<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/36865?offset=280 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/researchlabs/view/43913/lsugenomics-lab Thu, 07 Jul 2022 05:26:37 -0500 <![CDATA[lsugenomics Lab]]> In our lab, we seek to characterize and to compare genomes in order to better understand genetic and evolutionary processes linking genotypes to phenotypes.

Sequencing and decoding plant genomes have been integral in our approaches.

The overarching goal of our research is to understand how to interpret complex and fascinating messages embedded in genomes.

https://www.lsugenomics.org/

]]> https://bioinformaticsonline.com/bookmarks/view/44489/proksee Wed, 27 Mar 2024 11:11:54 -0500 https://bioinformaticsonline.com/bookmarks/view/44489/proksee <![CDATA[Proksee]]> Proksee is an expert system for genome assembly, annotation and visualization. To begin using Proksee, provide a complete genome sequence, sequencing reads or a CGView/Proksee map JSON file.

Please Cite the Following
Grant JR, Enns E, Marinier E, Mandal A, Herman EK, Chen C, Graham M, Van Domselaar G, and Stothard P
Nucleic Acids Research, 2023, gkad326, https://doi.org/10.1093/nar/gkad326

Address of the bookmark: https://proksee.ca/

]]> LEGE 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/33003/surankco-supervised-ranking-of-contigs-in-de-novo-assemblies Wed, 24 May 2017 04:46:52 -0500 https://bioinformaticsonline.com/bookmarks/view/33003/surankco-supervised-ranking-of-contigs-in-de-novo-assemblies <![CDATA[SuRankCo: supervised ranking of contigs in de novo assemblies]]> SuRankCo is a machine learning based software to score and rank contigs from de novo assemblies of next generation sequencing data. It trains with alignments of contigs with known reference genomes and predicts scores and ranking for contigs which have no related reference genome yet.

https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-015-0644-7

 

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

]]> Neel https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies Mon, 04 Dec 2017 10:09:37 -0600 https://bioinformaticsonline.com/bookmarks/view/34519/bandage-interactive-visualization-of-de-novo-genome-assemblies <![CDATA[Bandage: interactive visualization of de novo genome assemblies]]> Bandage (a Bioinformatics Application for Navigating De novo Assembly Graphs Easily) is a tool for visualizing assembly graphs with connections. Users can zoom in to specific areas of the graph and interact with it by moving nodes, adding labels, changing colors and extracting sequences. BLAST searches can be performed within the Bandage graphical user interface and the hits are displayed as highlights in the graph. By displaying connections between contigs, Bandage presents new possibilities for analyzing de novo assemblies that are not possible through investigation of contigs alone.

Availability and implementation: Source code and binaries are freely available at https://github.com/rrwick/Bandage. Bandage is implemented in C++ and supported on Linux, OS X and Windows. A full feature list and screenshots are available at http://rrwick.github.io/Bandage.

Address of the bookmark: http://rrwick.github.io/Bandage/

]]> Shruti Paniwala https://bioinformaticsonline.com/bookmarks/view/37842/rapclust-accurate-lightweight-clustering-of-de-novo-transcriptomes-using-fragment-equivalence-classes Thu, 04 Oct 2018 17:57:10 -0500 https://bioinformaticsonline.com/bookmarks/view/37842/rapclust-accurate-lightweight-clustering-of-de-novo-transcriptomes-using-fragment-equivalence-classes <![CDATA[RapClust: Accurate, Lightweight Clustering of de novo Transcriptomes using Fragment Equivalence Classes]]> RapClust is a tool for clustering contigs from de novo transcriptome assemblies. RapClust is designed to be run downstream of the Sailfish or Salmon tools for rapid transcript-level quantification. Specifically, RapClust relies on the fragment equivalence classes computed by these tools in order to determine how seqeunce is shared across the transcriptome, and how reads map to potentially-related contigs across different conditions.

Address of the bookmark: https://github.com/COMBINE-lab/RapClust

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation Thu, 26 May 2022 00:59:49 -0500 https://bioinformaticsonline.com/bookmarks/view/43877/crowdgo-machine-learning-and-semantic-similarity-guided-consensus-gene-ontology-annotation <![CDATA[CrowdGO: Machine learning and semantic similarity guided consensus Gene Ontology annotation]]> CrowdGO is a protein Gene Ontology predictor using a meta approach, analyzing the predictions of other tools in order to get an improved precision and recall.

Please note that the CrowdGO snakemake workflow is currently only tested on Ubuntu. It should work on OSX, but please report any errors to maarten.reijnders@unil.ch or create an issue.

https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1010075

Address of the bookmark: https://gitlab.com/mreijnders/crowdgo

]]> Shruti Paniwala https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads Sat, 02 Jan 2021 07:05:36 -0600 https://bioinformaticsonline.com/bookmarks/view/42530/shovill-assemble-bacterial-isolate-genomes-from-illumina-paired-end-reads <![CDATA[shovill: Assemble bacterial isolate genomes from Illumina paired-end reads]]> Shovill is a pipeline which uses SPAdes at its core, but alters the steps before and after the primary assembly step to get similar results in less time. Shovill also supports other assemblers like SKESA, Velvet and Megahit, so you can take advantage of the pre- and post-processing the Shovill provides with those too.

Address of the bookmark: https://github.com/tseemann/shovill

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