BOL: Related items

HECIL: A Hybrid Error Correction Algorithm for Long Reads with Iterative Learning

Abhimanyu Singh — Tue, 01 Jan 2019 12:01:00 -0600

HECIL—Hybrid Error Correction with Iterative Learning—a hybrid error correction framework that determines a correction policy for erroneous long reads, based on optimal combinations of decision weights obtained from short read alignments.

HECIL’s core algorithm by introducing an iterative learning paradigm that enhances the correction policy at each iteration by incorporating knowledge gathered from previous iterations via data-driven confidence metrics assigned to prior corrections.

Address of the bookmark: https://github.com/NDBL/HECIL

BEAR: Better Emulation for Artificial Reads

BioStar — Sat, 06 Jul 2024 04:27:53 -0500

Created by Stephen Johnson, Brett Trost, Dr. Jeffrey R. Long, Dr. Anthony Kusalik University of Saskatchewan, Department of Computer Science

BEAR is intended to be an easy-to-use collection of scripts for generating simulated WGS metagenomic reads with read lengths, quality scores, error profiles, and species abundances derived from real user-supplied WGS data.

Address of the bookmark: https://github.com/sej917/BEAR

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.

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/

NCBI PSI-BLAST Tutorial

Fri, 23 Aug 2013 02:25:02 -0500

http:--www.biotechnology.jhu.edu- Tutorial for PSI-BLAST, an extension of BLAST that uses matrix algebra. BLAST is a cornerstone bioinformatics tool at NCBI. BLAST is the Basic Local Alignment Search tool and will protein and DNA sequences that are related to a sequence that the user provides.

Andi

Jit — Fri, 13 May 2016 05:16:35 -0500

This is the andi program for estimating the evolutionary distance between closely related genomes. These distances can be used to rapidly infer phylogenies for big sets of genomes. Because andi does not compute full alignments, it is so efficient that it scales even up to thousands of bacterial genomes.

This readme covers all necessary instructions for the impatient to get andi up and running. For extensive instructions please consult the manual.

More at https://github.com/evolbioinf/andi/

Address of the bookmark: http://bioinformatics.oxfordjournals.org/content/early/2015/01/13/bioinformatics.btu815.full

Samtools Primer !!

Jit — Thu, 23 Jun 2016 07:18:17 -0500

SAMtools: Primer / Tutorial by Ethan Cerami, Ph.D.

keywords: samtools, next-gen, next-generation, sequencing, bowtie, sam, bam, primer, tutorial, how-to, introduction
Revisions

    1.0: May 30, 2013: First public release on biobits.org.
    1.1: July 24, 2013: Updated with Disqus Comments / Feedback section.
    1.2: December 19, 2014: Multiple updates, including:
        Updated to use samtools 1.1 and bcftools 1.2.
        Updated usage for bcftools.

About

SAMtools is a popular open-source tool used in next-generation sequence analysis. This primer provides an introduction to SAMtools, and is geared towards those new to next-generation sequence analysis. The primer is also designed to be self-contained and hands-on, meaning that you only need to install SAMtools, and no other tools, and sample data sets are provided. Terms in bold are also explained in the glossary at the end of the document.

Address of the bookmark: http://biobits.org/samtools_primer.html

FSA: Fast Statistical Alignment

Jit — Mon, 06 Feb 2017 04:26:01 -0600

FSA is a probabilistic multiple sequence alignment algorithm which uses a "distance-based" approach to aligning homologous protein, RNA or DNA sequences. Much as distance-based phylogenetic reconstruction methods like Neighbor-Joining build a phylogeny using only pairwise divergence estimates, FSA builds a multiple alignment using only pairwise estimations of homology. This is made possible by the sequence annealing technique for constructing a multiple alignment from pairwise comparisons, developed by Ariel Schwartz in "Posterior Decoding Methods for Optimization and Control of Multiple Alignments."

FSA brings the high accuracies previously available only for small-scale analyses of proteins or RNAs to large-scale problems such as aligning thousands of sequences or megabase-long sequences. FSA introduces several novel methods for constructing better alignments:

FSA uses machine-learning techniques to estimate gap and substitution parameters on the fly for each set of input sequences. This "query-specific learning" alignment method makes FSA very robust: it can produce superior alignments of sets of homologous sequences which are subject to very different evolutionary constraints.
FSA is capable of aligning hundreds or even thousands of sequences using a randomized inference algorithm to reduce the computational cost of multiple alignment. This randomized inference can be over ten times faster than a direct approach with little loss of accuracy.
FSA can quickly align very long sequences using the "anchor annealing" technique for resolving anchors and projecting them with transitive anchoring. It then stitches together the alignment between the anchors using the methods described above.
The included GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned (see the picture and movie at the top of the page).

You can see more information on the FAQ.

Address of the bookmark: http://fsa.sourceforge.net/

FOGSAA: Fast Optimal Global Sequence Alignment Algorithm

Jit — Fri, 08 Dec 2017 14:41:08 -0600

Sequence alignment algorithms are widely used to infer similarirty and the point of differences between pair of sequences. FOGSAA is a fast Global alignment algorithm. It is basically a branch and bound approach which starts branch expansion in a greedy way taking the symbols from the given pair of sequences (protein or nucleotide) and results in an optimal alignment faster than conventional dymanic programming techniques. It is also better than the heuristic methods with respect to alignment quality.

Address of the bookmark: http://www.isical.ac.in/~bioinfo_miu/FOGSAA.htm

medaka: Sequence correction provided by ONT Research

BioStar — Mon, 18 May 2020 16:28:00 -0500

medaka is a tool to create a consensus sequence from nanopore sequencing data. This task is performed using neural networks applied from a pileup of individual sequencing reads against a draft assembly. It outperforms graph-based methods operating on basecalled data, and can be competitive with state-of-the-art signal-based methods, whilst being much faster.

Address of the bookmark: https://github.com/nanoporetech/medaka