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	<title><![CDATA[BOL: Related items]]></title>
	<link>https://bioinformaticsonline.com/related/2423?offset=120</link>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/9639/find-certain-filesdocuments-in-linux-os</guid>
	<pubDate>Sun, 06 Apr 2014 23:56:18 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/9639/find-certain-filesdocuments-in-linux-os</link>
	<title><![CDATA[Find certain files/documents in Linux OS]]></title>
	<description><![CDATA[<p>As bioinformatician I know the fact that we usually handle the large dataset and lost in the huge numbers of files and folders. In order to search the missing file a strong search command is required. The Linux Find Command is one of the most important and much used command in Linux sytems. Find command used to search and locate list of files and directories based on conditions you specify for files that match the arguments. Find can be used in variety of conditions like you can find files by permissions, users, groups, file type, date, size and other possible criteria.<br /><br />Through this article we are sharing our day-to-day Linux find command experience and its usage in the form of examples. In this article we will show you the most used 35 Find Commands examples in Linux. We have divided the section into Five parts from basic to advance usage of find command.</p><p><strong>Part I &ndash; Basic Find Commands for Finding Files with Names</strong><br />1. Find Files Using Name in Current Directory<br /><br />Find all the files whose name is gene.txt in a current working directory.<br /><br /># find . -name gene.txt<br /><br />./gene.txt<br /><br />2. Find Files Under Home Directory<br /><br />Find all the files under /home directory with name gene.txt.<br /><br /># find /home -name gene.txt<br /><br />/home/gene.txt<br /><br />3. Find Files Using Name and Ignoring Case<br /><br />Find all the files whose name is gene.txt and contains both capital and small letters in /home directory.<br /><br /># find /home -iname gene.txt<br /><br />./gene.txt<br />./Gene.txt<br /><br />4. Find Directories Using Name<br /><br />Find all directories whose name is Gene in / directory.<br /><br /># find / -type d -name Gene<br /><br />/Gene<br /><br />5. Find fasta Files Using Name<br /><br />Find all php files whose name is gene.fasta in a current working directory.<br /><br /># find . -type f -name gene.fasta<br /><br />./gene.fasta<br /><br />6. Find all PHP Files in Directory<br /><br />Find all fasta files in a directory.<br /><br /># find . -type f -name "*.fasta"<br /><br />./gene.fasta<br />./cancer.fasta<br />./allgene.fasta<br /><br /><strong>Part II &ndash; Find Files Based on their Permissions</strong><br />7. Find Files With 777 Permissions<br /><br />Find all the files whose permissions are 777.<br /><br /># find . -type f -perm 0777 -print<br /><br />8. Find Files Without 777 Permissions<br /><br />Find all the files without permission 777.<br /><br /># find / -type f ! -perm 777<br /><br />9. Find SGID Files with 644 Permissions<br /><br />Find all the SGID bit files whose permissions set to 644.<br /><br /># find / -perm 2644<br /><br />10. Find Sticky Bit Files with 551 Permissions<br /><br />Find all the Sticky Bit set files whose permission are 551.<br /><br /># find / -perm 1551<br /><br />11. Find SUID Files<br /><br />Find all SUID set files.<br /><br /># find / -perm /u=s<br /><br />12. Find SGID Files<br /><br />Find all SGID set files.<br /><br /># find / -perm /g+s<br /><br />13. Find Read Only Files<br /><br />Find all Read Only files.<br /><br /># find / -perm /u=r<br /><br />14. Find Executable Files<br /><br />Find all Executable files.<br /><br /># find / -perm /a=x<br /><br />15. Find Files with 777 Permissions and Chmod to 644<br /><br />Find all 777 permission files and use chmod command to set permissions to 644.<br /><br /># find / -type f -perm 0777 -print -exec chmod 644 {} \;<br /><br />16. Find Directories with 777 Permissions and Chmod to 755<br /><br />Find all 777 permission directories and use chmod command to set permissions to 755.<br /><br /># find / -type d -perm 777 -print -exec chmod 755 {} \;<br /><br />17. Find and remove single File<br /><br />To find a single file called gene.txt and remove it.<br /><br /># find . -type f -name "gene.txt" -exec rm -f {} \;<br /><br />18. Find and remove Multiple File<br /><br />To find and remove multiple files such as .fa or .gb, then use.<br /><br /># find . -type f -name "*.fa" -exec rm -f {} \;<br /><br />OR<br /><br /># find . -type f -name "*.gb" -exec rm -f {} \;<br /><br />19. Find all Empty Files<br /><br />To file all empty files under certain path.<br /><br /># find /tmp -type f -empty<br /><br />20. Find all Empty Directories<br /><br />To file all empty directories under certain path.<br /><br /># find /tmp -type d -empty<br /><br />21. File all Hidden Files<br /><br />To find all hidden files, use below command.<br /><br /># find /tmp -type f -name ".*"<br /><br /><strong>Part III &ndash; Search Files Based On Owners and Groups</strong><br />22. Find Single File Based on User<br /><br />To find all or single file called gene.txt under / root directory of owner root.<br /><br /># find / -user root -name gene.txt<br /><br />23. Find all Files Based on User<br /><br />To find all files that belongs to user Rahul under /home directory.<br /><br /># find /home -user rahul<br /><br />24. Find all Files Based on Group<br /><br />To find all files that belongs to group Developer under /home directory.<br /><br /># find /home -group developer<br /><br />25. Find Particular Files of User<br /><br />To find all .txt files of user Rahul under /home directory.<br /><br /># find /home -user rahul -iname "*.txt"<br /><br /><strong>Part IV &ndash; Find Files and Directories Based on Date and Time</strong><br />26. Find Last 50 Days Modified Files<br /><br />To find all the files which are modified 50 days back.<br /><br /># find / -mtime 50<br /><br />27. Find Last 50 Days Accessed Files<br /><br />To find all the files which are accessed 50 days back.<br /><br /># find / -atime 50<br /><br />28. Find Last 50-100 Days Modified Files<br /><br />To find all the files which are modified more than 50 days back and less than 100 days.<br /><br /># find / -mtime +50 &ndash;mtime -100<br /><br />29. Find Changed Files in Last 1 Hour<br /><br />To find all the files which are changed in last 1 hour.<br /><br /># find / -cmin -60<br /><br />30. Find Modified Files in Last 1 Hour<br /><br />To find all the files which are modified in last 1 hour.<br /><br /># find / -mmin -60<br /><br />31. Find Accessed Files in Last 1 Hour<br /><br />To find all the files which are accessed in last 1 hour.<br /><br /># find / -amin -60<br /><br /><strong>Part V &ndash; Find Files and Directories Based on Size</strong><br />32. Find 50MB Files<br /><br />To find all 50MB files, use.<br /><br /># find / -size 50M<br /><br />33. Find Size between 50MB &ndash; 100MB<br /><br />To find all the files which are greater than 50MB and less than 100MB.<br /><br /># find / -size +50M -size -100M<br /><br />34. Find and Delete 100MB Files<br /><br />To find all 100MB files and delete them using one single command.<br /><br /># find / -size +100M -exec rm -rf {} \;<br /><br />35. Find Specific Files and Delete<br /><br />Find all .gb files with more than 10MB and delete them using one single command.<br /><br /># find / -type f -name *.gb -size +10M -exec rm {} \;</p>]]></description>
	<dc:creator>Rahul Nayak</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10127/assistant-professor-at-sardar-patel-university</guid>
  <pubDate>Mon, 21 Apr 2014 21:03:55 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor at SARDAR PATEL UNIVERSITY]]></title>
  <description><![CDATA[
<p>SARDAR PATEL UNIVERSITY<br />Centre for Interdisciplinary Studies in Science and Technology</p>

<p>No.: SPU/CISST/Advt./2014-15/519</p>

<p>ADVERTISEMENT for Teaching Positions (Contractual)</p>

<p>Applications for the following Contractual Teaching Position are invited for Centre for Interdisciplinary Studies in Science and Technology (CISST), Sardar Patel University:</p>

<p>2. Assistant Professor (ONE) (Contractual)</p>

<p>For the subject of Bioinformatics</p>

<p>Qualifications:</p>

<p>(I) Good academic record as defined by the concerned university with at least 55 % marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master’s level</p>

<p>(II) Ph.D. degree in the concerned subject or in a relevant interdisciplinary subject<br />from an Indian University or NET/SLET clearance Contractual appointment carries a total Fixed Emoluments of Rs. 30,000/- p.m without any assurance of permanent Positions and related benefits.</p>

<p>An Application Form in prescribed Performa, available on University Website: www.spuvvn.edu should be filled in completely in Twelve Copies with self attested copies of certificates of qualifications and experience. Only one copy of each mark sheet be attached with the first copy of the application form. All 12 (Twelve) Application forms should be sent to Registrar’s office along with Demand Draft of Application form fee of Rs. 250/- (Non-refundable) in favour of “REGISTRAR, SARDAR PATEL UNIVERSITY, VALLABH VIDYANAGAR”. The S.C. and S.T. category candidates need not to pay Application fee.</p>

<p>Applicants who are in service should apply through their present employers. Candidates called for interview shall be required to attend at their own cost.</p>

<p>In absence of suitable candidate, the University may relax the eligibility criteria, for conditional appointment.</p>

<p>The last date of receipt of application by the University is 30th April, 2014</p>

<p>Advertisement: www.spuvvn.edu/careers/CISST%20Advt.%20April%202014.pdf</p>
]]></description>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/10457/assistant-professor-bio-informatics-at-health-and-family-welfare-department-medical-education-in-raipur</guid>
  <pubDate>Wed, 07 May 2014 00:08:38 -0500</pubDate>
  <link></link>
  <title><![CDATA[Assistant Professor (Bio-Informatics) at Health and Family Welfare Department (Medical Education) in Raipur]]></title>
  <description><![CDATA[
<p>Advertisement No.05/2014/ Exam/Dated 17/04/2014</p>

<p>No of vacancies: 01</p>

<p>Pay scale:Rs. 15600 – 39100 + 6600/-</p>

<p>Essential Academic Qualifications / Experience : Good academic record as defined by the concerned university with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed) at the Master's Degree level in a relevant subject from an Indian University, or an equivalent degree from an accredited foreign university.</p>

<p>Besides fulfilling the above qualifications, the candidate must have cleared the National Eligibility Test (NET) conducted by the UGC, CSIR or similar test accredited by the UGC like SLET/ SET.</p>

<p>Notwithstanding anything contained in sub-clauses (a) and (b) to this Clause, candidates, who are, or have been awarded a Ph.D. Degree in accordance with the University Grants Commission (Minimum Standards and Procedure for Award of Ph.D. Degree) Regulations, 2009, shall be exempted from the requirement of the minimum eligibility condition of NET/SLET/SET for recruitment and appointment of Assistant Professor or equivalent positions in Universities/Colleges/Institutions.</p>

<p>NET/SLET/SET shall also not be required for such Masters Programmes in disciplines for which NET/SLET/SET is not conducted.</p>

<p>Apply online: http://www.psc.cg.gov.in/htm/OA_ME2014.html</p>

<p>Last Date for Online Registration: 22/05/2014</p>

<p>For more details: http://www.psc.cg.gov.in/pdf/Advertisement/ADV_ME2014.pdf</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</guid>
	<pubDate>Sat, 10 May 2014 04:33:28 -0500</pubDate>
	<link>https://bioinformaticsonline.com/videolist/watch/10659/gps-dna-tracking-university-of-sheffield</link>
	<title><![CDATA[GPS DNA tracking - University of Sheffield]]></title>
	<description><![CDATA[<iframe width="" height="" src="https://www.youtube-nocookie.com/embed/Aap-s1kle4Q" frameborder="0" allowfullscreen></iframe>University of Sheffield geneticist and bioinformatics expert Dr Eran Elhaik demonstrates the power of his new DNA research, which allows people to discover their genetic homeland from 1000 years ago. Find out more about our biological research here http://www.sheffield.ac.uk/aps]]></description>
	
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/researchlabs/view/860/the-centre-for-bioinformatics-mcb-lab</guid>
  <pubDate>Sun, 14 Jul 2013 12:41:20 -0500</pubDate>
  <link></link>
  <title><![CDATA[The Centre for Bioinformatics (MCB) Lab]]></title>
  <description><![CDATA[
<p>The Centre for Bioinformatics (MCB) is a diverse collection of professors, postdoctoral fellows, and students, who share a common interest in Bioinformatics.</p>

<p>Research Area</p>

<p>We are interested in the development of the statistics and computational methods for the analysis of this data in breast cancer.<br />We have worked on probabilistic models for subcellular localization, protein-protein interactions, and problems related to chemical genomics.<br />We are interested in the development of bioinformatics/biostatistical methodology in the analysis of epigenetic/epigenomic data.<br />We are interested in integrative bioinformatics approaches to learn the gene, gene products, interactions, and regulatory mechanisms involved in mental retardation.</p>

<p>Link @ http://www.mcgill.ca/mcb/</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</guid>
	<pubDate>Sat, 10 May 2014 06:28:06 -0500</pubDate>
	<link>https://bioinformaticsonline.com/bookmarks/view/10741/managing-and-analyzing-next-generation-sequence-data</link>
	<title><![CDATA[Managing and Analyzing Next-Generation Sequence Data]]></title>
	<description><![CDATA[<p>Centralized Bioinformatics Core Facilities provide shared resources for the computational and IT requirements of the investigators in their department or institution. As such, they must be able to effectively react to new types of experimental technology. Recently faced with an unprecedented flood of data generated by the next generation of DNA sequencers, these groups found it necessary to respond quickly and efficiently to the informatics and infrastructure demands. Centralized Facilities newly facing this challenge need to anticipate time and design considerations of necessary components, including infrastructure upgrades, staffing, and tools for data analyses and management ...</p>
<p>More at http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</p><p>Address of the bookmark: <a href="http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369" rel="nofollow">http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1000369</a></p>]]></description>
	<dc:creator>Rahul Agarwal</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12593/visiting-scientist-computational-genomics-two-positions</guid>
  <pubDate>Mon, 07 Jul 2014 22:53:41 -0500</pubDate>
  <link></link>
  <title><![CDATA[Visiting Scientist - Computational Genomics (two positions)]]></title>
  <description><![CDATA[
<p>Scientific/Managerial &amp; International Recruitment</p>

<p>ICRISAT seeks applications from Indian nationals Visiting Scientist-Computational Genomics (2 positions), to be part of a team of Centre of Excellence in Genomics (CEG), (www.icrisat.org/ceg) to work on legume genomics projects.  The positions will be based at ICRISAT’s Headquarters in Patancheru, Hyderabad, India.</p>

<p>ICRISAT is a non-profit, non-political organization that conducts agricultural research for development in Asia and sub-Saharan Africa with a wide array of partners throughout the world. Covering 6.5 million square kilometers of land in 55 countries, the semi-arid tropics is home to over 2 billion people, with 650 million of these are the poorest of the poor. ICRISAT and its partners help empower those living in the semi-arid tropics, especially smallholder farmers, to overcome poverty, hunger, malnutrition and a degraded environment through more efficient and profitable agriculture. ICRISAT is headquartered in Greater Hyderabad, Andhra Pradesh, India and belongs to the Consortium of Centers supported by the Consultative Group on International Agricultural Research (CGIAR).</p>

<p>The Job: Responsibilities for these positions include:</p>

<p>    Analyzing and handling large-scale next generation sequencing DNA and RNA data<br />    Data mining and development of pipelines and troubleshooting<br />    Genome diversity analysis such as SNPs, Indels, Structural Variations, population structure<br />    Genome wide association study (GWAS) related analysis- LD analysis, hapmap and trait mapping<br />    Expression analysis based on RNA-Seq data, annotation, gene ontology and metabolic pathway analysis<br />    Epigenome analysis, small RNA identification<br />    Gene family analysis, sequence level protein analysis, orthology/paralogy and molecular modelling<br />    Compiling and analysis of results, writing reports and research papers</p>

<p>The Person:  Ph.D. or MSc/MTech/PGDCA with two years research experience in Biotechnology, Computational biology, Agricultural/ Plant Biotechnology, Genetics, Molecular Biology or related discipline. Good knowledge of programming/scripting in at least two of following languages: Perl, C, C++, R, Shell Scripting and Python is plus.</p>

<p>How to apply: Please apply latest by 20 July 2014.  The application should include the name of the position applied for, a letter of motivation, a full Curriculum Vita (CV), and the names and contact information of three references that are knowledgeable of the candidate’s professional qualifications and work experience. Technical details and more information about these positions can be obtained from R.K.VARSHNEY@CGIAR.ORG. All applications will be acknowledged, however only short listed candidates will be contacted.</p>

<p>Apply here https://recruit.zoho.com/ats/Portal.na?digest=T642sgLYWZOStExJ77cPrcM*sIMGZETWw4yPxngbmHA-</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11181/perl-one-liner-for-bioinformatician</guid>
	<pubDate>Fri, 30 May 2014 05:49:07 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11181/perl-one-liner-for-bioinformatician</link>
	<title><![CDATA[Perl one-liner for bioinformatician !!!]]></title>
	<description><![CDATA[<p>With the emergence of NGS technologies, and sequencing data most of the bioinformaticians mung and wrangle around massive amounts of genomics text. There are several "standardized" file formats (FASTQ, SAM, VCF, etc.) and some tools for manipulating them (fastx toolkit, samtools, vcftools, etc.), there are still times where knowing a little bit of Perl onliner is extremely helpful.</p><p>Perl one-liners are small and awesome Perl programs that fit in a single line of code and they do one thing really well. These things include changing line spacing, numbering lines, doing calculations, converting and substituting text, deleting and printing certain lines, parsing logs, editing files in-place, doing statistics, carrying out system administration tasks, updating a bunch of files at once, and many more. Perl one-liners will make you the shell warrior. Anything that took you minutes to solve, will now take you seconds!<br /><br />perl -pe '$\="\n"'&nbsp; &nbsp;<br />#double space a file<br /><br />perl -pe '$_ .= "\n" unless /^$/' <br />#double space a file except blank lines<br /><br />perl -pe '$_.="\n"x7' <br />#7 space in a line.<br /><br />perl -ne 'print unless /^$/' <br />#remove all blank lines<br /><br />perl -lne 'print if length($_) &lt; 20' <br />#print all lines with length less than 20.<br /><br />perl -00 -pe '' <br />#If there are multiple spaces, delete all leaving one(make the file a single spaced file).<br /><br />perl -00 -pe '$_.="\n"x4' <br />#Expand single blank lines into 4 consecutive blank lines<br /><br />perl -pe '$_ = "$. $_"'<br />#Number all lines in a file<br /><br />perl -pe '$_ = ++$a." $_" if /./' <br />#Number only non-empty lines in a file<br /><br />perl -ne 'print ++$a." $_" if /./' <br />#Number and print only non-empty lines in a file<br /><br />perl -pe '$_ = ++$a." $_" if /regex/' <br />#Number only lines that match a pattern<br /><br />perl -ne 'print ++$a." $_" if /regex/' <br />#Number and print only lines that match a pattern<br /><br />perl -ne 'printf "%-5d %s", $., $_ if /regex/' <br />#Left align lines with 5 white spaces if matches a pattern (perl -ne 'printf "%-5d %s", $., $_' : for all the lines)<br /><br />perl -le 'print scalar(grep{/./}&lt;&gt;)' <br />#prints the total number of non-empty lines in a file<br /><br />perl -lne '$a++ if /regex/; END {print $a+0}' <br />#print the total number of lines that matches the pattern<br /><br />perl -alne 'print scalar @F' <br />#print the total number fields(words) in each line.<br /><br />perl -alne '$t += @F; END { print $t}' <br />#Find total number of words in the file<br /><br />perl -alne 'map { /regex/ &amp;&amp; $t++ } @F; END { print $t }' <br />#find total number of fields that match the pattern<br /><br />perl -lne '/regex/ &amp;&amp; $t++; END { print $t }' <br />#Find total number of lines that match a pattern<br /><br />perl -le '$n = 20; $m = 35; ($m,$n) = ($n,$m%$n) while $n; print $m' <br />#will calculate the GCD of two numbers.<br /><br />perl -le '$a = $n = 20; $b = $m = 35; ($m,$n) = ($n,$m%$n) while $n; print $a*$b/$m' <br />#will calculate lcd of 20 and 35.<br /><br />perl -le '$n=10; $min=5; $max=15; $, = " "; print map { int(rand($max-$min))+$min } 1..$n' <br />#Generates 10 random numbers between 5 and 15.<br /><br />perl -le 'print map { ("a".."z",&rdquo;0&rdquo;..&rdquo;9&rdquo;)[rand 36] } 1..8'<br />#Generates a 8 character password from a to z and number 0 &ndash; 9.<br /><br />perl -le 'print map { ("a",&rdquo;t&rdquo;,&rdquo;g&rdquo;,&rdquo;c&rdquo;)[rand 4] } 1..20'<br />#Generates a 20 nucleotide long random residue.<br /><br />perl -le 'print "a"x50'<br />#generate a string of &lsquo;x&rsquo; 50 character long<br /><br />perl -le 'print join ", ", map { ord } split //, "hello world"'<br />#Will print the ascii value of the string hello world.<br /><br />perl -le '@ascii = (99, 111, 100, 105, 110, 103); print pack("C*", @ascii)'<br />#converts ascii values into character strings.<br /><br />perl -le '@odd = grep {$_ % 2 == 1} 1..100; print "@odd"'<br />#Generates an array of odd numbers.<br /><br />perl -le '@even = grep {$_ % 2 == 0} 1..100; print "@even"'<br />#Generate an array of even numbers<br /><br />perl -lpe 'y/A-Za-z/N-ZA-Mn-za-m/' file <br />#Convert the entire file into 13 characters offset(ROT13)<br /><br />perl -nle 'print uc' <br />#Convert all text to uppercase:<br /><br />perl -nle 'print lc' <br />#Convert text to lowercase:<br /><br />perl -nle 'print ucfirst lc' <br />#Convert only first letter of first word to uppercas<br /><br />perl -ple 'y/A-Za-z/a-zA-Z/' <br />#Convert upper case to lower case and vice versa<br /><br />perl -ple 's/(\w+)/\u$1/g' <br />#Camel Casing<br /><br />perl -pe 's|\n|\r\n|' <br />#Convert unix new lines into DOS new lines:<br /><br />perl -pe 's|\r\n|\n|' <br />#Convert DOS newlines into unix new line<br /><br />perl -pe 's|\n|\r|' <br />#Convert unix newlines into MAC newlines:<br /><br />perl -pe '/regexp/ &amp;&amp; s/foo/bar/' <br />#Substitute a foo with a bar in a line with a regexp.</p><p>Reference/Sources:</p><p>http://genomics-array.blogspot.in/2010/11/some-unixperl-oneliners-for.html</p><p><a href="http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html">http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html</a></p><p><a href="http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/">http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/</a></p><p><a href="http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html">http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html</a></p><p><a href="http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/">http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/</a></p>]]></description>
	<dc:creator>Abhimanyu Singh</dc:creator>
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  <guid isPermaLink='true'>https://bioinformaticsonline.com/opportunity/view/12896/inspire-faculty-scheme-a-component-of-%E2%80%9Cassured-opportunity-for-research-career-aorc%E2%80%9D-under-inspire</guid>
  <pubDate>Sat, 19 Jul 2014 14:59:30 -0500</pubDate>
  <link></link>
  <title><![CDATA[INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.]]></title>
  <description><![CDATA[
<p>Ministry of Science and Technology, Department of Science and Technology</p>

<p>7th ADVERTISEMENT – 2014 (2)</p>

<p>INSPIRE Faculty Scheme: a component of “Assured Opportunity for Research Career (AORC)” under INSPIRE.</p>

<p>The Department of Science and Technology, Government of India, has launched the “Innovation in Science Pursuit for Inspired Research (INSPIRE)” [http://www.inspire-dst.gov.in] program in 2008.</p>

<p>The program aims to attract talent for study of science and careers with research. INSPIRE includes many components. The importance of Assured Career Opportunity in R&amp;D sector has been recognized.</p>

<p>INSPIRE Faculty Scheme opens up an “Assured Opportunity for Research Career (AORC)” for young researchers in the age group of 27-32 years. It offers a contractual research awards to young achievers and opportunity for independent research in the near term and emerge as a future leader in the long term.</p>

<p>Eligibility</p>

<p>Essential Indian citizens and people of Indian origin including NRI/PIO status with PhD (in science, mathematics, engineering, pharmacy, medicine, and agriculture related subjects) from any recognized university in the world,</p>

<p>Those who have submitted their PhD Theses and are awaiting award of the degree are also<br />eligible. However, the award will be conveyed only after confirmation of the awarding the<br />PhD degree.</p>

<p>The upper age limit as on 1st July 2014 should be 32 years for considering support for a<br />period of 5 years. However, for SC and ST candidates, upper age limit will be 35 years.</p>

<p>Publication(s) in highly reputed Journals demonstrating research potential of the candidate.</p>

<p>Desirable</p>

<p>Candidates who are within top 1% at the School Leaving Examination, IIT-JEE rank, 1st Rank Holder either in graduation or post-graduation level university examination (which are used presently for identifying INSPIRE Scholars at under-graduate level and INSPIRE Fellows for doctoral degree)</p>

<p>More at http://www.inspire-dst.gov.in/faculty_scheme.html</p>
]]></description>
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	<guid isPermaLink="true">https://bioinformaticsonline.com/pages/view/11457/commercial-and-public-next-gen-seq-ngs-software</guid>
	<pubDate>Tue, 03 Jun 2014 20:45:11 -0500</pubDate>
	<link>https://bioinformaticsonline.com/pages/view/11457/commercial-and-public-next-gen-seq-ngs-software</link>
	<title><![CDATA[Commercial and public next-gen-seq (NGS) software]]></title>
	<description><![CDATA[<p><strong>Integrated solutions</strong><br /> <a href="http://www.clcbio.com/index.php?id=1240" target="_blank">CLCbio Genomics Workbench</a> - <em>de novo</em> 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.<br /><a href="http://g2.trac.bx.psu.edu/" target="_blank">Galaxy</a> - Galaxy = interactive and reproducible genomics. A job webportal.<br /> <a href="http://www.genomatix.de/products/index.html" target="_blank">Genomatix</a> - Integrated Solutions for Next Generation Sequencing data analysis.<br /> <a href="http://www.jmp.com/software/genomics/" target="_blank">JMP Genomics</a> - Next gen visualization and statistics tool from SAS. They are <a href="http://www.marketwatch.com/news/story/JMPR-Genomics-NCGR-Partnership-Foster/story.aspx?guid=%7B7AC9DE36-B6AA-4EDE-9CD5-633B29FE6154%7D" target="_blank">working with NCGR</a> to refine this tool and produce others.<br /> <a href="http://softgenetics.com/NextGENe.html" target="_blank">NextGENe</a> - <em>de novo</em> 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.<br /><a href="http://www.partek.com" target="_blank" title="Partek Incorporated">Partek</a>&nbsp;<span>- Commercial software for NGS, microarray, and qPCR data analysis. Streamlined analysis workflows for: ChIP-Seq, RNA-Seq, DNA-Seq, DNA Methylation, Gene Expression, Exon, miRNA Expression, Copy Number, Allele-Specific Copy Number, LOH, Association, Trio Analysis, and Tiling. Supports all commercial sequencing and microarray technologies.&nbsp;</span><br /> <a href="http://www.dnastar.com/products/SMGA.php" target="_blank">SeqMan Genome Analyser</a> - 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.<br /><a href="http://1001genomes.org/downloads/shore.html" target="_blank">SHORE</a> - 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.<br /> <a href="http://www.realtimegenomics.com/" target="_blank">SlimSearch</a> - Fledgling commercial product.<br />Synamatix has SXOligoSearch (<a href="http://synasite.mgrc.com.my:8080/sxog/NewSXOligoSearch.php" target="_blank">http://synasite.mgrc.com.my:8080/sxo...ligoSearch.php</a>)<br />The SWIFT suit is a software collection for fast index-based sequence comparison. It contains the following programs: SWIFT &mdash; fast local alignment search, guaranteeing to find epsilon-matches between two sequences; SWIFT BALSAM &mdash; a very fast program to find semiglobal non-gapped alignments based on k-mer seeds. <a href="http://bibiserv.techfak.uni-bielefeld.de/swift/" target="_blank">http://bibiserv.techfak.uni-bielefeld.de/swift/</a><br /><a href="http://http//bioinf.comav.upv.es/svn/biolib/biolib/src/" target="_blank">biolib</a>.is library and a set of script targeted to NGS. There are modules to: clean sequences (sanger, 454, ilumina), parse caf, ace and bowtie map files, clean and filter contigs, look for snps and indels., filter snps, do statistics for: reads, contigs and snps.</p><p><br /> <strong>Align/Assemble to a reference</strong><br /> <a href="https://secure.genome.ucla.edu/index.php/BFAST" target="_blank">BFAST</a> - Blat-like Fast Accurate Search Tool. Written by Nils Homer, Stanley F. Nelson and Barry Merriman at UCLA.<br /><a href="http://bowtie-bio.sourceforge.net/" target="_blank">Bowtie</a> - 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. <a href="http://seqanswers.com/forums/showthread.php?t=706" target="_blank">Link to discussion thread here</a>. Written by Ben Langmead and Cole Trapnell. Linux, Windows, and Mac OS X.<br /> <a href="http://maq.sourceforge.net/" target="_blank">BWA</a> - 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.<br /> <a href="http://bioinfo.cgrb.oregonstate.edu/docs/solexa/" target="_blank">ELAND</a> - 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.<br /> <a href="http://www.ebi.ac.uk/%7Eguy/exonerate/" target="_blank">Exonerate</a> - 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.<br /> <a href="http://1001genomes.org/downloads/genomemapper.html" target="_blank">GenomeMapper</a> - 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.<br /> <a href="http://www.gene.com/share/gmap/" target="_blank">GMAP</a> - GMAP (Genomic Mapping and Alignment Program) for mRNA and EST Sequences. Developed by Thomas Wu and Colin Watanabe at Genentec. C/Perl for Unix.<br /> <a href="http://dna.cs.byu.edu/gnumap/" target="_blank">gnumap</a> - 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.<br /> <a href="http://sourceforge.net/projects/maq/" target="_blank">MAQ</a> - 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<br /> <a href="http://bioinformatics.bc.edu/marthlab/Mosaik" target="_blank">MOSAIK</a> - 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 Str&ouml;mberg at Boston College. Win/Linux/MacOSX<br /> <a href="http://mrfast.sourceforge.net/" target="_blank">MrFAST and MrsFAST</a> - mrFAST &amp; 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.<br /> <a href="http://mummer.sourceforge.net/" target="_blank">MUMmer</a> - 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.<br /> <a href="http://www.novocraft.com/index.html" target="_blank">Novocraft</a> - 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.<br /> <a href="http://pass.cribi.unipd.it/cgi-bin/pass.pl" target="_blank">PASS</a> - 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.<br /> <a href="http://rulai.cshl.edu/rmap/" target="_blank">RMAP</a> - 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.<br /> <a href="http://biogibbs.stanford.edu/%7Ejiangh/SeqMap/" target="_blank">SeqMap</a> - 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.<br /> <a href="http://compbio.cs.toronto.edu/shrimp/" target="_blank">SHRiMP</a> - 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.<br /> <a href="http://www.bcgsc.ca/platform/bioinfo/software/slider" target="_blank"><span style="text-decoration: underline;">Slider</span></a>- 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 <a href="http://seqanswers.com/forums/showthread.php?t=740" target="_blank">here</a>.<br /> <a href="http://soap.genomics.org.cn/" target="_blank">SOAP</a> - 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.<br /> <a href="http://www.sanger.ac.uk/Software/analysis/SSAHA/" target="_blank">SSAHA</a> - 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.<br /> <a href="http://socs.biology.gatech.edu/" target="_blank">SOCS</a> - 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.<br /> <a href="http://bibiserv.techfak.uni-bielefeld.de/swift/welcome.html" target="_blank">SWIFT</a> - The SWIFT suit is a software collection for fast index-based sequence comparison. It contains: SWIFT &mdash; fast local alignment search, guaranteeing to find epsilon-matches between two sequences. SWIFT BALSAM &mdash; 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)<br /> <a href="http://synasite.mgrc.com.my:8080/sxog/NewSXOligoSearch.php" target="_blank">SXOligoSearch</a> - SXOligoSearch is a commercial platform offered by the Malaysian based <a href="http://www.synamatix.com/" target="_blank">Synamatix</a>. Will align Illumina reads against a range of Refseq RNA or NCBI genome builds for a number of organisms. Web Portal. OS independent.<br /> <a href="http://www.vmatch.de/" target="_blank">Vmatch</a> - 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.<br /> <a href="http://www.bioinformaticssolutions.com/products/zoom/index.php" target="_blank">Zoom</a> - 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.<br />NCGR uses GMAP (<a href="http://www.gene.com/share/gmap/" target="_blank">http://www.gene.com/share/gmap/</a>) to alignment Solexa reads. GMAP is free, though.<br />Exonerate (<a href="http://www.ebi.ac.uk/%7Eguy/exonerate/" target="_blank">http://www.ebi.ac.uk/~guy/exonerate/</a>)<br /> MUMmer (<a href="http://mummer.sourceforge.net/" target="_blank">http://mummer.sourceforge.net/</a>)<br /> The mapping short reads called gnumap (<a href="http://dna.cs.byu.edu/gnumap/" target="_blank">http://dna.cs.byu.edu/gnumap/</a>) made to increase the accuracy with duplicate matches. Open source, creates viewable output (with Affy's Integrated Genome Browser), and produces results very similar to novocraft's.<br /><a href="http://socs.biology.gatech.edu/" target="_blank">SOCS</a> (short oligonucleotides in color space)<br />BFAST <a href="https://secure.genome.ucla.edu/index.php/BFAST" target="_blank">https://secure.genome.ucla.edu/index.php/BFAST</a></p><p><br /> <strong><em>De novo</em> Align/Assemble</strong><br /> <a href="http://www.bcgsc.ca/platform/bioinfo/software/abyss" target="_blank">ABySS</a> - 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. <br /> <a href="http://www.broad.mit.edu/science/programs/genome-biology/computational-rd/computational-research-and-development" target="_blank">ALLPATHS</a> - 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.<br /> <a href="http://www.genomic.ch/edena.php" target="_blank">Edena</a> - 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. Fran&ccedil;ois, L. Farinelli, M. Osteras, and J. Schrenzel. Linux/Win.<br /> <a href="http://euler-assembler.ucsd.edu/portal/" target="_blank">EULER-SR</a> - Short read <em>de novo</em> assembly. By Mark J. Chaisson and Pavel A. Pevzner from UCSD (published in Genome Research). Uses a de Bruijn graph approach.<br /> <a href="http://chevreux.org/projects_mira.html" target="_blank">MIRA2</a> - 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.<br /> <a href="http://www.seqan.de/projects/consensus.html" target="_blank">SEQAN</a> - A Consistency-based Consensus Algorithm for De Novo and Reference-guided Sequence Assembly of Short Reads. By Tobias Rausch and others. C++, Linux/Win.<br /> <a href="http://sharcgs.molgen.mpg.de/" target="_blank">SHARCGS</a> - 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.<br /> <a href="http://www.bcgsc.ca/platform/bioinfo/software/ssake" target="_blank">SSAKE</a> - 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 Ren&eacute; Warren, Granger Sutton, Steven Jones and Robert Holt from the Canada's Michael Smith Genome Sciences Centre. Perl/Linux.<br /> <a href="http://soap.genomics.org.cn/" target="_blank">SOAPdenovo</a> - Part of the SOAP suite. See above. <br /> <a href="https://sourceforge.net/projects/vcake" target="_blank">VCAKE</a> - De novo assembly of short reads with robust error correction. An improvement on early versions of SSAKE.<br /> <a href="http://www.ebi.ac.uk/%7Ezerbino/velvet/" target="_blank">Velvet</a> - 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).<br />SOAP (<a href="http://soap.genomics.org.cn" target="_blank">http://soap.genomics.org.cn</a>) by Ruiqiang Li, as has been pointed by ECO.<br />Euler-SR (Euler-Short Reads Assembly, <a href="http://euler-assembler.ucsd.edu/portal/" target="_blank">http://euler-assembler.ucsd.edu/portal/</a>) by Mark J. Chaisson and Pavel A. Pevzner from UCSD. (published in Genome Research)<br />RMAP (A program for mapping Solexa reads, <a href="http://rulai.cshl.edu/rmap/" target="_blank">http://rulai.cshl.edu/rmap/</a>) by Andrew D. Smith and Zhenyu Xuan at CSHL. (published in BMC Bioinformatics)<br />Short read aligner called Bowtie (<a href="http://bowtie-bio.sourceforge.net/" target="_blank">http://bowtie-bio.sourceforge.net/</a>) designed for fast mapping of Illumina reads<br /> <br /> <strong>SNP/Indel Discovery</strong><br /> <a href="http://www.sanger.ac.uk/Software/analysis/ssahaSNP/" target="_blank">ssahaSNP</a> - 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<br /> <a href="http://bioinformatics.bc.edu/marthlab/PbShort" target="_blank">PolyBayesShort</a> - 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.<br /> <a href="http://bioinformatics.bc.edu/marthlab/PyroBayes" target="_blank">PyroBayes</a> - 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.<br />Maq is also able to find SNPs with its own alignment. It has a graphical viewer, but again for its own alignment format.<br />SSAHA has been optimized for short-reads, too. But yes, SSAHASNP appears in your "SNP/INDEL discovery" category.<br /> <br /> <strong>Genome Annotation/Genome Browser/Alignment Viewer/Assembly Database</strong><br /> <a href="http://bioinformatics.bc.edu/marthlab/EagleView" target="_blank">EagleView</a> - 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.<br /> <a href="http://www.sanger.ac.uk/Software/analysis/lookseq/" target="_blank">LookSeq</a> - 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.<br /> <a href="http://evolution.sysu.edu.cn/mapview/" target="_blank">MapView</a> - MapView: visualization of short reads alignment on desktop computer. From the Evolutionary Genomics Lab at Sun-Yat Sen University, China. Linux.<br /> <a href="http://www.bcgsc.ca/platform/bioinfo/software/sam" target="_blank">SAM</a> - 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. <br /> <a href="http://staden.sourceforge.net/" target="_blank">STADEN</a> - Includes GAP4. GAP5 once completed will handle next-gen sequencing data. A partially implemented test version is available <a href="https://sourceforge.net/project/show...kage_id=256957" target="_blank">here</a><br /> <a href="http://www.bcgsc.ca/platform/bioinfo/software/xmatchview" target="_blank">XMatchView</a> - 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.<br /> <br /> <strong>Counting e.g. CHiP-Seq, Bis-Seq, CNV-Seq</strong><br /> <a href="http://epigenomics.mcdb.ucla.edu/BS-Seq/download.html" target="_blank">BS-Seq</a> - The source code and data for the "Shotgun Bisulphite Sequencing of the Arabidopsis Genome Reveals DNA Methylation Patterning" Nature paper by <a href="http://www.ncbi.nlm.nih.gov/sites/entrez?holding=&amp;db=pubmed&amp;cmd=search&amp;term=Shotgun%20Bisulphite%20Sequencing" target="_blank">Cokus et al.</a> (Steve Jacobsen's lab at UCLA). POSIX.<br /> <a href="http://woldlab.caltech.edu/chipseq/" target="_blank">CHiPSeq</a> - Program used by Johnson et al. (2007) in their Science publication<br /> <a href="http://tiger.dbs.nus.edu.sg/cnv-seq/" target="_blank">CNV-Seq</a> - 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.<br /> <a href="http://www.bcgsc.ca/platform/bioinfo/software/findpeaks" target="_blank">FindPeaks</a> - 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 <a href="http://vancouvershortr.sourceforge.net/" target="_blank">Vancouver Short Read Analysis Package</a><br /> <a href="http://liulab.dfci.harvard.edu/MACS/" target="_blank">MACS</a> - 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. <br /> <a href="http://www.gersteinlab.org/proj/PeakSeq/" target="_blank">PeakSeq</a> - 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.<br /> <a href="http://mendel.stanford.edu/sidowlab/downloads/quest/" target="_blank">QuEST</a> - Quantitative Enrichment of Sequence Tags. Sidow and Myers Labs at Stanford. From the 2008 publication <a href="http://www.ncbi.nlm.nih.gov/pubmed/18711362" target="_blank">Genome-wide analysis of transcription factor binding sites based on ChIP-Seq data</a>. (C++)<br /> <a href="http://dir.nhlbi.nih.gov/papers/lmi/epigenomes/sissrs/" target="_blank">SISSRs</a> - Site Identification from Short Sequence Reads. BED file input. Raja Jothi @ NIH. Perl.<br />SeqMap (<a href="http://biogibbs.stanford.edu/%7Ejiangh/SeqMap/" target="_blank">http://biogibbs.stanford.edu/~jiangh/SeqMap/</a>) - work like ELand, can do 3 or more bp mismatches and also insdel<br />ChIPSeq analysis is:&nbsp; <a href="http://dir.nhlbi.nih.gov/papers/lmi/epigenomes/sissrs/" target="_blank">http://dir.nhlbi.nih.gov/papers/lmi/epigenomes/sissrs/</a></p><p>See also <a href="http://seqanswers.com/forums/showthread.php?t=742" target="_blank">this thread</a> for ChIP-Seq, until I get time to update this list.<br /> <br /> <strong>Alternate Base Calling</strong><br /> <a href="http://svitsrv25.epfl.ch/R-doc/library/Rolexa/html/00Index.html" target="_blank">Rolexa</a> - R-based framework for base calling of Solexa data. Project <a href="http://www.biomedcentral.com/1471-2105/9/431" target="_blank">publication</a><br /> <a href="http://hannonlab.cshl.edu/Alta-Cyclic/main.html" target="_blank">Alta-cyclic</a> - "a novel Illumina Genome-Analyzer (Solexa) base caller"<br /> <br /> <strong>Transcriptomics</strong><br /> <a href="http://woldlab.caltech.edu/rnaseq/" target="_blank">ERANGE</a> - Mapping and Quantifying Mammalian Transcriptomes by RNA-Seq. Supports Bowtie, BLAT and ELAND. From the Wold lab.<br /> <a href="http://www.genoscope.cns.fr/externe/gmorse/" target="_blank">G-Mo.R-Se</a> - 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.<br /> <a href="http://evolution.sysu.edu.cn/english/software/mapnext.htm" target="_blank">MapNext</a> - 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.<br /> <a href="http://www.fml.tuebingen.mpg.de/raetsch/suppl/qpalma" target="_blank">QPalma</a> - Optimal Spliced Alignments of Short Sequence Reads. Authors are Fabio De Bona, Stephan Ossowski, Korbinian Schneeberger, and Gunnar R&auml;tsch. A paper is <a href="http://www.fml.tuebingen.mpg.de/raetsch/suppl/qpalma/qpalma-final.pdf" target="_blank">available</a>.<br /> <a href="http://biogibbs.stanford.edu/%7Ejiangh/rsat/" target="_blank">RSAT</a> - RSAT: RNA-Seq Analysis Tools. RNASAT is developed and maintained by Hui Jiang at Stanford University.<br /> <a href="http://tophat.cbcb.umd.edu/" target="_blank">TopHat</a> - 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<br />NGS-Trex: Next Generation Sequencing Transcriptome profile explorer http://www.biomedcentral.com/1471-2105/14/S7/S10</p><p>Reference</p><p>Illumina has a software list: <a href="http://www.illumina.com/pagesnrn.ilmn?ID=245" target="_blank">http://www.illumina.com/pagesnrn.ilmn?ID=245</a>.</p><p>Some softwares in his blog (<a href="http://www.fejes.ca/labels/DNA.html" target="_blank">http://www.fejes.ca/labels/DNA.html</a>)</p><p><a href="http://seqanswers.com/wiki/Software" target="_blank">http://seqanswers.com/wiki/Software</a></p>]]></description>
	<dc:creator>Surabhi Chaudhary</dc:creator>
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