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Welcome to lecture 2: Feeling at home in *nix IGERT – Sponsored Bioinformatics Workshop Series Michael Janis and Max Kopelevich, Ph.D. Dept. of Chemistry.

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Presentation on theme: "Welcome to lecture 2: Feeling at home in *nix IGERT – Sponsored Bioinformatics Workshop Series Michael Janis and Max Kopelevich, Ph.D. Dept. of Chemistry."— Presentation transcript:

1 Welcome to lecture 2: Feeling at home in *nix IGERT – Sponsored Bioinformatics Workshop Series Michael Janis and Max Kopelevich, Ph.D. Dept. of Chemistry & Biochemistry, UCLA

2 Last time… We covered a bit of material… Try to keep up with the reading – it’s all in there! How’s it coming along? –BioKnoppix –Remote logins, navigation –Unix / linux concepts? –General questions?

3 The CLI and YOU Most of bioinformatics is accomplished through command-line tools Command line interaction is easily batched Command line interaction is easily integrated Command line interaction is a form of PROGRAMMING It’s therefore worthwhile to become familiar with your *nix environment in a non-graphical interface

4 Commands In Bioinformatics, we are mostly concerned with TEXT PROCESSING – the CLI is well suited for this type of work Specific commands are used to perform functions in the shell Each command is itself a program and takes command line arguments –The syntax order is program [-options] filename For help on a specific command type: man command; apropos topic; command --help

5 Some review of system tools Who W Uname Pwd Find Top

6 Another example of a pipe Command 1 (cut) Command 2 (sort) Pipe cut –d: -f1 < /etc/passwd | sort file Stdout The file /etc/passwd stores information about user’s accounts on the system Let’s get a sorted listing of all user names

7 Example: redirecting STDOUT Command Or Program STDIN STDOUT cut –d: -f1 output_file more output_file OUTPUT_FILE “redirection operator”

8 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 Control keys –CTRL-C -> stop current command –CTRL-D -> end of input

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

10 What are you doing, Dave?

11 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

12 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

13 File System Navigation Absolute filepaths begin with the root ‘/’ Relative filepaths don’t have a preceding slash; they begin from the cwd What is the absolute path to cd from john to mary? What is the relative path to cd from john to mary? Once you are in mary, and your username is john, what are two ways to return to your home directory?

14 The society for anti-defamation of computer mouses opposes this slide There’s very little reason to leave the CLI Most tasks can be written within the shell The user-friendliness becomes self-limiting

15 Let’s take an example… Suppose you wanted to do some biological analysis – like motif searching through a database of biological sequences… What do you need to do this? –You need to retrieve the sequences –You need to describe the motif –You need to search the sequences

16 I want to search for zinc-finger motifs genomically in yeast (S.c.) I’m going to need the genomic sequence for Saccharomyces cerevisiae (http://www.yeastgenome.org)http://www.yeastgenome.org I’m going to need the motif that describes the zinc finger I’d like to search for (ProSite). I’m going to need do do this search many times across every chromosome.

17 A brief overview of some databases / biological information repositories NCBI Genome-specific databases (SGD…) SMD The Stanford Microarray Database. Repository of microarray analysis from a wide variety. PROSITE Used to rapidly search your protein sequences for catalogued motifs.PROSITE SWISSPROT SWISSPROT is a "one stop shop" for protein sequence information. Use it to extend your knowledge of your proteins.SWISSPROT PDB: The Protein Databank The Protein Data Bank is the single worldwide archive of structural data of biological macromolecules. Structure implies function in general.PDB: PFAM: This database is a collection of protein motifs. PFAM: PRODOM PRODOM is similar to PFAM in that it is a set of curated protein domain families. However, the underlying computational engine is different.PRODOM BLOCKS Blocks are multiply aligned ungapped segments corresponding to the most highly conserved regions of proteins. The blocks for the Blocks Database are made automatically by looking for the most highly conserved regions in groups of proteins documented in InterPro. BLOCKSBlocks DatabaseInterPro COG COG stands for Clusters of Orthologous Groups of proteins. This is a tool for phylogenetic classification of proteins encoded in complete genomes. COGs were delineated by comparing protein sequences encoded in complete genomes, representing major phylogenetic lineages.COG

18 Retrieving data

19 You don’t have to leave the CLI. Really. –If you need to do something, chances are there’s a utility to do so –Debian is your friend (search packages FIRST!!!) Introducing wget: > wget ftp://genome- ftp.stanford.edu/pub/yeast/data_download/protein_info/hypothetical _peptides/*.gz Of course you can use ftp: >ftp genome-ftp.stanford.edu -login anonymous; use your address as passwd -traverse filesystem like any linux CLI -bin, get, prompt, mget…

20 A note about file archives Most files will be compressed. Usually using gunzip. Most files will be agglomerative, using TAR. Introducing gunzip: > gunzip *.gz Introducing tar (tape archive): >tar –xvf *.tar Or to create a tar >tar –cvf output.tar *.*

21 A brief note about the biological file format called FASTA In bioinformatics, FASTA format is a file format used to exchange information between genetic sequence databases. Its format looks like this:bioinformaticsfile formatgeneticsequence databases >SEQUENCE_1 ;comment line 1 (optional) MTEITAAMVKELRESTGAGMMDCKNALSETNGDFDKAVQLL REKGLGKAAKKADRLAAEGLVSVKVSDDFTIAAMRPSYLSYE DLDMTFVENEYKALVAELEKENEERRRLKDPNKPEHKIPQFA SRKQLSDAILKEAEE It consists of a header line (beginning with a '>') which gives a name and/or a unique identifier for the sequence. Many different sequence databases use FASTA files.sequence databases After the header line and comments, one or more sequence lines may follow. Sequences may be protein sequences or DNA sequencesprotein sequencesDNA sequences –they must be shorther than 80 characters and can contain gaps or alignment characters FASTA format files often have file extensions like.fa or.fsafile extensions The simple format of FASTA files makes them easy to manipulate using text processing tools and scripting languages like Perl.scripting languagesPerl *From

22 ProSite motif

23 Describing the motif - GREP “GREP” searches contents of a file or directory of files –“Get Regex” – uses regular expressions –File wildcards can be used like with ls grep 1sq ~/DATA/*.CEL -> array type used –We explored this last time (briefly!)

24 Regular expressions A regular expression, often called a pattern, is an expression that describes a set of strings. They are usually used to give a concise description of a set, without having to list all elements. –For example, the set containing the three strings Mike, Mark, and Matt can be described by the pattern “M((ike|(ark|att))?)" –Alternatively, it is said that the pattern “M((ike|(ark|att))?)" matches each of the three strings. –There are usually multiple different patterns describing any given set. Most formalisms provide the following operations to construct regular expressions.

25 Formalisms of regular expressions alternation –A vertical bar separates alternatives. For example, "gray|grey" matches grey or gray. grouping –Parentheses are used to define the scope and precedence of the operators. For example, "gray|grey" and "gr(a|e)y" are different patterns, but they both describe the set containing gray and grey. quantification –A quantifier after a character or group specifies how often that preceding expression is allowed to occur. The most common quantifiers are ?, *, and +: –? The question mark indicates that the preceding character may be present at most once. For example, "colou?r" matches color and colour. –* The asterisk indicates that the preceding character may be present zero, one, or more times. For example, "0*42" matches 42, 042, 0042, etc. –+ The plus sign indicates that the preceding character must be present at least once. For example, "go+gle" matches the infinite set gogle, google, gooogle, etc. (but not ggle). These constructions can be combined to form arbitrarily complex expressions, very much like one can construct arithmetical expressions from the numbers and the operations +, -, * and /. *From

26 The real world is fuzzy and complex… What if we just want to search for a string in the format of a phone number; E.g Obviously we can’t check for each possible phone number (some possibilities makes for a very long set of statements…). No area code Area code

27 This is where regular expressions come in… Regular expressions describe generalised patterns of strings instead of exact strings. (clearly this is a little more complex as an example…) >grep /([0-9]{3} ){0,1}[0-9]{3} [0-9]{4}/) filename

28 Special characters (‘metacharacters’) ‘.’ is a wildcard and matches any character >grep ‘.ed’ filename If file contains “bed” -will find If file contains “red” -will find If file contains “head” -will not find If file contains “edward” -will find

29 Special characters (‘metacharacters’) ‘*’ means ‘zero or more of the previous character’. >grep ‘be*d’ filename If file contains “bed” -will find If file contains “red” -will not find If file contains “beeeed” -will find If file contains “bd” -will find

30 Special characters (‘metacharacters’) ‘+’ means ‘one or more of the previous character’. >grep ‘be+d’ filename If file contains “bed” -will find If file contains “red” -will not find If file contains “beeeed” -will find If file contains “bd” -will not find

31 Start and end of line ‘^’ is designates the start of the line, ‘$’ the end. >grep ‘bed’ filename If file contains “bed” -will find If file contains “bedbed” -will find If file contains “xxxbedxxx” - will find >grep ‘^bed$’ filename Iff file contains “bed” on line by itself -will find If file contains “bedbed” -will not find If file contains “xxxbedxxx” – will not find

32 Grouping with parentheses Parentheses group characters >grep ‘(bed)+’ filename If file contains “bed” -will find If file contains “bedbed” -will find If file contains “beddd” -will not find

33 Character classes The square brackets are used to denote whole groups of characters >grep ‘[brf]ed’ filename If file contains “bed” -will find If file contains “red” -will find If file contains “led” -will not find

34 Character classes (cont) A hyphen designates a range: >grep ‘[a-z]ed’ filename If file contains “bed” -will find If file contains “fed” -will find If file contains “Bed” -will NOT find (why not?)

35 Character class shortcuts Some character classes are so common there are in-built shortcuts: –[0-9]=\d –[A-Za-z0-9]=\w –[\f\t\n\r ]=\s

36 Quantifying Curly brackets quantify repeats better than ‘*’ (0+) or ‘+’ (1+) a{3,5}=three, four or five ‘a’’s. >grep ‘la{3,5}’ If file contains “laaaad” -will find If file contains “laaaaaaad” -will not find

37 Referencing Back-slashes match the substring previously matched by the nth parenthesized subexpression of the regular expression. –The back-reference is denoted `\n', where n is a single digit >grep ‘(a)\1’ If file contains “laaaad” -will find If file contains “lad” -will not find

38 Back to our ProSite motif… We can use regular expressions to describe the motif –The motif is actually a REGULAR EXPRESSION! chr04.peptides fsa-4202->Annotated|04: : | frame 1; YDR448W/ADA2; Verified; this gene contains 1 exon chr04.peptides fsa:4203:MSNKFHCDVCSADCTNRVRVSCAICPEYDLCVPCFSQGSY TGKHRPYHDYRIIETNSYPILCPDWGADEELQLIKGAQTL >grep -n –E -–color –B2 ‘C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE ][YFVLI].[LIVFM]C.{2}C *.fsa

39 Did it work?

40 Let’s try this… Download the genomic DNA sequence from SGD Search for any variant of the TATA – box promoter –TATAAA –TATAAT –TATATT –TAATAA –TAATAT

41 More more more Many MS tools allow for wildcard searching The shell allows variables; interpolation; control structures –For example, attempt to find a palindrome of length 4 within genomic sequences (hint: use backreferences!) –Variables allow for persistence and control structures >myVar=`grep -n –E -–color ‘C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE ][YFVLI].[LIVFM]C.{2}C *.fsa` echo $myVar chr04.peptides fsa:4203:MSNKFHCDVCSADCTNRVRVSCAICPEYDLCVPCFSQGSY TGKHRPYHDYRIIETNSYPILCPDWGADEELQLIKGAQTL

42 A better variable interpolation The variable is allowed to change We can set the variable to the Prosite Pattern myVar=C\.{2}C\.{4,8}[RHDGSCV][YWFMVIL]\.[CS]\.{2,5}[CHEQ]\.[DNSAGE][YFVLI]\.[LIVF M]C\.{2}C echo $myVar C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE][YFVLI].[LIVFM]C.{2}C grep -n -E --color $myVar *.fsa chr04.peptides fsa:4203:MSNKFHCDVCSADCTNRVRVSCAICPEYDLCVPCFSQGSY TGKHRPYHDYRIIETNSYPILCPDWGADEELQLIKGAQTL

43 Variables can be overwritten The variable is allowed to change We can set the variable to the Prosite Pattern function afun { > for i in > do > echo $i > echo $myVar > done > } afun 1 C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE][YFVLI].[LIVFM]C.{2}C 2 C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE][YFVLI].[LIVFM]C.{2}C 3 C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE][YFVLI].[LIVFM]C.{2}C 4 C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE][YFVLI].[LIVFM]C.{2}C 5 C.{2}C.{4,8}[RHDGSCV][YWFMVIL].[CS].{2,5}[CHEQ].[DNSAGE][YFVLI].[LIVFM]C.{2}C

44 Functions What if we wanted to search every ProSite pattern against our genomic database? We’d have to repeatedly do our search –This is called a loop –We have to write this so the computer knows exactly what to repeat, how many times to repeat, and where to find the next ProSite pattern to match –We would store the what and where in VARIABLES –We would utilize a CONTROL STRUCTURE to handle the how…

45 Control structures All out programs so far have run from start to finish. Each line has been executed in turn. What if we only want to run some lines some of the time? This is where control structures come in.

46 Control structures Programming languages generally have a number of control structures. Basic structures: –if –while –for & foreach There are others (e.g. unless)

47 ‘for’ example >afunction() { for i in do echo "Looping... number $i" done }

48 Variables can interpolated The command is substituted from the system It’s like a pipe, but we are allowed to operate afun() { > myvar=$(ls -1 *.fsa) > for i in $myvar > do > echo $i > done > } afun chr01.fsa chr01.peptides fsa chr02.peptides fsa chr03.peptides fsa chr04.peptides fsa chr05.peptides fsa chr06.peptides fsa chr07.peptides fsa chr08.peptides fsa chr09.peptides fsa chr10.peptides fsa chr11.peptides fsa …

49 The ‘while’ control structure (combined with opening files) The ‘while’ control stucture keeps looping while a given condition is satisfied ‘while’ and open files go together very well: afun() { > while read f > do > echo $f > done > } afun < chrmt.peptides fsa >Notannotated|mt:385:459| frame 1 MNYILLLLLIKLLIIINMKLIKIL …

50 Editors Shell programming is like a batch file –Commands are linked together in a procedure –The procedure is accessed via a file We need an editor that will allow us to construct that file –We’ll use Emacs (or you can use vi, pico, …) –Comprehensive, extensible working environment –Complete (arguable!) IDE –Integration –Extensible (elisp)

51 Emacs Invoking Emacs is easy: emacs –nw filename In many cases, Emacs will work out the mode appropriate for your file (.cpp,.pl, etc…) –The mode allows Emacs to become sensitive to the task –There is a biomode for reverse complement, etc…. –You can write your own! Emacs has many tools –Search, replace, cut, paste, mail… –File navigation, ftp, remote shells…

52 The Emacs survival guide Notation –Emacs uses the control key and escape key heavily. We write it like this: C-x Pronounced "Control-x“ –Hold down the Ctrl key (usually in the lower left corner of the keyboard) while pressing the x key. –Both Ctrl and x must be down at the same time. M-x Pronounced "Meta-x" Press the Esc key (usually in the upper left corner of the keyboard), release it, then press the x key. –Esc and x should not be down at the same time. So C-x C-f means hold down the control key, then type x and then f while holding it down. (This is the command to load a file into emacs). Typing –Just type. All the regular keys, arrow keys, delete, backspace, and page up/down keys should work. Alternatively, you can try these commands: C-f cursor forward, C-b cursor back, C-p previous line, C-n next line, M-v page up, C-v page down. Exiting –Type C-x C-c. If you have any unsaved work, emacs will ask you if you want to save it. Type y. Other commands –Most control or escape sequences are commands. Usually a prompt appears in the command line at the bottom of the window. Here are a few: –C-x C-f Load file, prompt for filenameC-x C-s Save file without exiting C-x C-c Exit, prompt to save files C-s Search forward, prompt for search string C-r Search backward, prompt for search string C-h ?Show help options, prompt for choice C-h t Start emacs tutorial If you make a mistake or change your mind you can always escape: C-g –Abandon command and resume typing

53 Command line editing Learning the keybindings can be difficult –But it will increase your speed –Faster than using a mouse –Transferable! The keybindings for command line editing from Emacs is the default set of commands for line editing in the Bash Shell!

54 Let’s try it… Open up the file that we found contained the ProSite Motif Open a second window Goto the line that contains the motif (hint: use grep with –n!) Copy and paste that line into a new file Save and close that file

55 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 field1 filed2 field3 field4... $1 $2 $3 $4....

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

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

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


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