BOL: Related items

Bioinformatics tools for genome assembly !

BioStar — Mon, 24 Jul 2023 07:04:26 -0500

There are numerous genome assembly tools available, each with its strengths and weaknesses. Here is a list of some widely used genome assembly tools as of my last update in September 2021:

SPAdes: An assembler specifically designed for single-cell and multi-cell bacterial genomes, as well as small eukaryotic genomes.
ABySS: A parallelized assembler for large genomes that uses de Bruijn graphs.
Velvet: Another de Bruijn graph-based assembler optimized for short-read sequencing data.
SOAPdenovo: A de Bruijn graph-based assembler designed for short reads, widely used for assembling large and complex genomes.
MaSuRCA: A hybrid assembler that combines data from multiple sequencing technologies, such as Illumina and PacBio.
Canu: A long-read assembler optimized for PacBio and Oxford Nanopore sequencing data.
Flye: A long-read assembler suitable for bacterial and small eukaryotic genomes.
SMARTdenovo: An assembler designed for long reads, particularly suited for PacBio data.
SPAdes Long Read (SPAdesLR): An extension of SPAdes for long-read data, such as those from PacBio or Nanopore.
Minia: An assembler optimized for low memory consumption, suitable for small and medium-sized genomes.
Unicycler: A hybrid assembler that combines short and long reads for circular bacterial genome assembly.
wtdbg2: A de Bruijn graph assembler for long reads, efficient for very large genomes.
Shasta: A long-read assembler that uses the Overlap-Layout-Consensus approach, suitable for PacBio and Nanopore data.
Sparc: An assembler designed to handle noisy long reads from Nanopore sequencing.
CANA: An assembler for metagenomic data, particularly for complex and diverse microbial communities.
Ra Assembler: A metagenome assembler for long reads, designed for highly complex metagenomic samples.

Please note that the field of bioinformatics is constantly evolving, and new assembly tools may have emerged since my last update. Additionally, the performance of these tools can vary depending on the characteristics of the sequencing data and the genome being assembled. When selecting an assembly tool, consider the specific requirements of your project, the available data types, and the computational resources at your disposal. Always refer to the respective tool's documentation and publications for the most up-to-date information and recommendations.

Scalpel

Shruti Paniwala — Wed, 20 Aug 2014 02:07:58 -0500

A team from Cold Spring Harbor Laboratory has released an algorithm, called Scalpel, for finding insertions and deletions in next generation sequencing data sets. Scalpel, which is open source and available for download on SourceForge, outperformed the popular tools GATK HaplotypeCaller and SOAPindel in test runs on both simulated and real whole human exomes.

Like other indel callers, Scalpel works by performing de novo assembly of regions of interest, so that misalignment to the reference genome cannot obscure the presence of an insertion or deletion. Scalpel's innovation is to repeatedly check its assembly before comparing to the reference genome, to account for simple sequence repeats that are a regular source of error in indel calling. When Scalpel assembles an exon, it collects reads that map to that exon (including partial matches), splits them into k-mers, and creates a de Bruijn graph to span the exon; however, if it detects repeats in the map, it iteratively increases the size of the k-mers by one base until the repeats are eliminated. This ensures that the final assembly of the exon is highly accurate while minimizing compute time.

The Cold Spring Harbor team's validation of Scalpel, published over the weekend in Nature Methods, compares Scalpel's performance on a live whole exome against HaplotypeCaller and SOAPindel. The donor is an individual with serious neurological disorders, which may be linked to a high incidence of indels. One thousand indels from this individual's exome, called by one or more of the informatics pipelines, were selected for focused resequencing. This resequencing revealed a 77% true positive rate for Scalpel calls, dramatically better than the rates for either of the competing tools; Scalpel performed especially well with indels longer than five base pairs, a traditional weak point for indel callers.

Finally, the authors demonstrate Scalpel's use on a large set of genetic data from nearly 600 families who donated samples to the Simons Simplex Collection, a project of the Simons Foundation Autism Research Initiative. Scalpel found a very high enrichment for indels in children affected by autism, compared with their unaffected siblings, a pattern that persisted even after excluding common variants.

BioKit: a set of tools dedicated to bioinformatics, data visualisation

Neel — Tue, 18 Jun 2024 02:04:39 -0500

BioKit is a set of tools dedicated to bioinformatics, data visualisation (biokit.viz), access to online biological data (e.g. UniProt, NCBI thanks to bioservices). It also contains more advanced tools related to data analysis (e.g., biokit.stats). Since R is quite common in bioinformatics, we also provide a convenient module to run R inside your Python scripts or shell (:mod:biokit.rtools module).

Address of the bookmark: https://biokit.readthedocs.io/en/latest/index.html

BioCodes/BioScripts

Jit — Tue, 22 Apr 2014 20:53:33 -0500

Over the years most bioinformatics people amass a collection of small utility scripts which make their lives easier. Too often they are kept either in private repositories or as part of a public collection to which noone else can contribute. Biocode is a curated repository of general-use utility scripts.

Algorithms scripts @ https://github.com/jschendel/bioinformatics-algorithms-coursera

Address of the bookmark: https://github.com/jorvis/biocode

Perl Special Vars Quick Reference

Abhimanyu Singh — Tue, 07 Feb 2017 05:08:47 -0600

`$_`	The default or implicit variable.
`@_`	Subroutine parameters.
`$a` `$b`	sort comparison routine variables.
`@ARGV`	The command-line args.
Regular Expressions
`$`	Regexp parenthetical capture holders.
`$&`	Last successful match (degrades performance).
`${^MATCH}`	Similar to `$&` without performance penalty. Requires /p modifier.
$`	Prematch for last successful match string (degrades performance).
`${^PREMATCH}`	Similar to $` without performance penalty. Requires `/p` modifier.
`$'`	Postmatch for last successful match string (degrades performance).
`${^POSTMATCH}`	Similar to `$'` without performance penalty. Requires `/p` modifier.
`$+`	Last paren match.
`$^N`	Last closed paren match (last submatch).
`@+`	Offsets of ends of successful submatches in scope.
`@-`	Offsets of starts of successful submatches in scope.
`%+`	Like `@+`, but for named submatches.
`%-`	Like `@-`, but for named submatches.
`$^R`	Last regexp (?{code}) result.
`${^RE_DEBUG_FLAGS}`	Current value of regexp debugging flags. See `use re 'debug';`
`${^RE_TRIE_MAXBUF}`	Control memory allocations for RE optimizations for large alternations.
Encoding
`${^ENCODING}`	The object reference to the Encode object, used to convert the source code to Unicode.
`${^OPEN}`	Internal use: \0 separated Input / Output layer information.
`${^UNICODE}`	Read-only Unicode settings.
`${^UTF8CACHE}`	State of the internal UTF-8 offset caching code.
`${^UTF8LOCALE}`	Indicates whether UTF8 locale was detected at startup.
IO and Separators
`$.`	Current line number (or record number) of most recent filehandle.
`$/`	Input record separator.
`$\|`	Output autoflush. 1=autoflush, 0=default. Applies to currently selected handle.
`$,`	Output field separator (lists)
`$\`	Output record separator.
`$"`	Output list separator. (interpolated lists)
`$;`	Subscript separator. (Use a real multidimensional array instead.)
Formats
`$%`	Page number for currently selected output channel.
`$=`	Current page length.
`$-`	Number of lines left on page.
`$~`	Format name.
`$^`	Name of top-of-page format.
`$:`	Format line break characters
`$^L`	Form feed (default "\f").
`$^A`	Format Accumulator
Status Reporting
`$?`	Child error. Status code of most recent system call or pipe.
`$!`	Operating System Error. (What just went 'bang'?)
`%!`	Error number hash
`$^E`	Extended Operating System Error (Extra error explanation).
`$@`	Eval error.
`${^CHILD_ERROR_NATIVE}`	Native status returned by the last pipe close, backtick (`` ) command, successful call to wait() or waitpid(), or from the system() operator.
ID's and Process Information
`$$`	Process ID
`$<`	Real user id of process.
`$>`	Effective user id of process.
`$(`	Real group id of process.
`$)`	Effective group id of process.
`$0`	Program name.
`$^O`	Operating System name.
Perl Status Info
`$]`	Old: Version and patch number of perl interpreter. Deprecated.
`$^C`	Current value of flag associated with -c switch.
`$^D`	Current value of debugging flags
`$^F`	Maximum system file descriptor.
`$^I`	Value of the -i (inplace edit) switch.
`$^M`	Emergency Memory pool.
`$^P`	Internal variable for debugging support.
`$^R`	Last regexp (?{code}) result.
`$^S`	Exceptions being caught. (eval)
`$^T`	Base time of program start.
`$^V`	Perl version.
`$^W`	Status of -w switch
`${^WARNING_BITS}`	Current set of warning checks enabled by `use warnings;`
`$^X`	Perl executable name.
`${^GLOBAL_PHASE}`	Current phase of the Perl interpreter.
`$^H`	Internal use only: Hook into Lexical Scoping.
`%^H`	Internaluse only: Useful to implement scoped pragmas.
`${^TAINT}`	Taint mode read-only flag.
`${^WIN32_SLOPPY_STAT}`	If true on Windows `stat()` won't try to open the file.
Command Line Args
`ARGV`	Filehandle iterates over files from command line (see also `<>`).
`$ARGV`	Name of current file when reading <>
`@ARGV`	List of command line args.
`ARGVOUT`	Output filehandle for -i switch
Miscellaneous
`@F`	Autosplit (-a mode) recipient.
`@INC`	List of library paths.
`%INC`	Keys are filenames, values are paths to modules included via `use, require,` or `do`.
`%ENV`	Hash containing current environment variables
`%SIG`	Signal handlers.
`$[`	Array and substr first element (Deprecated!).

See perlvar for detailed descriptions of each of these (and a few more) special variables.

RA at ALAGAPPA UNIVERSITY

Sun, 04 May 2014 23:33:15 -0500

DEPARTMENT OF BIOTECHNOLOGY
(UGC SAP and DST-FIST & PURSE Sponsored Department)
ALAGAPPA UNIVERSITY
(A State University Accredited by NAAC with „A‟ Grade)
Karaikudi - 630 004, India

WALK IN INTERVIEW

A walk-in Interview for the following position tenable at the Bioinformatics Infrastructure Facility (BIF), Department of Biotechnology, Alagappa University will be held at the Department of Biotechnology, Alagappa University, Karaikudi 630 003 on 15.05.2014 (Thursday) at 01:00 PM. This national facility is funded by the Department of Biotechnology, Ministry of Science and Technology, Government of India, New Delhi. The main objectives of the Centre involve teaching and research activities in bioinformatics/biotechnology.

RA (One Post):

Salary : Rs. 11000 p.m. plus admissible HRA

Qualification: M.Sc., in Bioinformatics/Biotechnology/Biophysics/Biochemistry/ Life Sciences

Interested candidates are encouraged to send their Curriculum Vitae by email to “sk_pandian@rediffmail.com” in advance. On the day of interview, the candidates must produce original certificates in proof of their educational qualification and experience and a recommendation letter from the Head of the Department/Institution where last studied/worked. Candidates who have already passed the required Degree alone are eligible to appear for interview. No TA&DA will be given for attending the interview.

Advertisement: http://www.alagappabiotech.org/Walk%20in%20interview.pdf

kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome

Jit — Fri, 08 Dec 2017 16:48:40 -0600

Sept. 20, 2017 Version 3.1 released. Major upgrade. Version 3.1 fixes the problems with SNP annotation that arose when NCBI discontinued use of GI numbers. Please read carefully the Preface (page 3) and the File of annotated genomes section (pages 9-10) in the version 3.1 User Guide. Thanks to Tom Slezak for revsing the get_genbank_file3 script and to Tod Stuber (USDA) for testing version 3.1 even though he doesn't need the annotation feature. All users are encouraged to upgrade to version 3.1.

Address of the bookmark: https://sourceforge.net/projects/ksnp/files/

Associate Professor - Bio-Informatics at University of Allahabad in Allahabad

Wed, 07 May 2014 00:26:53 -0500

No of vacancies: 01

Pay scale: Pay Band of Rs. 37400-67000 with AGP of Rs. 9000.

i. Educational Qualification: Good academic record with a Ph.D. Degree in the concerned/allied/relevant disciplines.

ii. A Master's Degree with at least 55% marks (or an equivalent grade in a point scale wherever grading system is followed).

iii. A minimum of eight years of experience of teaching and/or research in an academic/research position equivalent to that of Assistant Professor in a University, College or Accredited Research Institution/industry excluding the period of Ph.D. research with evidence of published work and a minimum of 5 publications as books and/or research/policy papers.

iv. Contribution to educational innovation, design of new curricula and courses, and technology - mediated teaching learning process with evidence of having guided doctoral candidates and research students.

v. A minimum score as stipulated in the Academic Performance Indicator (API) based Performance Based Appraisal System (PBAS), set out in UGC Regulation.

Download application form from website: http://www.allduniv.ac.in/

Send your application to the Registrar, University of Allahabad, Allahabad-211002 (U.P.) on or before 30th April 2014

For more details: http://www.allduniv.ac.in/images/adv/backlog/advt-details.pdf OR http://www.allduniv.ac.in/images/news/extension-notice.pdf

Last Apply Date: 30 May 2014

assemblytics: delta file to analyze alignments of an assembly to another assembly or a reference genome

Jit — Thu, 14 Jun 2018 07:31:00 -0500

Download and install MUMmer Align your assembly to a reference genome using nucmer (from MUMmer package) $ nucmer -maxmatch -l 100 -c 500 REFERENCE.fa ASSEMBLY.fa -prefix OUT Consult the MUMmer manual if you encounter problems Optional: Gzip the delta file to speed up upload (usually 2-4X faster) $ gzip OUT.delta Then use the OUT.delta.gz file for upload. Upload the .delta or delta.gz file (view example) to Assemblytics Important: Use only contigs rather than scaffolds from the assembly. This will prevent false positives when the number of Ns in the scaffolded sequence does not match perfectly to the distance in the reference. The unique sequence length required represents an anchor for determining if a sequence is unique enough to safely call variants from, which is an alternative to the mapping quality filter for read alignment. http://assemblytics.com/

Address of the bookmark: http://assemblytics.com/

DNA Replication Process [3D Animation]

Sat, 10 May 2014 04:41:22 -0500

See an organised list of all the animations: http://doctorprodigious.wordpress.com/hd-animations/