BOL: Related items

Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads

BioStar — Tue, 04 Feb 2020 23:23:16 -0600

Rcorrector has an accuracy higher than or comparable to existing methods, including the only other method (SEECER) designed for RNA-seq reads, and is more time and memory efficient. With a 5 GB memory footprint for 100 million reads, it can be run on virtually any desktop or server. The software is available free of charge under the GNU General Public License from https://github.com/mourisl/Rcorrector/.

Usage: perl run_rcorrector.pl [OPTIONS]
OPTIONS:
	Required
	-s seq_files: comma separated files for single-end data sets
	-1 seq_files_left: comma separated files for the first mate in the paried-end data sets
	-2 seq_files_right: comma separated files for the second mate in the paired-end data sets
	-i seq_files_interleaved: comma sperated files for interleaved paired-end data sets
	Optional
	-k INT: kmer_length (<=32, default: 23)
	-od STRING: output_file_directory (default: ./)
	-t INT: number of threads to use (default: 1)
	-trim : allow trimming (default: false)
	-maxcorK INT: the maximum number of correction within k-bp window (default: 4)
	-wk FLOAT: the proportion of kmers that are used to estimate weak kmer count threshold, lower for more divergent genome (default: 0.95)
	-ek INT: expected number of kmers; does not affect the correctness of program but affects the memory usage (default: 100000000)
	-stdout: output the corrected reads to stdout (default: not used)
	-verbose: output some correction information to stdout (default: not used)
	-stage INT: start from which stage (default: 0)
		0-start from begining(storing kmers in bloom filter) ;
		1-start from count kmers showed up in bloom filter;
		2-start from dumping kmer counts into a jf_dump file;
		3-start from error correction.

Address of the bookmark: https://github.com/mourisl/Rcorrector/

SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis

BioStar — Mon, 17 Aug 2020 05:21:09 -0500

SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, …).
The bioinformatics treatment is based on Vsearch [Rognes 2016] which showed to be both accurate and fast [Wescott 2015].The statistical analysis is based on DESeq2 R package [Anders and Huber 2010] which robustly identifies the differential abundant features as suggested in [McMurdie and Holmes 2014] and [Jonsson2016]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014].
SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available here and a poster here.

More at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4

Address of the bookmark: https://github.com/aghozlane/shaman

SqueezeMeta: a fully automated metagenomics pipeline, from reads to bins

BioStar — Sat, 06 Jul 2024 04:29:16 -0500

SqueezeMeta is a full automatic pipeline for metagenomics/metatranscriptomics, covering all steps of the analysis. SqueezeMeta includes multi-metagenome support allowing the co-assembly of related metagenomes and the retrieval of individual genomes via binning procedures. Thus, SqueezeMeta features several unique characteristics:

Co-assembly procedure with read mapping for estimation of the abundances of genes in each metagenome
Co-assembly of a large number of metagenomes via merging of individual metagenomes
Includes binning and bin checking, for retrieving individual genomes
The results are stored in a database, where they can be easily exported and shared, and can be inspected anywhere using a web interface.
Internal checks for the assembly and binning steps inform about the consistency of contigs and bins, allowing to spot potential chimeras.
Metatranscriptomic support via mapping of cDNA reads against reference metagenomes

Address of the bookmark: https://github.com/jtamames/SqueezeMeta

LoRMA: a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines

Jit — Wed, 15 Jun 2016 17:18:36 -0500

LoRMA is a tool for correcting sequencing errors in long reads such those produced by Pacific Biosciences sequencing machines.

Publication:

L. Salmela, R. Walve, E. Rivals, and E. Ukkonen: Accurate selfcorrection of errors in long reads using de Bruijn graphs. Accepted to RECOMB-Seq 2016.

Download:

Address of the bookmark: https://www.cs.helsinki.fi/u/lmsalmel/LoRMA/

ART: Set of Simulation Tools

Jit — Thu, 03 Nov 2016 08:28:25 -0500

ART is a set of simulation tools to generate synthetic next-generation sequencing reads. ART simulates sequencing reads by mimicking real sequencing process with empirical error models or quality profiles summarized from large recalibrated sequencing data. ART can also simulate reads using user own read error model or quality profiles. ART supports simulation of single-end, paired-end/mate-pair reads of three major commercial next-generation sequencing platforms: Illumina's Solexa, Roche's 454 and Applied Biosystems' SOLiD. ART can be used to test or benchmark a variety of method or tools for next-generation sequencing data analysis, including read alignment, de novo assembly, SNP and structure variation discovery. ART was used as a primary tool for the simulation study of the 1000 Genomes Project . ART is implemented in C++ with optimized algorithms and is highly efficient in read simulation. ART outputs reads in the FASTQ format, and alignments in the ALN format. ART can also generate alignments in the SAM alignment or UCSC BED file format. ART can be used together with genome variants simulators (e.g. VarSim) for evaluating variant calling tools or methods.

Address of the bookmark: http://www.niehs.nih.gov/research/resources/software/biostatistics/art/

QuorUM: An Error Corrector for Illumina Reads

Jit — Wed, 08 Nov 2017 11:40:41 -0600

Illumina Sequencing data can provide high coverage of a genome by relatively short (most often 100 bp to 150 bp) reads at a low cost. Even with low (advertised 1%) error rate, 100 × coverage Illumina data on average has an error in some read at every base in the genome. These errors make handling the data more complicated because they result in a large number of low-count erroneous k-mers in the reads. However, there is enough information in the reads to correct most of the sequencing errors, thus making subsequent use of the data (e.g. for mapping or assembly) easier. Here we use the term “error correction” to denote the reduction in errors due to both changes in individual bases and trimming of unusable sequence. We developed an error correction software called QuorUM. QuorUM is mainly aimed at error correcting Illumina reads for subsequent assembly. It is designed around the novel idea of minimizing the number of distinct erroneous k-mers in the output reads and preserving the most true k-mers, and we introduce a composite statistic π that measures how successful we are at achieving this dual goal. We evaluate the performance of QuorUM by correcting actual Illumina reads from genomes for which a reference assembly is available.

QuorUM is distributed as an independent software package and as a module of the MaSuRCA assembly software. Both are available under the GPL open source license at http://www.genome.umd.edu.

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130821

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/

List of popular bioinformatics software/tools

Jitendra Narayan — Tue, 16 Jul 2013 14:30:30 -0500

In current genome era, our day to day work is to handle the huge geneome sequences, expression data, several other datasets. This link provide a comprehensive list of commonly used sofware/tools.

Address of the bookmark: http://samtools.sourceforge.net/swlist.shtml