<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/36884?offset=290 https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data Fri, 04 Oct 2024 02:45:06 -0500 https://bioinformaticsonline.com/pages/view/44672/libraries-or-management-tools-for-high-throughput-sequencing-data <![CDATA[Libraries or management tools for high throughput sequencing data]]>
  • GATB Library. The Genome Analysis Toolbox with de-Bruijn graph. A large part of tools developed by the GenScale team are based on this library.
    These methods enable the analysis of data sets of any size on multi-core desktop computers, including very huge amount of reads data coming from any kind of organisms such as bacteria, plants, animals and even complex samples (e.g. metagenomes). Among them are (the full is available here: https://gatb.inria.fr/software/):
  • LRez: C++ Library and toolkit for the barcode-based management and indexation of linked-read datasets.

    • Variant calling and/or genotyping

    • DiscoSNP++ and discoSnpRAD: Reference-free small variant discovery (SNPs and indels)
    • MindTheGap: Detection and assembly of large insertion variants
    • TakeABreak: reference-free inversion discovery tool
    • SVJedi: Structural Variant genotyper with long read data
    • SVJedi-graph: Structural Variant genotyper with long read data using a variation graph

    Sequence assembly

    • MinYS: reference-guided genome assembly in metagenomics data
    • MTG-link: local assembly tool for linked-read data
    • Minia: De novo short read assembler
    • de-novo pipeline: de-novo assembly pipeline (error correction / contigs / scaffolding) for genomes and meta-genomes
    • Mapsembler2: Targeted assembly (not maintained)

    Managing k-mers & indexation

    • findere: simple strategy for speeding up queries and for reducing false positive calls from any Approximate Membership Query data structure.
      • fimpera extends findere adding the abundance information.
    • kmtricks: modular tool suite for counting kmers, and constructing Bloom filters or kmer matrices, for large collections of sequencing data.
    • kmindex is a tool for indexing and querying sequencing samples. It is built on top of kmtricks.
    • back to sequences: Find sequences (reads, unitigs, genes) related to a set of kmers in large datasets, in a matter of seconds.
    • Backpack Quotient Filter: k-mer indexing data structure with abundance
    • short read connector: Detect similar reads from potentially large read set
    • DSK: Count K-mer in sequences

    Pangenome graph manipulation

    • Pancat: Pangenome Comparison and Analysis Toolkit
    • GFAGraphs: a Python library to handle pangenome graph files in GFA format.

    Comparative metagenomics with k-mers

    Species and bacterial strains identification

    • ORI: software using long nanopore reads to identify bacteria present in a sample at the strain level
    • StrainFLAIR: STRAIN-level proFiLing using vArIation gRaph

    General-purpose sequencing data manipulation

    • GASSST: long read mapper
    • Leon: short read compressor (now included in GATB-core)
    • Bloocoo: short read corrector
    • BCALM: Construct compacted de Bruijn graphs (unitigs)

     Protein Structure

    • A_Purva: Contact Map Overlap solver
    • MD-Jeep: Distance Geometry solver
    • CSA: Comparative Structural Alignment

    Workflow

    • SLICEE: parallel execution of bioinformatics workflows

    Comparative Genomics

    • CASSIS: detection of rearrangement breakpoints
    • PLAST: intensive bank-to-bank sequence comparison
    • DRJBreakpointFinder: detection and precise localization of excision sites in proviral segments
    ]]>     LEGE     https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics Thu, 26 Jul 2018 04:58:45 -0500 https://bioinformaticsonline.com/pages/view/37411/my-commonly-used-commands-in-bioinformatics <![CDATA[My commonly used commands in Bioinformatics]]> FYI, I've found it useful to use MUMmer to extract the specific changes that Racon makes, so I can evaluate them individually:

    minimap -t 24 assembly.fasta long_reads.fastq.gz | racon -t 24 long_reads.fastq.gz - assembly.fasta racon_assembly.fasta
nucmer -p nucmer assembly.fasta racon_assembly.fasta
show-snps -C -T -r nucmer.delta

    This reports Racon's changes in a table. You can exclude indels with the -I option in show-snps. 

    This process (Racon -> MUMmer -> SNP table) solves the problem I originally raised in this issue. So as far as I'm concerned, you can close this issue (or keep it open if you still want to implement some kind of variant table).

    ]]>     Rahul Nayak     https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores Sun, 04 Nov 2018 16:44:30 -0600 https://bioinformaticsonline.com/bookmarks/view/38063/referee-genome-assembly-quality-scores <![CDATA[Referee: Genome assembly quality scores]]> Modern genome sequencing technologies provide a succint measure of quality at each position in every read, however all of this information is lost in the assembly process. Referee summarizes the quality information from the reads that map to a site in an assembled genome to calculate a quality score for each position in the genome assembly.

    We accomplish this by first calculating genotype likelihoods for every site. For a given site in a diploid genome, there are 10 possible genotypes (AA, AC, AG, AT, CC, CG, CT, GG, GT, TT). Referee takes as input the genotype likelihoods calculated for all 10 genotypes given the called reference base at each position.

    Referee is a program to calculate a quality score for every position in a genome assembly. This allows for easy filtering of low quality sites for any downstream analysis.

    https://github.com/gwct/referee

    Address of the bookmark: https://gwct.github.io/referee/#

    ]]>     Jit     https://bioinformaticsonline.com/bookmarks/view/40544/ngs-bits-short-read-sequencing-tools Thu, 16 Jan 2020 23:14:00 -0600 https://bioinformaticsonline.com/bookmarks/view/40544/ngs-bits-short-read-sequencing-tools <![CDATA[ngs-bits - Short-read sequencing tools]]> Binaries of ngs-bits are available via Bioconda. Alternatively, ngs-bits can be built from sources:

    Address of the bookmark: https://github.com/imgag/ngs-bits

    ]]>     Neel     https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping Wed, 29 Jan 2020 06:29:55 -0600 https://bioinformaticsonline.com/bookmarks/view/40754/understanding-your-reads-and-mapping <![CDATA[Understanding your reads and mapping !]]> One of the best tutorial for beginners ...

    https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

    Address of the bookmark: https://bioinformatics-core-shared-training.github.io/cruk-summer-school-2017/Day1/Session4-seqIntro.html

    ]]>     Neel     https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads Sun, 22 Dec 2019 03:48:28 -0600 https://bioinformaticsonline.com/bookmarks/view/40460/sviper-swipe-your-structural-variants-called-on-long-ontpacbio-reads-with-short-exact-illumina-reads <![CDATA[SViper: Swipe your Structural Variants called on long (ONT/PacBio) reads with short exact (Illumina) reads.]]> Call sviper

    ~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants

    This will output a polished_variants.vcf file, that contains all the refined variants.

    Sometimes it is helpful to look at the polished sequence, e.g. with the IGV browser. In that case you want SViper to output the polished and aligned sequences in a bam file via the option --output-polished-bam:

    ~$ ./sviper -s short-reads.bam -l long-reads.bam -r ref.fa -c variants.vcf -o polished_variants --output-polished-bam

    Address of the bookmark: https://github.com/smehringer/SViper

    ]]>     Neel     https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2 Mon, 10 Apr 2017 04:45:40 -0500 https://bioinformaticsonline.com/bookmarks/view/32131/wgs-celera-assembler-version-83rc2 <![CDATA[WGS Celera Assembler version 8.3rc2]]> These are release notes for Celera Assembler version 8.3rc2, which was released on May 24, 2015.

    This distribution package provides a stable, tested, documented version of the software.  The distribution is usable on most Unix-like platforms, and some platforms have pre-compiled binary distributions ready for installation.

    The source code package includes full source code (revision 4627), Makefiles, and scripts.  A subset of the kmer package (http://kmer.sourceforge.net/, version r1994), used by some modules of Celera Assembler, is included.  This distribution includes [http://samtools.sourceforge.net/ SAMtools], [http://www.cbcb.umd.edu/software/jellyfish/ Jellyfish 2.0], [https://github.com/pbjd/pbutgcns PBUTGCNS], [https://github.com/PacificBiosciences/pbdagcon PBDAGCON], [https://github.com/PacificBiosciences/BLASR BLASR], and parts of the [https://github.com/PacificBiosciences/FALCON/tree/v0.1.3 Falcon assembler].

    Full documentation can be found online at http://wgs-assembler.sourceforge.net/.

    Interesting scripts within it

    urbe@urbo214b[bin] ls                                                        []
    -rwxrwxr-x 1 urbe urbe  11K Apr 10 11:41 addCNSToStore
    -rwxrwxr-x 1 urbe urbe 575K Apr 10 11:41 addReadsToUnitigs
    -rwxrwxr-x 1 urbe urbe 128K Apr 10 11:41 analyzeBest
    -rwxrwxr-x 1 urbe urbe 257K Apr 10 11:41 analyzePosMap
    -rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 analyzeScaffolds
    -rwxrwxr-x 1 urbe urbe 224K Apr 10 11:41 asmOutputFasta
    -rwxrwxr-x 1 urbe urbe 448K Apr 10 11:41 asmOutputStatistics
    -rwxrwxr-x 1 urbe urbe 2,4K Apr 10 11:41 asmToAGP.pl
    -rwxrwxr-x 1 urbe urbe 7,6M Apr 10 11:41 blasr
    -rwxrwxr-x 1 urbe urbe 1,6M Apr 10 11:41 bogart
    -rwxrwxr-x 1 urbe urbe 183K Apr 10 11:41 bogus
    -rwxrwxr-x 1 urbe urbe 272K Apr 10 11:41 bogusness
    -rwxrwxr-x 1 urbe urbe 247K Apr 10 11:41 buildPosMap
    -rwxrwxr-x 1 urbe urbe 213K Apr 10 11:41 buildRefContigs
    -rwxrwxr-x 1 urbe urbe 990K Apr 10 11:41 buildUnitigs
    -rwxrwxr-x 1 urbe urbe  18K Apr 10 11:41 ca2ace.pl
    -rwxrwxr-x 1 urbe urbe  12K Apr 10 11:41 caqc_help.ini
    -rwxrwxr-x 1 urbe urbe  61K Apr 10 11:41 caqc.pl
    -rwxrwxr-x 1 urbe urbe  23K Apr 10 11:41 cat-corrects
    -rwxrwxr-x 1 urbe urbe  24K Apr 10 11:41 cat-erates
    -rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 cgw
    -rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 cgwDump
    -rwxrwxr-x 1 urbe urbe 204K Apr 10 11:41 chimChe
    -rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 chimera
    -rwxrwxr-x 1 urbe urbe 220K Apr 10 11:41 classifyMates
    -rwxrwxr-x 1 urbe urbe 201K Apr 10 11:41 classifyMatesApply
    -rwxrwxr-x 1 urbe urbe 215K Apr 10 11:41 classifyMatesPairwise
    -rwxrwxr-x 1 urbe urbe 366K Apr 10 11:41 computeCoverageStat
    -rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 convert-fasta-to-v2.pl
    -rwxrwxr-x 1 urbe urbe  48K Apr 10 11:41 convertOverlap
    -rwxrwxr-x 1 urbe urbe 119K Apr 10 11:41 convertSamToCA
    -rwxrwxr-x 1 urbe urbe  20K Apr 10 11:41 convertToPBCNS
    -rwxrwxr-x 1 urbe urbe 197K Apr 10 11:41 correct-frags
    -rwxrwxr-x 1 urbe urbe 259K Apr 10 11:41 correct-olaps
    -rwxrwxr-x 1 urbe urbe 520K Apr 10 11:41 correctPacBio
    -rwxrwxr-x 1 urbe urbe 540K Apr 10 11:41 ctgcns
    -rwxrwxr-x 1 urbe urbe 162K Apr 10 11:40 deduplicate
    -rwxrwxr-x 1 urbe urbe  37K Apr 10 11:41 demotePosMap
    -rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 dumpCloneMiddles
    -rwxrwxr-x 1 urbe urbe 124K Apr 10 11:41 dumpPBRLayoutStore
    -rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 dumpSingletons
    -rwxrwxr-x 1 urbe urbe 171K Apr 10 11:41 erate-estimate
    -rwxrwxr-x 1 urbe urbe 221K Apr 10 11:40 estimate-mer-threshold
    -rwxrwxr-x 1 urbe urbe 1,5M Apr 10 11:41 extendClearRanges
    -rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 extendClearRangesPartition
    -rwxrwxr-x 1 urbe urbe 205K Apr 10 11:40 extractmessages
    -rwxrwxr-x 1 urbe urbe 7,2M Apr 10 11:41 falcon_sense
    -rwxrwxr-x 1 urbe urbe 9,8K Apr 10 11:41 fastaToCA
    -rwxrwxr-x 1 urbe urbe 124K Apr 10 11:40 fastqAnalyze
    -rwxrwxr-x 1 urbe urbe 137K Apr 10 11:40 fastqSample
    -rwxrwxr-x 1 urbe urbe  62K Apr 10 11:40 fastqSimulate
    -rwxrwxr-x 1 urbe urbe 121K Apr 10 11:40 fastqSimulate-sort
    -rwxrwxr-x 1 urbe urbe 246K Apr 10 11:40 fastqToCA
    -rwxrwxr-x 1 urbe urbe 140K Apr 10 11:41 filterOverlap
    -rwxrwxr-x 1 urbe urbe 341K Apr 10 11:40 finalTrim
    -rwxrwxr-x 1 urbe urbe 228K Apr 10 11:41 fixUnitigs
    -rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 fragmentDepth
    -rwxrwxr-x 1 urbe urbe  29K Apr 10 11:41 fragsInVars
    -rwxrwxr-x 1 urbe urbe 545K Apr 10 11:41 frgs2clones
    -rwxrwxr-x 1 urbe urbe 398K Apr 10 11:40 gatekeeper
    -rwxrwxr-x 1 urbe urbe 139K Apr 10 11:40 gatekeeperbench
    -rwxrwxr-x 1 urbe urbe 167K Apr 10 11:40 gkpStoreCreate
    -rwxrwxr-x 1 urbe urbe 147K Apr 10 11:40 gkpStoreDumpFASTQ
    -rwxrwxr-x 1 urbe urbe 184K Apr 10 11:41 greedyFragmentTiling
    -rwxrwxr-x 1 urbe urbe 1,6K Apr 10 11:41 greedy_layout_to_IUM
    -rwxrwxr-x 1 urbe urbe 142K Apr 10 11:40 initialTrim
    -rwxrwxr-x 1 urbe urbe 967K Apr 10 11:41 jellyfish
    -rwxrwxr-x 1 urbe urbe 219K Apr 10 11:41 markRepeatUnique
    -rwxrwxr-x 1 urbe urbe 273K Apr 10 11:40 markUniqueUnique
    -rwxrwxr-x 1 urbe urbe 114K Apr 10 11:40 mercy
    -rwxrwxr-x 1 urbe urbe 3,8K Apr 10 11:41 mergeqc.pl
    -rwxrwxr-x 1 urbe urbe 422K Apr 10 11:40 merTrim
    -rwxrwxr-x 1 urbe urbe 125K Apr 10 11:40 merTrimApply
    -rwxrwxr-x 1 urbe urbe 376K Apr 10 11:40 meryl
    -rwxrwxr-x 1 urbe urbe 176K Apr 10 11:41 metagenomics_ovl_analyses
    -rwxrwxr-x 1 urbe urbe 297K Apr 10 11:41 olap-from-seeds
    -rwxrwxr-x 1 urbe urbe 275K Apr 10 11:41 outputLayout
    -rwxrwxr-x 1 urbe urbe 229K Apr 10 11:41 overlapInCore
    -rwxrwxr-x 1 urbe urbe 144K Apr 10 11:40 overlap_partition
    -rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStats
    -rwxrwxr-x 1 urbe urbe 179K Apr 10 11:41 overlapStore
    -rwxrwxr-x 1 urbe urbe 153K Apr 10 11:41 overlapStoreBucketizer
    -rwxrwxr-x 1 urbe urbe 175K Apr 10 11:41 overlapStoreBuild
    -rwxrwxr-x 1 urbe urbe  33K Apr 10 11:41 overlapStoreIndexer
    -rwxrwxr-x 1 urbe urbe  48K Apr 10 11:41 overlapStoreSorter
    -rwxrwxr-x 1 urbe urbe 604K Apr 10 11:40 overmerry
    lrwxrwxrwx 1 urbe urbe    4 Apr 10 11:41 pacBioToCA -> PBcR
    -rwxrwxr-x 1 urbe urbe 131K Apr 10 11:41 PBcR
    -rwxrwxr-x 1 urbe urbe 2,9M Apr 10 11:41 pbdagcon
    -rwxrwxr-x 1 urbe urbe 1,9M Apr 10 11:41 pbutgcns
    -rwxrwxr-x 1 urbe urbe 201K Apr 10 11:40 remove_fragment
    -rwxrwxr-x 1 urbe urbe 153K Apr 10 11:40 removeMateOverlap
    -rwxrwxr-x 1 urbe urbe 2,5K Apr 10 11:41 replaceUIDwithName-fastq
    -rwxrwxr-x 1 urbe urbe 1,2K Apr 10 11:41 replaceUIDwithName-posmap
    -rwxrwxr-x 1 urbe urbe 1,3M Apr 10 11:41 resolveSurrogates
    -rwxrwxr-x 1 urbe urbe 139K Apr 10 11:41 rewriteCache
    -rwxrwxr-x 1 urbe urbe 232K Apr 10 11:41 runCA
    -rwxrwxr-x 1 urbe urbe  88K Apr 10 11:41 runCA-dedupe
    -rwxrwxr-x 1 urbe urbe  14K Apr 10 11:41 runCA-overlapStoreBuild
    -rwxrwxr-x 1 urbe urbe 3,6K Apr 10 11:41 run_greedy.csh
    -rwxrwxr-x 1 urbe urbe 297K Apr 10 11:40 sffToCA
    -rwxrwxr-x 1 urbe urbe  13K Apr 10 11:40 show-corrects
    -rwxrwxr-x 1 urbe urbe 557K Apr 10 11:41 splitUnitigs
    -rwxrwxr-x 1 urbe urbe 1,4M Apr 10 11:41 terminator
    drwxrwxr-x 2 urbe urbe 4,0K Apr 10 11:41 TIGR
    -rwxrwxr-x 1 urbe urbe 526K Apr 10 11:41 tigStore
    -rwxrwxr-x 1 urbe urbe  35K Apr 10 11:41 tracearchiveToCA
    -rwxrwxr-x 1 urbe urbe  35K Apr 10 11:41 tracedb-to-frg.pl
    -rwxrwxr-x 1 urbe urbe  44K Apr 10 11:41 trimFastqByQVWindow
    -rwxrwxr-x 1 urbe urbe  18K Apr 10 11:40 uidclient
    -rwxrwxr-x 1 urbe urbe 589K Apr 10 11:41 unitigger
    -rwxrwxr-x 1 urbe urbe  42K Apr 10 11:40 upgrade-v8-to-v9
    -rwxrwxr-x 1 urbe urbe  42K Apr 10 11:40 upgrade-v9-to-v10
    -rwxrwxr-x 1 urbe urbe  854 Apr 10 11:41 utg2fasta
    -rwxrwxr-x 1 urbe urbe 731K Apr 10 11:41 utgcns
    -rwxrwxr-x 1 urbe urbe 561K Apr 10 11:41 utgcnsfix


    Address of the bookmark: http://wgs-assembler.sourceforge.net/wiki/index.php/Main_Page

    ]]>     Jit     https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator Wed, 24 May 2017 08:41:41 -0500 https://bioinformaticsonline.com/bookmarks/view/33011/grinder-biogrinder-a-versatile-omics-shotgun-and-amplicon-sequencing-read-simulator <![CDATA[Grinder / Biogrinder - A versatile omics shotgun and amplicon sequencing read simulator]]> Grinder is a versatile program to create random shotgun and amplicon sequence libraries based on DNA, RNA or proteic reference sequences provided in a FASTA file.

    Grinder can produce genomic, metagenomic, transcriptomic, metatranscriptomic, proteomic, metaproteomic shotgun and amplicon datasets from current sequencing technologies such as Sanger, 454, Illumina. These simulated datasets can be used to test the accuracy of bioinformatic tools under specific hypothesis, e.g. with or without sequencing errors, or with low or high community diversity. Grinder may also be used to help decide between alternative sequencing methods for a sequence-based project, e.g. should the library be paired-end or not, how many reads should be sequenced.

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

    ]]>     Jit     https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics Thu, 29 Apr 2021 23:39:14 -0500 https://bioinformaticsonline.com/bookmarks/view/43048/coverm-read-coverage-calculator-for-metagenomics <![CDATA[CoverM: Read coverage calculator for metagenomics]]> CoverM aims to be a configurable, easy to use and fast DNA read coverage and relative abundance calculator focused on metagenomics applications.

    CoverM calculates coverage of genomes/MAGs coverm genome (help) or individual contigs coverm contig (help). Calculating coverage by read mapping, its input can either be BAM files sorted by reference, or raw reads and reference genomes in various formats.

    Address of the bookmark: https://github.com/wwood/CoverM

    ]]>     Neel     https://bioinformaticsonline.com/bookmarks/view/38172/bamview-a-free-interactive-display-of-read-alignments-in-bam-data-files Fri, 09 Nov 2018 13:43:22 -0600 https://bioinformaticsonline.com/bookmarks/view/38172/bamview-a-free-interactive-display-of-read-alignments-in-bam-data-files <![CDATA[BamView: a free interactive display of read alignments in BAM data files]]> To run the application on UNIX from the downloaded jar file run the UNIX:

    java -mx512m -jar BamView.jar

    and extra command line options are given when '-h' is used:

    java -jar BamView.jar -h

    BAM files can be specified on the command line with the '-a' option:

    java -mx512m -jar BamView.jar -a pathToFile/sorted.bam

    If a BAM filename is not given on the command line BamView will prompt for a file to be entered. The BAM index file should have the same name as the BAM file but with a '.bai' suffix. Multiple BAM files can be loaded and overlaid in the viewer. To make this easier BamView will read in files that contain a list of filenames.

     

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

    ]]>     Neel