<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/39640?offset=10 https://bioinformaticsonline.com/bookmarks/view/41452/apollo-a-sequencing-technology-independent-scalable-and-accurate-assembly-polishing-algorithm Mon, 16 Mar 2020 10:09:26 -0500 https://bioinformaticsonline.com/bookmarks/view/41452/apollo-a-sequencing-technology-independent-scalable-and-accurate-assembly-polishing-algorithm <![CDATA[Apollo: A Sequencing-Technology-Independent, Scalable, and Accurate Assembly Polishing Algorithm]]> Apollo is an assembly polishing algorithm that attempts to correct the errors in an assembly. It can take multiple set of reads in a single run and polish the assemblies of genomes of any size. Described by Firtina et al. (preliminary version at https://arxiv.org/pdf/1902.04341.pdf

More at https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa179/5804978?rss=1

Address of the bookmark: https://github.com/CMU-SAFARI/Apollo

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data Tue, 27 Nov 2018 04:43:57 -0600 https://bioinformaticsonline.com/bookmarks/view/38304/lordfast-sensitive-and-fast-alignment-search-tool-for-long-noisy-read-sequencing-data <![CDATA[lordFAST: sensitive and Fast Alignment Search Tool for LOng noisy Read sequencing Data]]> lordFAST is a sensitive tool for mapping long reads with high error rates. lordFAST is specially designed for aligning reads from PacBio sequencing technology but provides the user the ability to change alignment parameters depending on the reads and application.

lordFAST, a novel long-read mapper that is specifically designed to align reads generated by PacBio and potentially other SMS technologies to a reference. lordFAST not only has higher sensitivity than the available alternatives, it is also among the fastest and has a very low memory footprint.

 

Address of the bookmark: https://github.com/vpc-ccg/lordfast

]]> BioJoker https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs Sun, 27 Oct 2019 00:57:23 -0500 https://bioinformaticsonline.com/bookmarks/view/40208/ragoo-fast-reference-guided-scaffolding-of-genome-assembly-contigs <![CDATA[RaGOO: Fast Reference-Guided Scaffolding of Genome Assembly Contigs]]> Alonge M, Soyk S, Ramakrishnan S, Wang X, Goodwin S, Sedlazeck FJ, Lippman ZB, Schatz MC: Fast and accurate reference-guided scaffolding of draft genomes. bioRxiv 2019.

RaGOO is a tool for coalescing genome assembly contigs into pseudochromosomes via minimap2 alignments to a closely related reference genome. The focus of this tool is on practicality and therefore has the following features:

  1. Good performance. On a MacBook Pro using Arabidopsis data, pseudochromosome construction takes less than a minute and the whole pipeline with SV calling takes ~2 minutes.
  2. Intact ordering and orienting of contigs.
  3. Misassembly correction
  4. GFF lift-over
  5. Structural variant calling with and integrated version of Assemblytics
  6. Confidence scores associated with the grouping, localization, and orientation for each contig.

Address of the bookmark: https://github.com/malonge/RaGOO

]]> Jit https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool Fri, 01 Dec 2017 04:10:54 -0600 https://bioinformaticsonline.com/bookmarks/view/34493/plast-a-fast-accurate-and-ngs-scalable-bank-to-bank-sequence-similarity-search-tool <![CDATA[PLAST: A fast, accurate and NGS scalable bank-to-bank sequence similarity search tool]]> PLAST is a fast, accurate and NGS scalable bank-to-bank sequence similarity search tool providing significant accelerations of seeds-based heuristic comparison methods, such as the Blast suite of algorithms.

Relying on unique software architecture, PLAST takes full advantage of recent multi-core personal computers without requiring any additional hardware devices.

PLAST stands for Parallel Local Sequence Alignment Search Tool and is was published in BMC Bioinformatics.

PLAST is a general purpose sequence comparison tool providing the following benefits:

  • PLAST is a high-performance sequence comparison tool designed to compare two sets of sequences (query vs. reference),
  • Reduces the processing time of sequences comparisons while providing highest quality results,
  • Contains a fully integrated data filtering engine capable of selecting relevant hits with user-defined criteria (E-Value, identity, coverage, alignment length, etc.),
  • Does not require any additional hardware, since it is a software solution. It is easy to install, cost-effective, takes full advantage of multi-core processors and uses a small RAM footprint,
  • Ready to be used on desktop computer, cluster, cloud as well as within distributed system running Hadoop.

https://plast.inria.fr/

Address of the bookmark: https://plast.inria.fr/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite Thu, 22 Mar 2018 10:40:51 -0500 https://bioinformaticsonline.com/bookmarks/view/36026/mmseqs20-ultra-fast-and-sensitive-protein-search-and-clustering-suite <![CDATA[MMseqs2.0: ultra fast and sensitive protein search and clustering suite]]> MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

The MMseqs2 user guide is available as Github Wiki or as PDF file (Thanks to pandoc!)

Please cite: Steinegger M and Soeding J. MMseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature Biotechnology, doi: 10.1038/nbt.3988 (2017).

Address of the bookmark: https://github.com/soedinglab/MMseqs2

]]> Jit https://bioinformaticsonline.com/bookmarks/view/36808/whatshap-fast-and-accurate-read-based-phasing Mon, 28 May 2018 09:52:16 -0500 https://bioinformaticsonline.com/bookmarks/view/36808/whatshap-fast-and-accurate-read-based-phasing <![CDATA[WhatsHap: fast and accurate read-based phasing]]> WhatsHap is a software for phasing genomic variants using DNA sequencing reads, also called read-based phasing or haplotype assembly. It is especially suitable for long reads, but works also well with short reads.

Features

  • Very accurate results (Martin et al., WhatsHap: fast and accurate read-based phasing)
  • Works well with Illumina, PacBio, Oxford Nanopore and other types of reads
  • It phases SNVs, indels and even “complex” variants (such as TCG → AGAA)
  • Pedigree phasing mode uses reads from related individuals (such as trios) to improve results and to reduce coverage requirements (Garg et al., Read-Based Phasing of Related Individuals).
  • WhatsHap is easy to install
  • It is easy to use: Pass in a VCF and one or more BAM files, get out a phased VCF. Supports multi-sample VCFs.
  • It produces standard-compliant VCF output by default
  • If desired, get output that is compatible with ReadBackedPhasing
  • Open Source (MIT license)

Address of the bookmark: https://whatshap.readthedocs.io/en/latest/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing Wed, 29 Aug 2018 09:20:46 -0500 https://bioinformaticsonline.com/bookmarks/view/37602/indexcov-fast-coverage-quality-control-for-whole-genome-sequencing <![CDATA[Indexcov: fast coverage quality control for whole-genome sequencing]]> indexcov, an efficient estimator of whole-genome sequencing coverage to rapidly identify samples with aberrant coverage profiles, reveal large-scale chromosomal anomalies, recognize potential batch effects, and infer the sex of a sample. Indexcov is available at https://github.com/brentp/goleft under the MIT license.

Address of the bookmark: https://github.com/brentp/goleft

]]> Jit https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains Wed, 14 Nov 2018 04:34:23 -0600 https://bioinformaticsonline.com/bookmarks/view/38208/anitools-web-a-web-tool-for-fast-genome-comparison-within-multiple-bacterial-strains <![CDATA[ANItools web: a web tool for fast genome comparison within multiple bacterial strains]]> ANItools is a software package written by PERL scripts that can be run in a Linux/Unix system. If you want to compare bacterial genomes and calculate their average nucleotide identity (ANI), you could download and run this program directly. Or you could send us the genome sequence by email. Then we will do the analysis work for you.

https://academic.oup.com/database/article/doi/10.1093/database/baw084/2630454

Address of the bookmark: http://ani.mypathogen.cn/

]]> Jit https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations Sun, 15 Dec 2019 10:19:35 -0600 https://bioinformaticsonline.com/bookmarks/view/40389/sequila-cov-a-fast-and-scalable-library-for-depth-of-coverage-calculations <![CDATA[SeQuiLa-cov: A fast and scalable library for depth of coverage calculations]]> The Docker image is available at https://hub.docker.com/r/biodatageeks/. Supplementary information on benchmarking procedure as well as test data are publicly accessible at the project documentation site http://biodatageeks.org/sequila/benchmarking/benchmarking.html#depth-of-coverage. An archival copy of the code and supporting data is also available via the GigaScience database GigaDB

• Project name: SeQuiLa-cov

• Project home page: http://biodatageeks.org/sequila/

• Source code repository: https://github.com/ZSI-Bio/bdg-sequila

• Operating system: Platform independent

• Programming language: Scala

• Other requirements: Docker

• License: Apache License 2.0

Address of the bookmark: https://academic.oup.com/gigascience/article/8/8/giz094/5543653

]]> Jit https://bioinformaticsonline.com/bookmarks/view/42645/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite Mon, 18 Jan 2021 10:47:56 -0600 https://bioinformaticsonline.com/bookmarks/view/42645/mmseqs2-ultra-fast-and-sensitive-sequence-search-and-clustering-suite <![CDATA[MMseqs2: ultra fast and sensitive sequence search and clustering suite]]> MMseqs2 (Many-against-Many sequence searching) is a software suite to search and cluster huge protein and nucleotide sequence sets. MMseqs2 is open source GPL-licensed software implemented in C++ for Linux, MacOS, and (as beta version, via cygwin) Windows. The software is designed to run on multiple cores and servers and exhibits very good scalability. MMseqs2 can run 10000 times faster than BLAST. At 100 times its speed it achieves almost the same sensitivity. It can perform profile searches with the same sensitivity as PSI-BLAST at over 400 times its speed.

Address of the bookmark: https://github.com/soedinglab/MMseqs2

]]> Manisha Mishra