost 5 years ago,
there are still some add-ons to the core language that haven't completely switched (though this
number is decreasing constantly). The number of "gotchas" between Python 2 and 3 is relatively
small, and we'll try to point out where there are differences, so if you do decide to make the leap,
things should go relatively smoothly.

How are you going to learn it?

This year, we've introduced a new change in how the course is typically run: we've doubled the class size. Historically, this has been a small class of about 25-30 students, in an intimate classroom setting, where the students got a lot of one-on-one time with instructors and TAs. While that format works great, the downside was the class size. Every year, we get over a hundred responses to our course announcement, and as you may have found from experience, spaces fill up FAST. Clearly, this class is in high demand, and this year, we decided to cut into that demand and see how well a larger class would work. The good news is that we've been able to enroll more students. The bad news is that each of you gets less one-on-one time with us and there are fewer TAs to go around. Unfortunately, you are the guinea pigs, and we ask that you be patient with us in working through the rough patches that we'll likely encounter. Every year, there are rough patches particular to that year; this year will be no different, and we ask that everyone be patient in trying to implement a larger class size.

The course is broadly divided into two parts.

Week 1: Learning Python Basics

In the first week of the course we will learn the very basics of programming practice and the
fundamentals of Python syntax, including:

- how to get information from files
- how to store information
- how to do interesting and complicated things with the information
- how to print information back out
- how to incorporate other people's code to do more faster, with less effort

Week 2: Python Applied to Bioinformatics

In the second week, we will use real data from several published studies on high-throughput sequencing for a range of biological applications. The second week will show us:

- how to build and manage a data analysis pipeline
- how to call other programs from within our Python code
- how to perform complicated scientific data analysis
- how to visualize our data
- a selection of other people's code that we find is particularly useful for biologists

Our daily schedule will generally proceed like this:

Start at 8:30 am
1-2 hour lecture
2-2.5 hours lab for exercises

Lunch from 12:15 - 1

1-2 hour lecture
2-3 hours lab for exercises
Leave at 5 pm

You will have a number of exercises each day covering the breadth of the lectures. You will not be
graded on these but it's REALLY important for you to be able to demonstrate what you've just
learned. Just like learning French, one learns programming by doing. If you only finish half the
problems, you've only really learned half the material. You get what you put in.

Coding has a steep learning curve!

Learning to program is really HARD! REALLY! Don't worry if you get frustrated or fall behind. Try to remember that
python is a logic-based language and that you can reason your way around most problems we will
be posing in the next two weeks. We have also posed some of these problems precisely because
things may not work the way you were expecting. Ask questions! The idea is to get you to the point
of being able to solve real problems in lab and to give you some tools to learn more on your own.

You have two incredibly useful resources at your disposal during the labs: first, you have us, the
TAs and instructors, who are all familiar with the language and here to help you out. Second, you
have the extensive documentation about python and programming that we will be introducing you to
in the course of the class.

You can also access some resources here:
Learning Python
Python Pocket Reference
Python Website (documentation)
Linux Pocket Guide
Python Code Visualization


Using the UNIX shell

You will spend nearly all of your time in one of three places: the shell, the text editor, or the
interactive interpreter. The shell allows you to move and copy files, run programs, and more, while
the text editor is where you will write your programs. We will focus mostly on the shell this morning,
although we will touch on the basic usage of a popular text editor, aquamacs. We will begin Python this
afternoon. We'll cover the interactive interpreter, which is another powerful tool, later on in the

A large fraction of what you can do in the shell (sometimes also called the "command line") can be
done using the windowed operating system you're used to. While for the simplest of tasks, the
command line may seem like a step backwards, for anything even mildly more complicated ("move
every file with 2012 anywhere in its name to the folder Backup"), it can save a lot of time. And then
there are the programs that can only be run from the command line, which are much easier to write
and more flexible in what they can do.

Informative Interlude: Some notes on the formatting of the lessons for this course

Periodically in these lessons, we may stop with an informative interlude outlined with a horizontal
line above and below (like the one two lines up!). In this case, we're taking a quick break to discuss
this and other aspects of the formatting.

For this and all further examples, a $ represents your shell prompt, and boldface indicates the
commands to type at the prompt. Italics will be used for output you should see when you take the
described action.

Finally, when we use actual python code examples, they will be contained in the shaded boxes,
such as:

This is where code will appear.

You'll notice that some of the words are in different colors. These words mean special things in
Python, and the wiki software understands that, and will color the code to make the structure more
clear. Many editors also have a "syntax highlighting" feature, and this can actually be a useful hint
when something inevitably goes wrong.

This concludes our first informative interlude.

Let's start by opening a new terminal window...

How do I move around?

One of the basic concepts is that your shell is always based somewhere in the directory structure.
An analogy here is if you have only a single window open (e.g. in the Finder on a Mac, or the
directory browser in Linux).

[where am I?]
(Print Working Directory) Prints the directory in which you are at the current moment. If you create
any files, they will appear in this spot. When you first open the terminal shell, you will be in your
"home" directory.

$ pwd

[move to a new directory]
(Change Directory) Given a path, this command moves your "current location" to the specified directory.

$ cd PythonCourse

$ pwd

To go up, use the command cd ..

$ cd ..
$ pwd

Thus far, these have been relative paths (i.e. relative to your current directory), but you can also use
an absolute path (which will start with a /):

$ pwd
$ cd /Library/Frameworks/Python.framework/Versions/Current/bin/

A shortcut for your home directory is ~:
$ cd ~
$ pwd

And you can use these as part of a path as well:

$ cd ~/Documents/MCB240/

Another way to get to the home directory is to simply type "cd":

$ cd
$ pwd

An aside on directories...
Directories in UNIX are set up the same way as your regular computer. Just as you would open up
a window into your directories and click to open up folders, here you use cd to go through the
directories. You are just typing the command instead of clicking!

ls directory_path
[lists contents of a directory] (LiSt) Shows the files and directories.

$ cd ~/Documents/MCB240
$ ls
MCB240 Midterm AE.doc

ls has many options. Here are some of the more useful ones to know:

ls -l
[lists the long form of the directory entries' security permissions, owners of files, sizes, date created]

ls -lh
[lists the long form of the directory entries, but with the sizes in a human-readable format (i.e. MB and GB instead of the number of bytes)]

ls -lt
[shows long listing, and sorts by modification time]

ls -lr
[reverses the list]

ls ..
[list contents of the directory above]

[list contents in the directory specified by A_PATH, which can be either relative or absolute.]

$ ls -ltr
-rw-r--r--@ 1 aishaellahi85 staff 136002 Sep 21 2010 MCB240ExamPractice.docx
-rw-r--r--@ 1 aishaellahi85 staff 40960 Sep 28 2010 MCB240 Midterm AE.doc
-rw-r--r--@ 1 aishaellahi85 staff 178763 Sep 30 2010 MCB240RineMidtermAnswers.docx
-rw-r--r--@ 1 aishaellahi85 staff 150748 Nov 3 2010 MCB240Midterm2.docx

Making your mark...

$ cd PythonCourse

mkdir directory_name
[Create a given directory](MaKe DIRectory) Exactly what it says - let's you create new directories.

$ mkdir S1.1
$ cd S1.1
$ echo 'Hello World' > python_notes.txt
$ ls
$ mkdir data
$ ls
data python_notes.txt

cp original_name copy_name
[copy file or directory](CoPy) Create a copy of the original file$

$ cp python_notes.txt python_notes2.txt
$ ls

echo 'To Do' > project_notes.txt
$ ls

$ cp project_notes.txt backup.txt
$ ls

mv source destination
[move files or directories](MoVe) Rename a file or directory. Renaming is the same as moving within the same directory.

$ mv backup.txt project_notes.txt

$ ls

Peeking inside files

less file_name
[view contents of a file] less shows the contents of a file, and allows you to scroll and search the
contents. However, less can only be used for simple text files, so you cannot reliably view contents
of, say, MS Word documents with less. Fortunately, most of the files we'll be dealing with will be
plain text files

So let's quickly create a text file called "pythons_of_the_world.txt" by copying and pasting the wikipedia entry on pythons into a new text file. To read into this file, type:

$ less pythons_of_the_world.txt

From Wikipedia, the free encyclopedia
Python molurus molurus 2.jpg
Indian python, Python molurus
Scientific classification
Kingdom: Animalia
Phylum: Chordata
Subphylum: Vertebrata
Class: Reptilia
Order: Squamata
Suborder: Serpentes
Infraorder: Alethinophidia
Family: Pythonidae
Fitzinger, 1826

Pythonoidea - Fitzinger, 1826
Pythonoidei - Eichwald, 1831
Holodonta - Müller, 1832
Pythonina - Bonaparte, 1840
Pythophes - Fitzinger, 1843
Pythoniens - A.M.C. Duméril & Bibron, 1844

Some useful navigational tips for less:
- Use the "enter" key to progress one line at a time through the text.
- You can use the arrow keys to move up or down a line in the text.
- The spacebar will advance an entire page.
- You can search for a word by typing a slash (e.g. /) followed by the search word.
- To quit, type q.
- To see the full help screen, type h.

Optional Informative Interlude: UNIX names tend to be overly clever.

As you've seen with the basic commands thus far, the names are generally descriptive abbreviations of the program's function. For example, mkdir is for making a directory, ls is for listing the contents of a directory, etc. However, programmers, especially UNIX programmers, tend to get increasingly clever as things progress. Unaware of the fact that this practice makes things opaque, the typical programmer cries out for attention by making program names self-referentially clever. less is a good example of this. In the olden days, the most basic ways to view a text file could not divide files into individual pages, thus a multipage document would scroll off the screen before the first page could be read. As a solution, a program called more was written, which paused at the bottom of each page and prompted the user to press the spacebar for "more." The program name here is reasonably descriptive, but more had some noticeable feature deficiencies: you could neither advance the text one line at a time nor navigate backward in the document without reloading the whole file. The program written to accommodate these features is less. The cleverness of the name is revealed by the paradoxical adage "less is more ." Your teachers and TAs may use the more command interchangeable with less throughout the class.

head filename
[print first 10 lines of the file]

By default, head prints the top 10 lines of the input file. To print a different number, say 12, lines:
$ head -n 12 filename
$ head pythons_of_the_world.txt
From Wikipedia, the free encyclopedia
Python molurus molurus 2.jpg
Indian python, Python molurus
Scientific classification
Kingdom: Animalia
Phylum: Chordata
Subphylum: Vertebrata
Class: Reptilia


tail filename
[print the last ten lines of the file]

$ tail pythons_of_the_world.txt
"Pythonidae". Integrated Taxonomic Information System. Retrieved 15 September 2007.
"Huge, Freed Pet Pythons Invade Florida Everglades", National Geographic News. Accessed 16 September 2007.
Hardy, David L. (1994). "A re-evaluation of suffocation as the cause of death during constriction by snakes". Herpetological Review 229: 45-47.
Mehrtens JM. 1987. Living Snakes of the World in Color. New York: Sterling Publishers. 480 pp. ISBN 0-8069-6460-X.
Stidworthy J. 1974. Snakes of the World. Grosset & Dunlap Inc. 160 pp. ISBN 0-448-11856-4.
Carr A. 1963. The Reptiles. Life Nature Library. Time-Life Books, New York. 192 pp. LCCCN 63-12781.
Bryan G. Fry, Nicolas Vidal, Janette A. Norman, Freek J. Vonk, Holger Scheib, S. F. Ryan Ramjan, Sanjaya Kuruppu, Kim Fung, S. Blair Hedges, Michael K. Richardson, Wayne. C. Hodgson, Vera Ignjatovic, Robyn Summerhayes, Elazar Kochva (2006). "Early evolution of the venom system in lizards and snakes". Nature 439 (7076): 584–588. doi:10.1038/nature04328. PMID 16292255.
Bryan G. Fry, Eivind A. B. Undheim, Syed A. Ali, Jordan Debono, Holger Scheib, Tim Ruder, Timothy N. W. Jackson, David Morgenstern, Luke Cadwallader, Darryl Whitehead, Rob Nabuurs, Louise van der Weerd, Nicolas Vidal, Kim Roelants, Iwan Hendrikx, Sandy Pineda Gonzalez, Alun Jones, Glenn F. King, Agostinho Antunes, Kartik Sunagar (2013). "Squeezers and leaf-cutters: differential diversification and degeneration of the venom system in toxicoferan reptiles". Molecular & Cellular Proteomics 12 (7): 1881–1899. doi:10.1074/mcp.M112.023143.
"The Keeping of Large Pythons" at Anapsid. Accessed 16 September 2007.

cat file1 file2 ...
[print named files to the screen]
(conCATenate) If given just one file, cat will print the contents of the file to the screen. Given multiple files, it will print one after another.

Let's start by making two files, cat1.txt and cat2.txt:

$ echo 'HEY EVERYONE!!!' > cat1.txt
$ echo 'WISH I WAS OUTSIDE PLAYING!!! :O(' > cat2.txt

To view the contents, type:

$ cat cat1.txt
$ cat cat2.txt
$ cat cat1.txt cat2.txt

grep 'search_string' file1 [file2 ...]
(Global Regular Expression Print)
Searches for the "search string" in a text file and prints out all lines where it find the desired text. The search string can be a simple word, or a complicated specification of matches/mismatches.

$ grep python pythons_of_the_world.txt
The Pythonidae, commonly known simply as pythons, from the Greek word python (πυθων), are a family of nonvenomous snakes found in Africa, Asia and Australia. Among its members are some of the largest snakes in the world. Eight genera and 26 species are currently recognized.[2]
In the United States, an introduced population of Burmese pythons, Python molurus bivittatus, has existed as an invasive species in the Everglades National Park since the late 1990s.[3]
Many species have been hunted aggressively, which has decimated some, such as the Indian python, Python molurus.
Black-headed python,
Larger specimens usually eat animals about the size of a house cat, but larger food items are known: some large Asian species have been known to take down adult deer, and the African rock python, Python sebae, has been known to eat antelope. Prey is swallowed whole, and may take anywhere from several days or even weeks to fully digest.
Contrary to popular belief, even the larger species, such as the reticulated python, P. reticulatus, do not crush their prey to death; in fact, prey is not even noticeably deformed before it is swallowed. The speed with which the coils are applied is impressive and the force they exert may be significant, but death is caused by suffocation, with the victim not being able to move its ribs to breathe while it is being constricted.[5][6][7]
Apodora Kluge, 1993 1 0 Papuan python Most of New Guinea, from Misool to Fergusson Island
Bothrochilus Fitzinger, 1843 1 0 Bismark ringed python The islands of the Bismark Archipelago, including Umboi, New Britain, Gasmata (off the southern coast), Duke of York and nearby Mioko, New Ireland and nearby Tatau (off the east coast), the New Hanover Islands and Nissan Island
Leiopython Hubrecht, 1879 1 0 D'Albert's water python Most of New Guinea (below 1200 m), including the islands of Salawati and Biak, Normanby, Mussau, as well as a few islands in the Torres Strait
Carpet python,
Green tree python,
Albino Burmese python,
Borneo short-tailed python,

The -c argument counts the number of lines with a match (not the number of matches).

$ grep -c python pythons_of_the_world.txt

The -v argument inVerts the search (i.e. prints lines that *don't* contain your search string).

cut -f column_number(s) file

Many of the data files we'll be dealing with are actually tables, usually separated by tabs. The cut command will pull out the column numbers you specify and print them out to the shell, while leaving the original file alone.

Special characters

wildcard matching with the *

The star functions as a "wild-card" character that matches any number of characters.

$ ls
cat1.txt cat2.txt pythons_of_the_world.txt
$ ls *.txt
cat1.txt cat2.txt linux_text.txt

The star can go anywhere in a list of arguments you're supplying, even in the middle of words! There are other wildcards you can use but * is the most common.

pipe |

(the one above the backslash "\" key)

Piping with | connects UNIX commands, allowing the output of one command to "flow through the pipe" to another. This lets you chain programs together, such that each one only needs to worry about one step of the process (either generating, filtering, or modifying data), without knowing or caring where it came from or where it's going to.

$ env
PS1=(Canopy 32bit) \h:\W \u\$

$ env | head

$ env | grep HOME

Redirection with >

In addition to redirecting output to another command, the results can be sent into a file with the >

$ cat cat1.txt cat2.txt > wishes.txt
$ cat wishes.txt

Or you can append to the end of a file with >>
$ echo "Just kidding, I love Programming!" >> wishes.txt
$ cat wishes.txt
Just kidding, I love Programming!"


Unlike the computers you are used to, UNIX doesn't automatically know what to do with files (e.g. It won't know to use Word to open a .doc document), and it doesn't even know whether a file is data or a program (and as we'll see with the programs we write, it might be different things at different times)

The first thing that controls a file is the file's permissions. You can control who can read, write, and execute (run as a program) each of your files.

$ ls -la

The first letter tells you whether it is a directory.

The next set of letters tell you if a file is readable (r), writable (w), or executable (x).

The 2nd-4th letters tell you what *your* permissions are, 5th-7th tell you what your group's permissions are, and the last three tell you what the rest of the world's permissions are. Unix was designed to be a multi-user operating system, so even if you're the only one who uses the computer, it maintains the distinction for you, versus your group, versus everyone else.

chmod [flags] [filename]
Modify permissions.

$ echo 'script' >
$ ls -l
-rw-r--r-- 1 aishaellahi85 staff 7 Jul 13 20:52
$ chmod +x
$ ls -l
-rwxr-xr-x 1 aishaellahi85 staff 7 Jul 13 20:52*

Sara is going to explain how to get UNIX to run your executable scripts this afternoon. However, if you try running a program and it's not working at some point in the class, double check the permissions!!!

Help, I'm stuck!

man command_name
[what does that command do again?]

Most commands have many useful flags beyond what I've shown you. For information on a particular command, look at the MANual pages with man.
$ **man chmod**
CHMOD(1)                  BSD General Commands Manual                 CHMOD(1)
     chmod -- change file modes or Access Control Lists
     chmod [-fv] [-R [-H | -L | -P]] mode file ...
     chmod [-fv] [-R [-H | -L | -P]] [-a | +a | =a] ACE file ...
     chmod [-fhv] [-R [-H | -L | -P]] [-E] file ...
     chmod [-fhv] [-R [-H | -L | -P]] [-C] file ...
     chmod [-fhv] [-R [-H | -L | -P]] [-N] file ...
     The chmod utility modifies the file mode bits of the listed files as
     specified by the mode operand. It may also be used to modify the Access
     Control Lists (ACLs) associated with the listed files.
     The generic options are as follows:
     -f      Do not display a diagnostic message if chmod could not modify the
             mode for file.
     -H      If the -R option is specified, symbolic links on the command line
             are followed.  (Symbolic links encountered in the tree traversal
             are not followed by default.)
     -h      If the file is a symbolic link, change the mode of the link
             itself rather than the file that the link points to.
     -L      If the -R option is specified, all symbolic links are followed.
     -P      If the -R option is specified, no symbolic links are followed.
             This is the default.
     -R      Change the modes of the file hierarchies rooted in the files
             instead of just the files themselves.
     -v      Cause chmod to be verbose, showing filenames as the mode is modi-
             fied.  If the -v flag is specified more than once, the old and
             new modes of the file will also be printed, in both octal and
             symbolic notation.
     The -H, -L and -P options are ignored unless the -R option is specified.
     In addition, these options override each other and the command's actions
     are determined by the last one specified.
     Only the owner of a file or the super-user is permitted to change the
     mode of a file.

Text Editors

Lastly, now that we can see into files, it would be nice to be able to create and edit our own files. And... our first lesson in programming accents: different programmers use different text editors. I am going to introduce three common options here. Each has pluses and minuses depending on your needs. There is no 'right' one, so play around and pick your favorite. Note that each of the teachers will be using their fav, so don't worry if they are using something different than you. These can all operate in the terminal window, and for some quick edits, it may make sense to do it that way, although they also have standalone programs. Often, you'll want to have that window open editing your code, save, jump over to the terminal, and then run your code.

Program 1: vi
open a file: vi [filename]
write to file: i
save a file: :w
close: :q

Vi is somewhat unique in that it has a couple major "modes". The default, "normal mode" is not actually the one where you write text, so you need to use i to go into "insert mode", then ESC to get back to normal mode, where you can save, search, etc. For more info, see: Introduction to Vi

Program 2: emacs
open a file: emacs [filename]
save a file: CTRL-X CTRL-S
close: CTRL-X CTRL-C

Emacs (including Aquamacs) has many, many short-cut keys or "accelerators." A quick Googling of "Emacs Cheat Sheet" will reveal several resources, such as this one from the Princeton CS department: Emacs Cheat Sheet

Program 3: nedit (gedit) (Mac users may not have this one; don't worry!)
open a file: nedit [filename]
save a file: CTRL-S
close a file: CTRL-C pulldown menu!!!

And then there is my personal favorite:
Program 4: Aquamacs
open a file: aquamacs [filename] &
save a file: CTRL-X-S
write a file: CTRL-X-W
close a file: command + W

Final Installation Check

Ok, now that we have a handle on the terminal, let's do a final installation check of the programs we had you install. In your terminal window, type the following comands:

$ ipython
Enthought Python Distribution --

Python 2.7.3 |EPD 7.3-1 (32-bit)| (default, Apr 12 2012, 11:28:34)
Type "copyright", "credits" or "license" for more information.

IPython 0.12.1 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.

Raise your hand if this does NOT work for you. Now, try:

$ aquamacs &

This command should start aquamacs and open a new text editor window.
To test chimera, try:

$ chimera

This should start the chimera program.
To test git, type:

$ git
usage: git [--version] [--help] [-C <path>] [-c name=value]
[--exec-path[=<path>]] [--html-path] [--man-path] [--info-path]
[-p|--paginate|--no-pager] [--no-replace-objects] [--bare]
[--git-dir=<path>] [--work-tree=<path>] [--namespace=<name>]
<command> [<args>]

The most commonly used git commands are:
add Add file contents to the index
bisect Find by binary search the change that introduced a bug
branch List, create, or delete branches
checkout Checkout a branch or paths to the working tree
clone Clone a repository into a new directory
commit Record changes to the repository
diff Show changes between commits, commit and working tree, etc
fetch Download objects and refs from another repository
grep Print lines matching a pattern
init Create an empty Git repository or reinitialize an existing one
log Show commit logs
merge Join two or more development histories together
mv Move or rename a file, a directory, or a symlink
pull Fetch from and integrate with another repository or a local branch
push Update remote refs along with associated objects
rebase Forward-port local commits to the updated upstream head
reset Reset current HEAD to the specified state
rm Remove files from the working tree and from the index
show Show various types of objects
status Show the working tree status
tag Create, list, delete or verify a tag object signed with GPG

'git help -a' and 'git help -g' lists available subcommands and some
concept guides. See 'git help <command>' or 'git help <concept>'
to read about a specific subcommand or concept.

Raise your hand if any of these do NOT work for you.



1) Cerevisiae chromosomes

a) In your top-level directory, make a new directory called "fasta_files" and change into it
b) Go to
and individually download each of the files ending in .fsa. These are the chromosomes of the yeast, S. cerevisiae. You may have to right-click these files depending on your web browser (and be aware, some browsers will save your file with a .txt extenstion).
c) Make a single whole genome file called "cerevisiae_genome.fasta"
d) Count the chromosomes in the whole genome file using commands from the lecture. (HINT: Each of the original FASTA files contains a single chromosome).
e) Look up the command 'wc' and find out what it does. Get size of total genome. (HINT: The size of the genome can be determined by counting the number of characters not on the same line as a fasta header).

2) Cerevisiae genes

a) Get the list of cerevisiae chromosome features:
Columns within
1.   Primary Standfor Gene Database ID (SGDID) (mandatory)
2.   Feature type (mandatory)
3.   Feature qualifier (optional)
4.   Feature name (optional)
5.   Standard gene name (optional)
6.   Alias (optional, multiples separated by |)
7.   Parent feature name (optional)
8.   Secondary SGDID (optional, multiples separated by |)
9.   Chromosome (optional)
10.  Start_coordinate (optional)
11.  Stop_coordinate (optional)
12.  Strand (optional)
13.  Genetic position (optional)
14.  Coordinate version (optional)
15.  Sequence version (optional)
16.  Description (optional)

b) Count total genes
c) Count only verified genes. Count only uncharacterized genes.
d) What other types of genes are in this file? For this, you may want to use the sort command with the -u flag, which will sort the input alphabetically, then take only unique lines.

3) Star-struck
From the same directory as your fasta files, see if you can predict what each of these commands will do (then try it)
a) head *
b) head *.fsa
c) head chr1*.fsa
d) head chr1*
e) head chr*1.fsa
f) head chr*1
g) grep 'S288C' *
h) grep 'S288C' *.fsa
i) grep 'BK006935.2' *
j) cat * | grep 'BK006935.2' (what's the difference in the output between this one and the last one?)
k) head *.fsa | grep 'chr'
l) head *.fsa | grep 'chromosome' (what's the difference in the output between this one and the last one?)

4) Building a pipeline
a) Using the command line, copy the files "palinsreg" and "palinscmp" from the provided "data" directory to today's directory (S1.1). These are detected terminator sequences in the E. coli genome (using the program GeSTer, if you're curious).
b) The command grep '/G=[^ ]*' somefile will find all lines that match /G=somegenename, where somegenename is a sequence of non-blank characters. Read the output of man grep and figure out how to -only print /G=somegenename, rather than the whole line.
c) Pipe the results of part b) through a cut command to get only everything after the =
d) Store the results of part c) in a file named "terminated_genes.txt'
e) BONUS: google for a Unix command that only keeps each gene once, rather than once per annotated terminator.

5) Moving beyond the lecture
a) Use google and any other references you want to find a command that tells you how much disk space you have left.
b) Use the 'man' command to see how it works.
c) How much space is left on your system? Make the command output in terms of gigabytes and megabytes-- 'human-readable' form.

6) Picking your favorite text editor
a) Play around with the three text editors I just introduced.
b) Using your favorite editor, write a short note about what you are most excited about learning in this class. Email it to us at


1) Cerevisiae Chromosomes
a, b) Just do it!
$ cat *.fsa > cerevisiae_genome.fasta
$ grep -c '>' cerevisiae_genome.fasta
$ grep -v '>' cerevisiae_genome.fasta | wc
202628 202628 12359733
Then, subtract 202628 (the number of "newline" characters) from 12 359 733. In short, still about 12 megabases.

2) Cerevisiae Genes
a) Do it!
$ grep -c ORF
$ grep ORF | grep Verified | wc -l

$ grep ORF | grep Uncharacterized | wc -l

$ cut -f 3 | sort -u


3) Star-struck
a) This prints the first 10 lines of every file in the directory
b) This prints the first 10 lines of every file in the directory that ends with .fsa (but not .fasta)
c, d) The first 10 lines of every file in the directory where the filename starts with chr1 (i.e. chr10.fsa, chr11.fsa, etc)
e) The first 10 lines of chr01.fsa and chr11.fsa
f) Nothing! There is no file that starts with chr and ends with 1
g, h) Note again that cerevisiae_chromosome.fasta does not end with .fsa!
i, j)
$ grep 'BK006935.2' *
cerevisiae_genome.fasta:>tpg|BK006935.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=I] [note=R64-1-1]
chr01.fsa:>tpg|BK006935.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=I] [note=R64-1-1]
$ cat * | grep 'BK006935.2'
>tpg|BK006935.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=I] [note=R64-1-1]
>tpg|BK006935.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=I] [note=R64-1-1]

Note that the first one, grep will put the name of the file it found it in at the beginning of the line, whereas in the second, once they've ben cat'ed together, the filename goes away.

k, l)
==> chr01.fsa <==
>tpg|BK006935.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=I] [note=R64-1-1]
==> chr02.fsa <==
>tpg|BK006936.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=II] [note=R64-1-1]
==> chr03.fsa <==
>tpg|BK006937.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=III] [note=R64-1-1]
==> chr04.fsa <==
>tpg|BK006938.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=IV] [note=R64-1-1]
==> chr05.fsa <==
>tpg|BK006939.2| [organism=Saccharomyces cerevisiae S288c] [strain=S288c] [moltype=genomic] [chromosome=V] [note=R64-1-1]


Note that when you do head on multiple files, it includes the name of each file in ==> <==. When grep'ing for chr, you find the chr in the name of the file, as well as the chr inside the file, whereas chromosome only matches inside the file.

4) Building a Pipeline
a) something like:
$ cp Downloads/palins* PythonCourse/S1.1
$ grep -o '/G=[^ ]*' palins*
$ grep -o '/G=[^ ]*' palins* | cut -d '=' -f 2
$ grep -o '/G=[^ ]*' palins* | cut -d '=' -f 2 > terminated_genes.txt
$ grep -o '/G=[^ ]*' palins* | cut -d '=' -f 2 | sort -u > terminated_genes.txt

5) Moving beyond the lecture
Google is your friend! I searched for "unix disk space" and clicked on the first result...

$ df -h