BOL: Related items

R programming and Jobs website

Pragati Singh — Sun, 25 May 2014 14:43:57 -0500

Welcome to the R Jobs section of ProgrammingR.com. If your organization has an R employment opportunity that you would like to have posted here, submit it via the contact page. Prospective employees: use the contact information provided in the position listing to apply or contact the hiring organization.

Address of the bookmark: http://www.programmingr.com/category/stype/r-job-listings/

RStudio

Jitendra Narayan — Sat, 27 Dec 2014 06:50:58 -0600

RStudio IDE is a powerful and productive user interface for R. It’s free and open source, and works great on Windows, Mac, and Linux.

The developers and expert trainers are the authors of several popular R packages, including ggplot2, plyr, lubridate, and others.

More at http://www.rstudio.com/

http://www.rstudio.com/products/RStudio/

Address of the bookmark: http://www.rstudio.com/

seqloc 0.6

Gudiya Pal — Sun, 28 Dec 2014 12:51:29 -0600

The Bio.SeqLoc modules in seqloc are designed to represent positions and locations (ranges of positions) on sequences, particularly nucleotide sequences. My original motivation for writing these packages was handing the locations of genes in eukaryotic genomes.

Handle sequence locations for bioinformatics http://www.ingolia-lab.org/seqloc-tutorial.html

Address of the bookmark: http://www.stackage.org/snapshot/nightly-2014-12-28/package/seqloc-0.6

Bioinformatics Scripts

Jit — Thu, 22 Jan 2015 22:29:39 -0600

Some of the useful bioinformatics scripts.

For example ... contig-stats.pl is a Perl script that will automatically describe features of a sequence assembly.

http://milkweedgenome.org/?q=scripts

Address of the bookmark: http://milkweedgenome.org/?q=scripts

Bioinformatics PhDs - Cover Letter

Martin Jones — Mon, 16 Feb 2015 12:48:52 -0600

Overview
The reception your cover letter will receive is more varied and unpredictable than the other elements of your application packet. Some readers, especially at large research universities, will skip it entirely, and focus instead on more direct indicators of your academic achievements and potential: the CV, letters, and writing sample. Most often, however, your cover letter works in tandem with your CV, and represents your best opportunity to communicate directly with your target audience prior to an interview.

The cover letter should not simply repeat the information contained in the CV; rather it should elaborate and frame the aspects of your academic training and background that you want search committee members to have uppermost in their minds as they consider your candidacy. At a minimum, it should contain a clear statement of your research and teaching interests, and how your qualifications match the requirements of the job description. Many disciplines have their own conventions and protocols for application materials including the cover letter. Be sure to show a draft of your letter to your chair or the department's placement advisor.

There is no perfect or even preferred style of cover letter save that tone should be that of a confident professional. Departments aren't interested in hiring graduate students (they already have enough of those). They are looking for serious scholars/teachers who will make interesting, congenial, and productive colleagues. While it is probably not a good use of your time to tailor your letter for each opening, you will probably need at least two base versions that emphasize different elements (You would not want to use the same cover letter to apply to Oberlin as UC Irvine). You may want to customize the letters for the three to five jobs most attractive to you.

Your cover letter should not exceed a page and a half or two at the most. No one will read a four-page letter, and your apparent inability to communicate your credentials in a concise manner is not to your advantage. Every line of your letter should serve a demonstrable purpose. Some people have gotten excellent jobs with a brief, boilerplate letter containing no more than a short intro, a paragraph on their research, and a couple of sentences on their teaching. Others use letters that discuss in very specific terms how they, their research, and their teaching would "fit" within the existing department and institutional setting. The choice of style is up to you, and should reflect what makes you feel most comfortable and most positive about your credentials.

There are, however, circumstances where a longer, more annotated version is more likely to be helpful. The issues you should take into account when making this decision are:

    The size of the department/institution
    The extent to which your research is mainstream and its significance readily apparent
    The extent to which your qualifications diverge from those mentioned in the job ad
    The extent to which the institution to which you are applying differs from UC Berkeley and the relative importance of teaching versus research
    Unusual circumstances or career paths

Size matters. The larger the department, the less detailed your letter needs to be. If there are already six people working in your sub-field, they can assess and translate the significance of your work to others in the department. If, however, you will be the only history of science person or the only physical anthropologist in the department, the search committee and others will likely need more help from you to understand the import of your work. Remember, if they are searching for your specialty they are understaffed in your area, and even if there is more than one person in your sub-field she/he may be on leave or otherwise uninvolved in the search.

Similarly, smaller departments are more likely to be concerned than larger ones about the specific courses you are prepared to teach. If there are certain core courses your position needs to cover, make it unambiguously clear that you are prepared to do so even if you haven't taught them already.

As a rule of thumb, the more your profile diverges from the specifics of the job description (or the norm, such that it exists), the more likely you will want to say more about why you are nonetheless a strong candidate. By doing so you can turn a question mark into an advantage. Highlight your strengths, and if you have time perform a little research on the department (see below) so you can explain how you would add to the department in ways that they might otherwise not have considered. Job descriptions are not always etched in stone. If you're very interested in the job, call the department and ask to speak to someone on the search committee. If that's too intimidating, call the departmental assistant or secretary. They can at least tell you if it’s a new position or replacement which in turn can indicate whether they really need someone who can teach The Politics of Southern Africa or if Middle Eastern Politics would do just as well. They may well be willing to sacrifice a course in an area that the ad specified in order to get the extra teaching experience or innovative research that you have to offer, but only if you give them the opportunity and explain what they'd get in return.

If you've taken an unusually long time to finish because you spent three years learning a new language in order to prepare for two years of original research or some other factor that enriches what you have to offer as a teacher or a scholar, let them know about it. Learning a new language, for example, is an indicator of your commitment to serious scholarship. Think of a way to put a positive valence on an aspect of your CV that you believe is likely to raise questions or doubts.

As hard as it may be for not-yet-employed-but-soon-to-be academics like yourselves to believe, there are some individuals and departments that are intimidated by you and your institutional pedigree. There are many fine schools and departments that are convinced that every Berkeley graduate student is only interested in a position at Harvard, Princeton, or (hold your nose) Stanford. If it is a small liberal arts college, they may also assume that you view teaching and advising undergraduates strictly as a necessary evil. Ergo, why interview someone who will either look down their nose at us, and/or desert us for greener pastures as soon as their third book has been published and Yale comes calling. They often don't seem to realize that Berkeley graduate students are sincerely interested in a wide range of academic settings for a variety of reasons personal and professional, and, perhaps more to the point, Yale rarely "comes calling." An even greater burden of proof exists if a quick scan of your CV reveals that your all of your experience in higher education has occurred in a large, elite, research-oriented setting. How can you overcome this potential obstacle especially if you're very interested in a school that you have reason to believe may be suspicious of Berkeley PhDs?

It's probably not advisable to write in a cover letter that they shouldn't be intimidated by lil' old you (i.e., "I'm really not very good; in fact, my advisor says I'm her worst graduate student in twenty years."), but there are ways to indicate a sincere interest in their department. One means is to do a little research, and briefly discuss how you might fit into the department and the institutional community-at-large. There are numerous articles written by faculty about the search process that state explicitly the positive impact it can have on their impression of a candidate to see evidence that that he/she has taken the time to learn something about them. Researching a department and its associated programs/research centers has never been easier. Virtually all colleges and universities are online, and their web addresses can be easily located using Education/Universities link.

A second way to address fears of imminent flight is to provide evidence of ties to the area, the university, or lifestyle.   If you are from the Midwest, have family nearby, or even if you just spent an enjoyable summer there, add a line about it and your desire to return to your cover letter for Purdue or Wayne State. If you did your undergraduate work at a similar type of institution, draw their attention to that link. Don't assume that they will notice where you got your BA on your CV, and make the connection.

If you are applying to small, liberal arts colleges, don't just list the courses you've taught with a line of boilerplate about how important you take your teaching responsibilities to be. These days, a good, small college has a list price of about $30,000 a year, and close contact with people like you is one of their key selling points to parents and potential students. You are expected to be more than a lecturer, and your ability to convey your recognition of that fact and a sincere interest in working closely with students matters. Advising, participating in non-academic activities, watching your students grow and mature inside the classroom and out (and having an influence on that process) can be among the most rewarding aspects of the profession. If you value these broader elements of being a professor, let them know. In particular, if your own experience has been limited to large universities, think about describing an episode where you had a positive impact on the development of a student and the satisfaction you derived from helping him or her. At many small colleges, and large universities (including Berkeley) as well, one of the most significant pedagogical trends is fostering greater student involvement in faculty research. If you can articulate how this might occur for you and their students in a brief but thoughtful manner, it can alleviate some of the concerns occasioned by your Berkeley background.

Your letter typically will have four segments: the introduction, research, teaching, and the closing.

Introduction
Be sure to identify the position you are applying for by rank and sub-field in the first sentence or two. It is not uncommon for departments to be engaged in more than one search in a given year, and large departments may have more than one in your sub-field. If it is an open rank position and you are applying as an assistant professor, in most cases you and your record of accomplishments will not be directly compared with those of more experienced candidates applying for it at the associate or full professor level. Rather, applicants are assessed based on where they are in their career path, and you have every chance of successfully competing against them.

If you have finished, mention it up front. If not, state when you expect to file - no later than June 2003. Many readers will view your optimistic prediction with a skeptical eye, and anything you can say that makes the claim appear more credible (e.g., "I have written and my chair has reviewed four of the six chapters.") can help mitigate their concerns. You can put such a statement in the introduction or wait until you discuss the dissertation itself.

If your discipline holds its annual meeting in the summer or early fall (i.e., before application deadlines) and you had an excellent conference interview, make reference to it in the cover letter including the names of the faculty with whom you spoke. By the time people actually start to read files, months may have passed and even the strongest of impressions can fade. But they can be rehabilitated and revived, especially if you can remind them of a specific strength, ability, or issue that seemed particularly salient during the interview.
Research
Unless you are applying to a school that cares only about your teaching (increasingly rare), a description of your research generally follows next. The challenge here is not simply to describe your research, but to frame it in terms of your sub-field and discipline. The search committee, hasn't lived, eaten and breathed Post-Edwardian Hermeneutics for the past five years the way you have. And they haven't been there every step of the torturous process like your friends and significant others. So forgive them for not immediately recognizing your research at first blush for the path-breaking work that it is.

Departments want to know that in hiring you, they are adding someone who will make a future contribution to the discipline and enhance the reputation of the department. However, they are often ill-equipped to understand exactly how that will be true in your particular case. Many disciplines are sufficiently broad that leading or cutting-edge research in one sub-field is barely intelligible to those in others. In addition, when you became a candidate for the short list, your file will be read by department members outside your specialty, and, oftentimes later on in the process, by individuals outside your discipline as well. You need to describe the forest in which your tree resides, and explain why it matters in terms of the broader trends and issues within your discipline. Obviously, if your work is focused on one of the classic conundrums of your field, much less in the way of providing perspective is necessary than if you are addressing an emergent issue or employing an unconventional approach.

If your research is particularly novel or cutting-edge, any markers of broader acceptance by other, more established scholars or scholarly organs in your field can ameliorate possible concerns about its relevance and potential importance. In discussing your work, note the recognition it has received in the form of competitive grants, awards, publications in refereed journals, and/or presentations at major conferences.

It is also important to mention where you expect your research to go after the completion of your dissertation and the publications that will flow from it. They, especially at research-oriented institutions, want to know at least in broad terms where you expect to go from here. They want to see evidence of a scholarly agenda that extends beyond the dissertation. You don't need to have pages written or titles blocked out, but you need to tell them in a paragraph, (two at the most) about what questions intrigue you, and how you expect to go about finding the answers to them. These questions for future research may have been generated by the findings of your dissertation, unusual data uncovered during your fieldwork, or interesting side issues that you were forced to put off in order to keep your dissertation taut and focused. Think twice about mentioning future projects that appear entirely unrelated to your current work. Departments will want you to be firmly established in one area before you go off into another.

The relative importance of teaching versus research is a continuous and not a discrete variable. Even schools that emphasize teaching in their job listing will generally want evidence of scholarly engagement and publishing potential. It is a very competitive market for students out there, and virtually all institutions are under pressure to sell themselves via the quality of their faculty to the limited number of good students in the applicant pool. A good marker for the relative importance of teaching versus research is the teaching load. An institution with a 3-2 teaching load (a total of five courses taught per two-semester year) will expect more in the way of and value research more highly than one with a 3-3 load.

If you work in a capital-intensive area, mention your track record of gaining grants and other sources of external funding.
Teaching
In a similar fashion, the more the institution you are applying to diverges from Berkeley and the more your profile differs from the job description, the more expansive you should be in talking about your teaching and what you have to offer their students. If you have won a teaching award at Berkeley, don't make them wait until they read your CV to discover that fact.

For letters sent to large universities where you will be expected to teach large, lecture courses and graduate seminars, little is needed except to convey that you have the necessary experience and/or background. Since the dominant pedagogical style is the same as that found at Berkeley, it will be assumed that you will be able to do the same for them.

If you have TA'd some of the courses that (based on the job description) you would be expected to offer, let them know. If you have not had that opportunity, but your fields and research fall within the domain of the job description, you may want to add a line about how well prepared you are to teach such courses based on your training and research.

If your profile does not correspond exactly to the description found in the job announcement, but you believe that you could nonetheless teach the required courses, explain the basis for your confidence. What strength would you bring to the department that would more than make up for your "otherness"? Departments may decide that they don't "need" another conventional European historian if you can convince them that you can handle the core courses and offer something new that they don't currently cover as well. In this case especially, think about doing some research so you can speak in more specific terms about how you would fit into and enhance the department's offerings. Help them visualize how you would strengthen them as a department.

Small colleges will want to know that you are able to teach on a more intimate basis and are prepared to take the time to do it well. If you give them three generic lines about how "important" you consider your teaching responsibilities, don't expect much of a positive response. Spend a couple of paragraphs describing your teaching experience and philosophy, and how you would take advantage of the opportunity to create you own courses.

If you've had the opportunity to design and teach your own course, tell them, briefly, how you went about it and the choices you made. Don't just say you're a good teacher, tell them why. Look over your teaching evaluations and pick out one or two consistent strengths to highlight. Drawing on your experience, talk about how you engage students and enhance their skills (especially writing) and intellectual development.

For good, small colleges, the quality of the teaching offered to students is their stock-in- trade. Even the most research-oriented, small colleges take teaching undergraduates very seriously. You need to demonstrate that you take it seriously as well, and can talk about it using more than vague generalities and shop-worn cliches.
Closing/Enclosures
Wrap it up quickly. If you are going to be traveling for any significant portion of the job search season be sure to let them know how they can contact you (email, cellphone and/or a Pacific Bell message center account are particularly good options).

Before closing, include a sentence where you list the materials you have enclosed (e.g., CV, dissertation abstract, transcripts, teaching statement/portfolio, writing samples, etc.) and are having sent separately (letters of recommendation). You will often be assembling multiple packets at the same time (as in midnight October 14th, midnight November 14th, etc.) for jobs that ask for different combinations of enclosures. In addition to telling them what they should have received, it serves as a handy list for you to check before sealing the envelope.

Should you send a writing sample, even if they haven't asked for one? Unless the norm in your discipline is to never send more than they ask for, if you've been smart and have already run off thirty copies at two cents per page (that's only sixty cents for a thirty page chapter) by all means send it. That way it's in the file should someone become interested in you and want to read more.

BINC Sample Question Paper !!!

Jitendra Narayan — Thu, 16 Apr 2015 09:14:14 -0500

BINC sample question paper round TWO.

Perl One liner basics !!

Abhimanyu Singh — Sun, 24 May 2015 09:28:33 -0500

Perl has a ton of command line switches (see perldoc perlrun), but I'm just going to cover the ones you'll commonly need to debug code. The most important switch is -e, for execute (or maybe "engage" :) ). The -e switch takes a quoted string of Perl code and executes it. For example:

$ perl -e 'print "Hello, World!\n"'
Hello, World!

It's important that you use single-quotes to quote the code for -e. This usually means you can't use single-quotes within the one liner code. If you're using Windows cmd.exe or PowerShell, you must use double-quotes instead.

I'm always forgetting what Perl's predefined special variables do, and often test them at the command line with a one liner to see what they contain. For instance do you remember what $^O is?

$ perl -e 'print "$^O\n"'
linux

It's the operating system name. With that cleared up, let's see what else we can do. If you're using a relatively new Perl (5.10.0 or higher) you can use the -E switch instead of -e. This turns on some of Perl's newer features, like say, which prints a string and appends a newline to it. This saves typing and makes the code cleaner:

$ perl -E 'say "$^O"'
linux

Pretty handy! say is a nifty feature that you'll use again and again.

Frequent words problem solution by Perl

Jit — Tue, 09 Jun 2015 23:38:44 -0500

Solved with perl http://rosalind.info/problems/1a/

#Find the most frequent k-mers in a string.
#Given: A DNA string Text and an integer k.
#Return: All most frequent k-mers in Text (in any order).

use strict;
use warnings;

my $string="ACGTTGCATGTCGCATGATGCATGAGAGCT";
my $kmer=4;
my %myHash;
my $max=0;

for (my $aa=0; $aa<=(length($string)-4); $aa++) {
   my $myStr=substr $string, $aa,$kmer;
   #print "$myStr\n";
   my $km=kmerMatch ($string, $myStr, $kmer);
   if ($km > $max) { $max = $km;}
   #print "$km\t$myStr\n";
   $myHash{$myStr}=$km;

}

#Print all key which have matching values
foreach my $name (keys %myHash){
    print "$name " if $myHash{$name} == $max;
}

sub kmerMatch { #Check the exact matching kmers with sliding window
my ($string, $myStr, $kmer)=@_;
my $count=0;
for (my $aa=0; $aa<=(length($string)-4); $aa++) {
   my $myWin=substr $string, $aa,$kmer;
   if ($myWin eq $myStr) {
       #print "$myWin eq $myStr\n";
       $count++;
   }
}
return $count;
}

Clump Finding Problem Solved with Perl

Jit — Wed, 10 Jun 2015 00:17:17 -0500

The question at http://rosalind.info/problems/1d/

Script are moved to http://bioinformaticsonline.com/snippets/view/34633/clump-finding-problem-solved-with-perl

Software packages for next gen sequence analysis

Rahul Nayak — Fri, 19 Jun 2015 21:07:15 -0500

Integrated solutions
* CLCbio Genomics Workbench - de novo and reference assembly of Sanger, Roche FLX, Illumina, Helicos, and SOLiD data. Commercial next-gen-seq software that extends the CLCbio Main Workbench software. Includes SNP detection, CHiP-seq, browser and other features. Commercial. Windows, Mac OS X and Linux.
* Galaxy - Galaxy = interactive and reproducible genomics. A job webportal.
* Genomatix - Integrated Solutions for Next Generation Sequencing data analysis.
* JMP Genomics - Next gen visualization and statistics tool from SAS. They are working with NCGR to refine this tool and produce others.
* NextGENe - de novo and reference assembly of Illumina, SOLiD and Roche FLX data. Uses a novel Condensation Assembly Tool approach where reads are joined via "anchors" into mini-contigs before assembly. Includes SNP detection, CHiP-seq, browser and other features. Commercial. Win or MacOS.
* SeqMan Genome Analyser - Software for Next Generation sequence assembly of Illumina, Roche FLX and Sanger data integrating with Lasergene Sequence Analysis software for additional analysis and visualization capabilities. Can use a hybrid templated/de novo approach. Commercial. Win or Mac OS X.
* SHORE - SHORE, for Short Read, is a mapping and analysis pipeline for short DNA sequences produced on a Illumina Genome Analyzer. A suite created by the 1001 Genomes project. Source for POSIX.
* SlimSearch - Fledgling commercial product.

Align/Assemble to a reference
* BFAST - Blat-like Fast Accurate Search Tool. Written by Nils Homer, Stanley F. Nelson and Barry Merriman at UCLA.
* Bowtie - Ultrafast, memory-efficient short read aligner. It aligns short DNA sequences (reads) to the human genome at a rate of 25 million reads per hour on a typical workstation with 2 gigabytes of memory. Uses a Burrows-Wheeler-Transformed (BWT) index. Link to discussion thread here. Written by Ben Langmead and Cole Trapnell. Linux, Windows, and Mac OS X.
* BWA - Heng Lee's BWT Alignment program - a progression from Maq. BWA is a fast light-weighted tool that aligns short sequences to a sequence database, such as the human reference genome. By default, BWA finds an alignment within edit distance 2 to the query sequence. C++ source.
* ELAND - Efficient Large-Scale Alignment of Nucleotide Databases. Whole genome alignments to a reference genome. Written by Illumina author Anthony J. Cox for the Solexa 1G machine.
* Exonerate - Various forms of pairwise alignment (including Smith-Waterman-Gotoh) of DNA/protein against a reference. Authors are Guy St C Slater and Ewan Birney from EMBL. C for POSIX.
* GenomeMapper - GenomeMapper is a short read mapping tool designed for accurate read alignments. It quickly aligns millions of reads either with ungapped or gapped alignments. A tool created by the 1001 Genomes project. Source for POSIX.
* GMAP - GMAP (Genomic Mapping and Alignment Program) for mRNA and EST Sequences. Developed by Thomas Wu and Colin Watanabe at Genentec. C/Perl for Unix.
* gnumap - The Genomic Next-generation Universal MAPper (gnumap) is a program designed to accurately map sequence data obtained from next-generation sequencing machines (specifically that of Solexa/Illumina) back to a genome of any size. It seeks to align reads from nonunique repeats using statistics. From authors at Brigham Young University. C source/Unix.
* MAQ - Mapping and Assembly with Qualities (renamed from MAPASS2). Particularly designed for Illumina with preliminary functions to handle ABI SOLiD data. Written by Heng Li from the Sanger Centre. Features extensive supporting tools for DIP/SNP detection, etc. C++ source
* MOSAIK - MOSAIK produces gapped alignments using the Smith-Waterman algorithm. Features a number of support tools. Support for Roche FLX, Illumina, SOLiD, and Helicos. Written by Michael Strömberg at Boston College. Win/Linux/MacOSX
* MrFAST and MrsFAST - mrFAST & mrsFAST are designed to map short reads generated with the Illumina platform to reference genome assemblies; in a fast and memory-efficient manner. Robust to INDELs and MrsFAST has a bisulphite mode. Authors are from the University of Washington. C as source.
* MUMmer - MUMmer is a modular system for the rapid whole genome alignment of finished or draft sequence. Released as a package providing an efficient suffix tree library, seed-and-extend alignment, SNP detection, repeat detection, and visualization tools. Version 3.0 was developed by Stefan Kurtz, Adam Phillippy, Arthur L Delcher, Michael Smoot, Martin Shumway, Corina Antonescu and Steven L Salzberg - most of whom are at The Institute for Genomic Research in Maryland, USA. POSIX OS required.
* Novocraft - Tools for reference alignment of paired-end and single-end Illumina reads. Uses a Needleman-Wunsch algorithm. Can support Bis-Seq. Commercial. Available free for evaluation, educational use and for use on open not-for-profit projects. Requires Linux or Mac OS X.
* PASS - It supports Illumina, SOLiD and Roche-FLX data formats and allows the user to modulate very finely the sensitivity of the alignments. Spaced seed intial filter, then NW dynamic algorithm to a SW(like) local alignment. Authors are from CRIBI in Italy. Win/Linux.
* RMAP - Assembles 20 - 64 bp Illumina reads to a FASTA reference genome. By Andrew D. Smith and Zhenyu Xuan at CSHL. (published in BMC Bioinformatics). POSIX OS required.
* SeqMap - Supports up to 5 or more bp mismatches/INDELs. Highly tunable. Written by Hui Jiang from the Wong lab at Stanford. Builds available for most OS's.
* SHRiMP - Assembles to a reference sequence. Developed with Applied Biosystem's colourspace genomic representation in mind. Authors are Michael Brudno and Stephen Rumble at the University of Toronto. POSIX.
* Slider- An application for the Illumina Sequence Analyzer output that uses the probability files instead of the sequence files as an input for alignment to a reference sequence or a set of reference sequences. Authors are from BCGSC. Paper is here.
* SOAP - SOAP (Short Oligonucleotide Alignment Program). A program for efficient gapped and ungapped alignment of short oligonucleotides onto reference sequences. The updated version uses a BWT. Can call SNPs and INDELs. Author is Ruiqiang Li at the Beijing Genomics Institute. C++, POSIX.
* SSAHA - SSAHA (Sequence Search and Alignment by Hashing Algorithm) is a tool for rapidly finding near exact matches in DNA or protein databases using a hash table. Developed at the Sanger Centre by Zemin Ning, Anthony Cox and James Mullikin. C++ for Linux/Alpha.
* SOCS - Aligns SOLiD data. SOCS is built on an iterative variation of the Rabin-Karp string search algorithm, which uses hashing to reduce the set of possible matches, drastically increasing search speed. Authors are Ondov B, Varadarajan A, Passalacqua KD and Bergman NH.
* SWIFT - The SWIFT suit is a software collection for fast index-based sequence comparison. It contains: SWIFT — fast local alignment search, guaranteeing to find epsilon-matches between two sequences. SWIFT BALSAM — a very fast program to find semiglobal non-gapped alignments based on k-mer seeds. Authors are Kim Rasmussen (SWIFT) and Wolfgang Gerlach (SWIFT BALSAM)
* SXOligoSearch - SXOligoSearch is a commercial platform offered by the Malaysian based Synamatix. Will align Illumina reads against a range of Refseq RNA or NCBI genome builds for a number of organisms. Web Portal. OS independent.
* Vmatch - A versatile software tool for efficiently solving large scale sequence matching tasks. Vmatch subsumes the software tool REPuter, but is much more general, with a very flexible user interface, and improved space and time requirements. Essentially a large string matching toolbox. POSIX.
* Zoom - ZOOM (Zillions Of Oligos Mapped) is designed to map millions of short reads, emerged by next-generation sequencing technology, back to the reference genomes, and carry out post-analysis. ZOOM is developed to be highly accurate, flexible, and user-friendly with speed being a critical priority. Commercial. Supports Illumina and SOLiD data.

De novo Align/Assemble
* ABySS - Assembly By Short Sequences. ABySS is a de novo sequence assembler that is designed for very short reads. The single-processor version is useful for assembling genomes up to 40-50 Mbases in size. The parallel version is implemented using MPI and is capable of assembling larger genomes. By Simpson JT and others at the Canada's Michael Smith Genome Sciences Centre. C++ as source.
* ALLPATHS - ALLPATHS: De novo assembly of whole-genome shotgun microreads. ALLPATHS is a whole genome shotgun assembler that can generate high quality assemblies from short reads. Assemblies are presented in a graph form that retains ambiguities, such as those arising from polymorphism, thereby providing information that has been absent from previous genome assemblies. Broad Institute.
* Edena - Edena (Exact DE Novo Assembler) is an assembler dedicated to process the millions of very short reads produced by the Illumina Genome Analyzer. Edena is based on the traditional overlap layout paradigm. By D. Hernandez, P. François, L. Farinelli, M. Osteras, and J. Schrenzel. Linux/Win.
* EULER-SR - Short read de novo assembly. By Mark J. Chaisson and Pavel A. Pevzner from UCSD (published in Genome Research). Uses a de Bruijn graph approach.
* MIRA2 - MIRA (Mimicking Intelligent Read Assembly) is able to perform true hybrid de-novo assemblies using reads gathered through 454 sequencing technology (GS20 or GS FLX). Compatible with 454, Solexa and Sanger data. Linux OS required.
* SEQAN - A Consistency-based Consensus Algorithm for De Novo and Reference-guided Sequence Assembly of Short Reads. By Tobias Rausch and others. C++, Linux/Win.
* SHARCGS - De novo assembly of short reads. Authors are Dohm JC, Lottaz C, Borodina T and Himmelbauer H. from the Max-Planck-Institute for Molecular Genetics.
* SSAKE - The Short Sequence Assembly by K-mer search and 3' read Extension (SSAKE) is a genomics application for aggressively assembling millions of short nucleotide sequences by progressively searching for perfect 3'-most k-mers using a DNA prefix tree. Authors are René Warren, Granger Sutton, Steven Jones and Robert Holt from the Canada's Michael Smith Genome Sciences Centre. Perl/Linux.
* SOAPdenovo - Part of the SOAP suite. See above.
* VCAKE - De novo assembly of short reads with robust error correction. An improvement on early versions of SSAKE.
* Velvet - Velvet is a de novo genomic assembler specially designed for short read sequencing technologies, such as Solexa or 454. Need about 20-25X coverage and paired reads. Developed by Daniel Zerbino and Ewan Birney at the European Bioinformatics Institute (EMBL-EBI).

SNP/Indel Discovery
* ssahaSNP - ssahaSNP is a polymorphism detection tool. It detects homozygous SNPs and indels by aligning shotgun reads to the finished genome sequence. Highly repetitive elements are filtered out by ignoring those kmer words with high occurrence numbers. More tuned for ABI Sanger reads. Developers are Adam Spargo and Zemin Ning from the Sanger Centre. Compaq Alpha, Linux-64, Linux-32, Solaris and Mac
* PolyBayesShort - A re-incarnation of the PolyBayes SNP discovery tool developed by Gabor Marth at Washington University. This version is specifically optimized for the analysis of large numbers (millions) of high-throughput next-generation sequencer reads, aligned to whole chromosomes of model organism or mammalian genomes. Developers at Boston College. Linux-64 and Linux-32.
* PyroBayes - PyroBayes is a novel base caller for pyrosequences from the 454 Life Sciences sequencing machines. It was designed to assign more accurate base quality estimates to the 454 pyrosequences. Developers at Boston College.

Genome Annotation/Genome Browser/Alignment Viewer/Assembly Database
* EagleView - An information-rich genome assembler viewer. EagleView can display a dozen different types of information including base quality and flowgram signal. Developers at Boston College.
* LookSeq - LookSeq is a web-based application for alignment visualization, browsing and analysis of genome sequence data. LookSeq supports multiple sequencing technologies, alignment sources, and viewing modes; low or high-depth read pileups; and easy visualization of putative single nucleotide and structural variation. From the Sanger Centre.
* MapView - MapView: visualization of short reads alignment on desktop computer. From the Evolutionary Genomics Lab at Sun-Yat Sen University, China. Linux.
* SAM - Sequence Assembly Manager. Whole Genome Assembly (WGA) Management and Visualization Tool. It provides a generic platform for manipulating, analyzing and viewing WGA data, regardless of input type. Developers are Rene Warren, Yaron Butterfield, Asim Siddiqui and Steven Jones at Canada's Michael Smith Genome Sciences Centre. MySQL backend and Perl-CGI web-based frontend/Linux.
* STADEN - Includes GAP4. GAP5 once completed will handle next-gen sequencing data. A partially implemented test version is available here
* XMatchView - A visual tool for analyzing cross_match alignments. Developed by Rene Warren and Steven Jones at Canada's Michael Smith Genome Sciences Centre. Python/Win or Linux.

Counting e.g. CHiP-Seq, Bis-Seq, CNV-Seq
* BS-Seq - The source code and data for the "Shotgun Bisulphite Sequencing of the Arabidopsis Genome Reveals DNA Methylation Patterning" Nature paper by Cokus et al. (Steve Jacobsen's lab at UCLA). POSIX.
* CHiPSeq - Program used by Johnson et al. (2007) in their Science publication
* CNV-Seq - CNV-seq, a new method to detect copy number variation using high-throughput sequencing. Chao Xie and Martti T Tammi at the National University of Singapore. Perl/R.
* FindPeaks - perform analysis of ChIP-Seq experiments. It uses a naive algorithm for identifying regions of high coverage, which represent Chromatin Immunoprecipitation enrichment of sequence fragments, indicating the location of a bound protein of interest. Original algorithm by Matthew Bainbridge, in collaboration with Gordon Robertson. Current code and implementation by Anthony Fejes. Authors are from the Canada's Michael Smith Genome Sciences Centre. JAVA/OS independent. Latest versions available as part of the Vancouver Short Read Analysis Package
* MACS - Model-based Analysis for ChIP-Seq. MACS empirically models the length of the sequenced ChIP fragments, which tends to be shorter than sonication or library construction size estimates, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome sequence, allowing for more sensitive and robust prediction. Written by Yong Zhang and Tao Liu from Xiaole Shirley Liu's Lab.
* PeakSeq - PeakSeq: Systematic Scoring of ChIP-Seq Experiments Relative to Controls. a two-pass approach for scoring ChIP-Seq data relative to controls. The first pass identifies putative binding sites and compensates for variation in the mappability of sequences across the genome. The second pass filters out sites that are not significantly enriched compared to the normalized input DNA and computes a precise enrichment and significance. By Rozowsky J et al. C/Perl.
* QuEST - Quantitative Enrichment of Sequence Tags. Sidow and Myers Labs at Stanford. From the 2008 publication Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data. (C++)
* SISSRs - Site Identification from Short Sequence Reads. BED file input. Raja Jothi @ NIH. Perl.
**See also this thread for ChIP-Seq, until I get time to update this list.

Alternate Base Calling
* Rolexa - R-based framework for base calling of Solexa data. Project publication
* Alta-cyclic - "a novel Illumina Genome-Analyzer (Solexa) base caller"

Transcriptomics
* ERANGE - Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq. Supports Bowtie, BLAT and ELAND. From the Wold lab.
* G-Mo.R-Se - G-Mo.R-Se is a method aimed at using RNA-Seq short reads to build de novo gene models. First, candidate exons are built directly from the positions of the reads mapped on the genome (without any ab initio assembly of the reads), and all the possible splice junctions between those exons are tested against unmapped reads. From CNS in France.
* MapNext - MapNext: A software tool for spliced and unspliced alignments and SNP detection of short sequence reads. From the Evolutionary Genomics Lab at Sun-Yat Sen University, China.
* QPalma - Optimal Spliced Alignments of Short Sequence Reads. Authors are Fabio De Bona, Stephan Ossowski, Korbinian Schneeberger, and Gunnar Rätsch. A paper is available.
* RSAT - RSAT: RNA-Seq Analysis Tools. RNASAT is developed and maintained by Hui Jiang at Stanford University.
* TopHat - TopHat is a fast splice junction mapper for RNA-Seq reads. It aligns RNA-Seq reads to mammalian-sized genomes using the ultra high-throughput short read aligner Bowtie, and then analyzes the mapping results to identify splice junctions between exons. TopHat is a collaborative effort between the University of Maryland and the University of California, Berkeley