Welcome to the UCLA IGERT 2005 Summer

Welcome to the UCLA – IGERT 2005 Summer Bioinformatics Workshop IGERT – Sponsored Bioinformatics Workshop Series Michael Janis and Max Kopelevich, Ph. D. Dept. of Chemistry & Biochemistry, UCLA

Who this workshop is for • Biologists: –Integrating bioinformatics methods into their existing projects • Bioinformatics students: –Preparing for and augmenting existing bioinformatics coursework • Computational researchers: –Identifying and understanding common bioinformatics language classes and data structures

Why this workshop? • Current graduate curriculum: – Assumes substantial knowledge base upon entry into bioinformatics program • Researchers: – No general overview of computational research environments • some aimed at tools (suites), others deep in theory base

Why learn bioinformatics? • The 1 gene, 1 protein research model ignores the deluge of inferential biological data at our disposal • This information must be combined for any thorough study of biological phenomena • Assembly of qualitative (sequence, etc. ) and quantitative (measured, inferential) data is beyond the capacity of a human to interpret in a systematic fashion • Computational methods must be addressed both to interpret and to share research data in a meaningful way – Yet Another Tool in a biologist’s arsenal

What is Bioinformatics? • A tool in a molecular biologist’s arsenal such as PCR, gels, or microarrays; or: • A support machine for handling and storing large data sets; or: • A discipline in its’ own right, enabled by a critical mass of biological data and mirroring the evolution of a number of scientific sub-disciplines

An argument for learning: as a tool for molecular biologists? • 1 gene, 1 protein becomes an interactive series of pathways and protein interactions • A pathway allows novel interaction discovery and ontological groupings of data • Moving from identification of a gene that has biological function to elucidation of a pathway from a given biological function (just for example)

An argument for learning: as support for data management? • Completion of the human genome working draft in June 2000 resulted in an absolute requirement for a logical, hierarchical way to store, modify, and retrieve data • Cross-referencing information is necessary to incorporate disparate and sometimes conflicting information • Combination of data and necessary algorithm development to find signal among the noise of the genome

An argument for learning: as an entirely new discipline? • Evolutionary biology through homology – (COG for example) • Gene expression and structure prediction – (alternative splicing for example) • Protein and nc. RNA modeling • Genome mapping – (statistical genetics and disease correlations) • Pathway prediction • Towards an end: Systems Biology

What has bioinformatics allowed us to do? • Evolutionary Biology – Clusters of Orthologous Genes (COG database) http: //www. ncbi. nlm. nih. gov/COG/ • Structure and alignments – PFAM/RFAM http: //www. sanger. ac. uk/Software/Rfam/ • Expression inferences – clustering to find interactions (for example through SMD: http: //genome-www 5. stanford. edu/ • Genome mapping – (for example the UCSC Genome Browser: http: //genome. ucsc. edu/cgi-bin/hg. Gateway

What do we need to create our own genomic inferences? • That’s the problem… The data is encoded… • AGCTAGCGATTATA… – Now predict what this sequence codes for, how it is transcriptionally regulated, in what pathway does it function … • The human genome is 3 billion bases. – Clearly we need a new set of tools • Problem: no human being could ever look at all this data, so the patterns must be discovered computationally

The magic wand analogy • The sum of all human knowledge can be encrypted and stored by marking a single scratch on a metal rod. It all depends upon RESOLUTION and LANGUAGE. • We can apply this analogy to our analytical process: – High RESOLUTION is required to decode the genome – A robust LANGUAGE is required to achieve that RESOLUTION – Computational biology seeks to describe that LANGUAGE

How do discover meaningful biological patterns? • • • Need to be able to pick “needles from haystacks” Need to be able to assemble needles Need to orient and classify needles And so on… This requires a strong, flexible environment The Shell, PERL, R, Post. Gre. SQL/My. SQL – integration, data exploration • Statistical development environments – making inferences from the data • Databases and resources – combining the data

How our workshop will help you (and how it won’t? ) • We cover common, portable, powerful resources – but require suitable activation energy! • Integration for a project model is key • Thus, easily understood but limited GUI based suites are not covered • Likewise theory of algorithm development is covered in other courses and will be ignored (for the time being!)

How this workshop is structured • Two lectures a week for six weeks (fast!) • Lots of reading material (need to keep pace) • Hands – on practical experience with biological data and programming tasks • Peer interaction

What you’ll need for this workshop • Access to either the online version of the text through O’Reilly Media (linked on the website, $20 for two months) or through purchase of the print bound version (approx $130, we’ll put in an order during the second week) • Access to a computer. Any computer will do. • Motivation to learn, and to ask questions

What is the text for this workshop? • O’Reilly Media Safari. U agglomerative text of 10 textbooks from O’Reilly, New Riders, and Addison. Wesley publishers • Chosen for topics applicable to modern computational biology • Since many texts overlap, no need to own all – cost reduction ($130 vs. over $500)

Class information • • • mjanis@chem. ucla. edu Office: 4054 Young Hall http: //www. bol. ucla. edu/~mjanis/biohackers 2005. html http: //lists. ucla. edu/cgibin/mailman/listinfo/bioinformatics IRC: #ucla. Bioinformatics, freenode server (mako) T / R 2 -4 pm 1054 Young Hall, Aug 11 - Sept. 16 2005

Class information BRIEF SUBJECT MATTER OUTLINE (SUBJECT TO CHANGE!) 08/11 Unix: Introduction to Unix; Bioknoppix 08/16 Unix basics, editors, remote logins 08/18 Shell programming 08/23 Regular expressions; biological data formats 08/25 Perl: data and control structures 08/30 Modular programming 09/01 Object oriented perl 09/06 Biological classes; Bioperl 09/08 NCBI tools; BLAST 09/13 Database design; perl DBI 09/15 Net programming; XML; CGI 09/16 R; Bioconductor

We used to call it “biohackers”… • What is a hacker? • One with technical adpetness who delights in solving problems and overcoming limits… • Hackers can be found in all walks of life – music, art, science • Hackers create things – the internet, Unix, NCBI, the Human Genome project • Not what the media would call a “hacker”…

The hacker attitude* • Hackers believe the world is full of fascinating problems waiting to be solved. • Nobody should ever have to solve the same problem twice. • Boredom and drudgery are evil. • Freedom is good • Attitude is no substitute for competence * From “The Cathedral and the Bazaar”

Why would I want to become a “hacker” or a “biohacker” or whatever? • Spend less time brutally munging your data. Spend more time gaining biological insight. Publish faster. • Begin to assemble complex and disparate data in ways not achievable by humans. Think systematically about your data. Think systemically about your research. • Smugly travel easily through electronic medium. Automate your life • Be cool. Get chicks! (or whomever you want)…

It worked for “neo”…

In reality, it worked for someone else too …

How does one become a hacker? • Learn to program. The more languages, the better. (Don’t think in terms of languages… Think in terms of PROGRAMMING) • Get an extensible, modifiable OS and learn to use it • Learn how to access and use information • Practice, practice. This workshop can only show you the door. You have to walk through it.

So what is biohacking? • Inferential analysis of disparate biological data • Discovering and creating new ways of looking at biological phenomenon • Creation of novel tools • Decoding the nature of life (BHAG)

So show me the tool to find the gene… I’ll be in the lab… • What if your research looks at biology from a novel angle? What if there are no tools? Where to start? • We need a modular framework. Something that will scale nicely so that we can incorporate more data later. Some set of tools that integrate well, each doing one job and doing it well. We need COMBINATORIC TOOLSETS!

A tale of two philosophies • Windows works extremely well at solving one problem at a time, if it falls within defined parameters… It does not scale well. • This monolithic approach is good for small scale biology but not for complex biological analysis

We need a construct where we can call upon modular tools to assemble our own analysis… I need bioinformatics tools… Lots of bioinformatics tools…

The construct – UNIX (the other philosophy) • UNIX is an operating system that provides powerful modular utilities that function together to create computer environments that can solve a wide variety of tasks. • Unix Operating System –created 1960 s –provides a multi-user, multitasking system • It’s a server by design • Networks extremely well due to ports – X 11 is an example –command line based • Bioinformatics relies heavily upon UNIX – and a fundamentally different philosophy: • modular by its’ very nature, UNIX is scaleable, robust, and … FREE! • But more than anything else, Unix has THE SHELL

The Unix Shell • • The shell is the unix user environment The shell is started automatically when you log in Everything is controlled from a shell The shell interprets commands – It’s also a programming language itself! • http: //www. looking-glass. org/shell. html – http: //www. strath. ac. uk/CC/Courses/Intro. To. Unix/node 46. html • More than one shell can be open at a time

Commands to the system • Specific commands used to perform functions in the shell – Ex: changing directories, copying files, mv files, sorting, cutting, pasting, etc… – Many of these can be done in XL, but… • What if you need a subsequent command? Chi. Square analysis for example? • What if you need to do this to 10 files? 10000? • Each command is itself a program and take command line arguments – The Shell is the “glue” that allows us to combinatorically daisy-chain our tools together to do a job • The Shell allows us to batch these commands into a pipeline or framework for analysis

The Shell controls input / output STDIN Command Or Program STDERR STDOUT

Input / Output II STDIN -Keyboard -File -Previous STDOUT Command Or Program STDERR STDOUT -Terminal/ monitor -File -Next STDIN

Input / Output III Command 1 Pipe Command 2

Large Pipe Command 1 Pipe Command 2 Pipe Command 3 Pipe Command 4 Can daisychain commands from every shell program

UNIX then… Linux? BSD? OS X? (over 360 distributions according to linux. org)

How can I get *nix to use? • Linux is open source – Available for a variety of platforms • BSD is likewise open source – Forms the basis of Mac OS X, and many MSWin utilities • There are live distributions as well – Example: Bioknoppix - http: //bioknoppix. hpcf. upr. edu/ • Bioknoppix is a customized distribution of Knoppix Linux Live CD. With this distribution you just boot from the CD and you have a fully functional Linux OS distribution with open source bioinformatics (sic) applications. • Beside using some RAM, Bioknoppix doesn't touch the host computer.

What about administrating the system? I heard it’s hard!

Package managers • Most modern distributions have a package manager – – Handles installation Handles dependencies Handles conflicts Packages are written in such a way as to ensure that they do not interfere with other parts of the OS install • With Bio. Knoppix, you won’t really need one • With Debian, there is aptitude, and synaptic • There a wealth of bioinformatics tools packaged for use with package managers • We’ll be exploring these as we go along…

For our Apple brethren…

There is fink • Mac OS X forms a natural basis for a end user bioinformatics analysis station • It’s UNIX underneath! • The GUI is advanced • It’s easy to administrate • http: //fink. sourceforge. net/ • Finks installs into its own protected directory /sw • Easy to remove if things go south…

What is fink? • Fink is a distribution of Unix Open Source software for Mac OS X and Darwin. – It brings a wide range of free command-line and graphical software developed for Linux and similar operating systems to your Mac. • Installation is accomplished via a tarball. – After that, it’s simple command line- interaction (based upon the debian model, which I’ll show in class) • http: //fink. sourceforge. net/doc/usersguide/install. php? php. Lang=en

For our MS brethren… Welcome to Earth A subsidiary of Microsoft

There is cygwin • • • Shell utilities written as windows executables Creates its own protected / filesystem Problems with networking No real package manager beyond the shell utils Can be problematic to install packages with deep *nix library dependencies • Created / maintained by Red. Hat developers • http: //www. cygwin. com/

But mainly have remote access to a real *nix machine

Configure Putty

SSH Option

We’ll be using… • Bio. Knoppix Beta 0. 2. 1 (but the Knoppix part is 3. 3…) • This distribution is included in your folder • Debian stable 3. 1 (“Sarge”) install – which I’ll do in class – will be our main server. We’ll call it “subi” (subi. chem. ucla. edu) for SUmmer BIonformatics. • The text has details about the use of knoppix • Let’s take a look …

The shell, files, directories, commands, and editors

File System visualize the Unix file system as an upside down tree. At the very top of the tree is the root directory, named "/".

Common filesystem locations /usr/ The majority of user utilities and applications. / Root directory of the file system. /usr/bin/ Common utilities, programming tools, and applications. /bin/ User utilities fundamental to both singleuser and multi-user environments. /usr/include/ Standard C include files. /boot/ Programs and configuration files used during operating system bootstrap. /usr/lib/ Archive libraries. /usr/libdata/ Miscellaneous utility data files. /boot/defaults/ Default bootstrapping configuration files; see loader. conf(5). /usr/libexec/ System daemons & system utilities (executed by other programs). /dev/ Device nodes; see intro(4). /etc/ System configuration files and scripts. /etc/defaults/ Default system configuration files; see rc(8). /usr/local/ /etc/mail/ Configuration files for mail transport agents such as sendmail(8). Local executables, libraries, etc. Also used as the default destination for the Free. BSD ports framework. Within /usr/local, the general layout sketched out by hier(7) for /usr should be used. Exceptions are the man directory, which is directly under /usr/local rather than under /usr/local/share, and the ports documentation is in share/doc/ port. /etc/namedb/ named configuration files; see named(8). /usr/obj/ Architecture-specific target tree produced by building the /usr/src tree. /etc/periodic/ Scripts that are run daily, weekly, and monthly, via cron(8); see periodic(8). /usr/ports The Free. BSD Ports Collection (optional). /etc/ppp/ ppp configuration files; see ppp(8). /usr/sbin/ System daemons & system utilities (executed by users). /mnt/ Empty directory commonly used by system administrators as a temporary mount point. /usr/share/ Architecture-independent files. /usr/src/ BSD and/or local source files. /proc/ Process file system; see procfs(5), mount_procfs(8). /usr/X 11 R 6/ X 11 R 6 distribution executables, libraries, etc (optional). /rescue/ Statically linked programs for emergency recovery; see rescue(8). /var/ Multi-purpose log, temporary, transient, and spool files. /root/ Home directory for the root account. /var/log/ Miscellaneous system log files. /sbin/ System programs and administration utilities fundamental to both singleuser and multi-user environments. /var/mail/ User mailbox files. /var/spool/ Miscellaneous printer and mail system spooling directories. /var/tmp/ Temporary files that are kept between system reboots. /var/yp NIS maps. /stand/ /tmp/ Programs used in a standalone environment. Temporary files, usually a mfs(8) memorybased file system (the contents of /tmp are usually NOT preserved

Types Files • ordinary files – – text files data files command text files (shell scripts), executable files (binaries); • directories; • links special device files (physical hardware) • In unix, everything is a file… and every file is a device… including the display – which is a port …

Directories All directories are subdirectories of the root directory Every directory can contain files or subdirectories Every directory can contain a device. Which is a file. Which really means that from anyplace in the filestructure hierarchy, you can pipe IO to any other place (device… err, file…)

Relevant Terminology • • Path File permission Home directory Current working directory Account Login Name / Username Password Root

Logging Into Machine Red Hat Linux release 9 Kernel 2. 4. 18 -14 on an i 686 localhost login:

The Unix Shell • http: //www. looking-glass. org/shell. html • http: //www. strath. ac. uk/CC/Courses/Intro. To. Unix/node 46. html • When you type commands you are communicating with the shell • The shell is started automatically when you log in • Everything is controlled from a shell • More than one shell can be open at a time

Commands • Specific commands used to perform functions in the shell • Ex: changing directories, copying files, mv files, etc… • Each command is itself a program and take command line arguments • For help on a specific command type: man command

ls • • pwd “returns current working dir path” ls “view contents of directory” ls “lists all files (except hidden files)” ls –A “all files INCLUDING hidden files” ls -lt “lists all files in descending time ls – 1 “what does this do? ” man ls ls *. CEL wildcards can be used

cd • cd “change directory” • cd “changes to user’s home directory” – ‘home directory’ –top of users dir tree • • • cd some_dir “moves you to some_dir” cd ~ “moves you to your home directory” cd. . /. . “moves you two directories up” Cd – “returns you to previous working dir” mkdir – creates a new directory with default permissions.

more / less • More “view contents of a file” – Use return or space to move through file – Use b to go backwards – ASCII only -> dos 2 unix command • Less “view contents of a file” – Use page up and page down to scrolol – Does not buffer whole file man more man less “less is more!!”

grep • Search contents of a file or directory of files – “Get Regex” – uses regular expressions we learned – File wildcards can be used like with ls • grep 1 sq ~/DATA/*. CEL -> array type used

rm • • rm “remove a file or directory” rm –R “remove all subdirectories” rm –f “dangerous, forces, no prompt” man rm • HOW DO YOU UNDELETE? ? ?

UNDELETE • THERE IS NO UNDELETE • (no trash, no recycle bin to open / browse) • Be careful what you do – But, that’s why there are permissions!!! – Also a reason for *nix stability

An Example ls –l output: Unix Permissions File permissions prevent users from deleting or tampering others files Permissions listings

chmod • • chmod “change file permissions” chmod 777 “change permissions to 777” chmod –R 775 “change recursively” man chmod

Permissions Explained • ------ • you group world • --- READ WRITE EXECUTE • rwx rwx • Binary 421 421 = 777 • rw- r– r-6 44

cp • • cp “copy from x to y” cp /home/igert/bin/a /home/igert cp –R directory /folder/new_dir man cp • cd /home/igert/temp • cp a. . • cp /home/igert/temp/a ~

Process Control, I/O Redirection & Pipes

Overview • Unix provides powerful features for: – – Managing your jobs (process control) Redirecting standard input and standard output Reading and writing files This is the ‘power of the shell’

Input / Output STDIN Command Or Program STDERR STDOUT

Input / Output II STDIN -Keyboard -File -Previous STDOUT Command Or Program STDERR STDOUT -Terminal/ monitor -File -Next STDIN

Input / Output III Command 1 Pipe Command 2

Large Pipe Command 1 Pipe Command 2 Pipe Command 3 Pipe Command 4 Can daisychain commands from every shell program

Example STDIN Command Or Program echo “Hello Genome Hacker!” STDOUT

Example (details) “Hello Genome Hacker!” ECHO Hello Genome Hacker! echo “Hello Genome Hacker!”

What can we pipe to? • Many useful shell commands exist – use apropos to find • awk, sed, perl –e, wc, diff, cut, paste, sort, uniq… just to name a few • What do these do? Try man ‘command’ (as: man paste)

AWK is your pre-perl friend • • Use to print a subset of fields Default field delimiter is “ “ (white space) Useful for grabbing a subset of fields Useful for rearranging fields field 1 filed 2 field 3 field 4. . . $1 $2 $3 $4. .

Using AWK pipe | awk –F” “ ‘{print $1}’ | awk –F” “ ‘{print $1”t”$2}’ t = TAB n = newline “$2}’

Example of a pipe “Hello Genome Hacker!” Command 1 (ECHO) Pipe Command 2 (AWK} Hacker! Genome Hello echo “Hello Genome Hacker!” | awk ‘{print $3”t”$2”t”$1}’

Example: redirecting STDOUT STDIN Command Or Program STDOUT OUTPUT_FILE echo “Hello Genome Hacker!” > output_file more output_file “redirection operator”

Overwrite versus Append • > OVERWRITE – delete and replace • >> APPEND – add to end of existing file

Example: microarray data tracking • grep 1 sq ~/DATA/*. CEL (gives array info) • grep 1 sq ~/DATA/*. CEL | awk ‘{print $12}’ gives array type only • grep 1 sq ~/DATA/*. CEL | awk ‘{print $12}’ > array. Types. txt (store results in file) • ls ~/DATA/*. DAT | wc (gives a count)

Process Control • Each specific job / command is called a process • Each process runs in a shell – BEFORE: prompt available – DURING: prompt NOT available – AFTER: prompt available

Two Ways to monitor Processes • “top” – Lists all jobs – Uses a table format – Dynamically changes • “ps” – man ps – static content – Command options

Top output

Background / Foreground • Commands running in foreground prevent prompt from being used until command completes • Commands can also run in BACKGROUND • “Backgrounded” commands DO NOT AFFECT the prompt

Two Ways to Background jobs • “&” – Running a command with “&” automacically sends it to the background – Backgrounded commands return the prompt • “bg” – Once a command is run from the prompt – Stop the command – Then background it • Starts the command again • Returns the prompt for use

Creating Our Own Commands • Use programming language to create the new command • We will use perl • We’ll start USING OUR ENVIRONMENT (*NIX) NEXT WEEK!

Homework Set 1 • • What is the purpose of a pipe? What does the pipe do? What symbol is used for pipe? How are commands put in background? Why would you want to background? What is the top command? Why is it useful? Submit one question about the *NIX environment to the bioinformatics mailing list • ANSWER one question from the bioinformatics mailing list! (estimated time: 10 – 15 minutes)

Homework Problem 2 • • Create a two command pipe What does it do What are the inputs and outputs for each command? Can you extend it to three commands? How about four? (command hints: echo, grep, awk, wc) Redirect output to a file Run it a second time, and redirect (append) this output to previous output (estimated time: 15 to 30 minutes)