<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/32905?offset=230 https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler Fri, 04 May 2018 19:18:41 -0500 https://bioinformaticsonline.com/bookmarks/view/36478/the-marvel-assembler <![CDATA[The MARVEL assembler]]> MARVEL consists of a set of tools that facilitate the overlapping, patching, correction and assembly of noisy (not so noisy ones as well) long reads.

The assembly process can be summarized as follows:

  1. overlap
  2. patch reads
  3. overlap (again)
  4. scrubbing
  5. assembly graph construction and touring
  6. optional read correction
  7. fasta file creation

Address of the bookmark: https://github.com/schloi/MARVEL

]]> Jit https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus Wed, 24 Oct 2018 23:35:09 -0500 https://bioinformaticsonline.com/bookmarks/view/37984/baum-%E2%80%93-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus <![CDATA[BAUM – Improving Genome Assembly by Adaptive Unique Mapping and Local Overlap-Layout-Consensus]]> BAUM, breaks the whole genome into regions by adaptive unique mapping; then the local OLC is used to assemble each region in parallel. BAUM can: (1) perform reference-assisted assembly based on the genome of a close species; (2) or improve the results of existing assemblies that are obtained based on short or long sequencing reads. 

Address of the bookmark: http://www.zhanyuwang.xin/wordpress/index.php/2017/07/21/baum-improving-genome-assembly-by-adaptive-unique-mapping-and-local-overlap-layout-consensus/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly Mon, 18 May 2020 16:47:56 -0500 https://bioinformaticsonline.com/bookmarks/view/41691/genobuntu-package-for-next-generation-sequencing-and-genome-assembly <![CDATA[Genobuntu: Package for Next Generation Sequencing and Genome Assembly]]>

Genobuntu is a software package containing more than 70 software and packages oriented towards NGS. In its current version, Genobuntu supports pre assembly tools, genome assemblers as well as post assembly tools.

Commonly used biological software and example script files for different assembly pipelines have also been provided, where the example script files can be updated to suit one’s experimental needs. Genobuntu attempts to reduce the amount of time and energy needed to build software workstations and it can also act as a good teaching source for a class room setting.

Therefore, Genobuntu offers a well-tailored environment for both novices and experts working in the field of genome assembly.

Features

  • Velvet
  • MiB
  • SSAKE
  • EULER
  • VCAKE
  • ABySS
  • ALLPATHS
  • Celera
  • SHARCGS
  • Allpaths
  • IDBA
  • TAIPAN
  • Edena
  • SOAPdenovo
  • Maq
  • IDBA-UD
  • No. of Reads present in the Ref. Seq.
  • ART NGS Reads Simulator
  • HiTEC, FASTQC
  • Minimum Description Length
  • SOAPaligner
  • Sequencing Read Archive Toolkit

Address of the bookmark: https://sourceforge.net/projects/genobuntu/

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics Sat, 26 Jun 2021 15:22:56 -0500 https://bioinformaticsonline.com/bookmarks/view/43110/quasimodo-quasispecies-metric-determination-on-omics <![CDATA[QuasiModo - Quasispecies Metric Determination on Omics]]> This repository contains the scripts and pipeline that reproduces the results of the HCMV benchmarking study. In this study we evaluated genome assemblers and variant callers on 10 in vitro generated, mixed strain HCMV sequence samples, each consisting of two lab strains in different abundance ratios. This tool can also be used to evaluate assemblies and variant calling results on other similar datasets.

https://academic.oup.com/bib/article/22/3/bbaa123/5868070

Address of the bookmark: https://github.com/hzi-bifo/Quasimodo

]]> Neel https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator Wed, 08 Mar 2023 01:39:33 -0600 https://bioinformaticsonline.com/bookmarks/view/44223/ale-assembly-likelihood-estimator <![CDATA[ALE: Assembly Likelihood Estimator]]> Just import the assembly, bam and ALE scores. You can convert the .ale file to a set of .wig files with ale2wiggle.py and IGV can read those directly.  Depending on your genome size you may want to convert the .wig files to the BigWig format.

Address of the bookmark: https://github.com/sc932/ALE

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly Sat, 08 Jun 2024 16:15:25 -0500 https://bioinformaticsonline.com/bookmarks/view/44559/metagraph-ultra-scalable-framework-for-dna-search-alignment-assembly <![CDATA[MetaGraph: Ultra Scalable Framework for DNA Search, Alignment, Assembly]]> The MetaGraph framework is designed to work with a wide range of input data sets, indexing from a few samples up to the contents of entire archives with hundreds of thousands of records. The indexing workflow always follows the same principle, transforming single input samples into error-removed, refined sample graphs, which are then merged into a joint metagraph index. Each input sample is annotated in the joint index as a subgraph. This graph index enriched with metadata can then be used for downstream applications such as sequence search or differential assembly.

Searcg link https://metagraph.ethz.ch/search 

Pre-print https://www.biorxiv.org/content/10.1101/2020.10.01.322164v4 

Address of the bookmark: https://metagraph.ethz.ch/

]]> Abhi https://bioinformaticsonline.com/bookmarks/view/36895/npscarf-real-time-scaffolder-using-spades-contigs-and-nanopore-sequencing-reads Mon, 11 Jun 2018 05:14:57 -0500 https://bioinformaticsonline.com/bookmarks/view/36895/npscarf-real-time-scaffolder-using-spades-contigs-and-nanopore-sequencing-reads <![CDATA[npScarf: real-time scaffolder using SPAdes contigs and Nanopore sequencing reads]]> Address of the bookmark: http://japsa.readthedocs.io/en/latest/tools/jsa.np.npscarf.html

]]> Shruti Paniwala https://bioinformaticsonline.com/bookmarks/view/35918/scubat-scaffolding-contigs-using-blat-and-transcripts Tue, 13 Mar 2018 06:52:24 -0500 https://bioinformaticsonline.com/bookmarks/view/35918/scubat-scaffolding-contigs-using-blat-and-transcripts <![CDATA[SCUBAT: Scaffolding Contigs Using Blat And Transcripts]]> SCUBAT (Scaffolding Contigs Using BLAT And Transcripts) uses any set of transcripts to identify cases where a transcript is split over multiple genome fragments and attempts to use this information to scaffold the genome.

Address of the bookmark: https://github.com/elswob/SCUBAT

]]> Rahul Nayak https://bioinformaticsonline.com/videolist/watch/3925/genome-annotation Sun, 25 Aug 2013 10:53:01 -0500 https://bioinformaticsonline.com/videolist/watch/3925/genome-annotation <![CDATA[Genome Annotation]]> Dr. Rob Edwards describes some of the problems, challenges, and approches in genome annotation, with a particular emphasis on how the Fellowship for the Interpretation of Genomes (FIG) developed subsystems using the SEED database available at http://www.theseed.org/]]> https://bioinformaticsonline.com/bookmarks/view/32868/pollux-platform-independent-error-correction-of-single-and-mixed-genomes Fri, 19 May 2017 09:41:27 -0500 https://bioinformaticsonline.com/bookmarks/view/32868/pollux-platform-independent-error-correction-of-single-and-mixed-genomes <![CDATA[Pollux: platform independent error correction of single and mixed genomes]]> Pollux: General-purpose error corrector that corrects errors introduced by Illumina, Ion Torrent, and Roche 454 sequencing technologies and can be applied to single- or mixed-genome data. In addition to correcting substitution errors, we locate and correct insertion, deletion, and homopolymer errors while remaining sensitive to low coverage areas of sequencing projects. Using published data sets, we correct 94% of Illumina MiSeq errors, 88% of Ion Torrent PGM errors, 85% of Roche 454 GS Junior errors. Introduced errors are 20 to 70 times more rare than successfully corrected errors. Furthermore, we show that the quality of assemblies improves when reads are corrected by our software.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-014-0435-6

Address of the bookmark: https://github.com/emarinier/pollux

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