<![CDATA[BOL: Related items]]> https://bioinformaticsonline.com/related/31295?offset=140 https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop Thu, 04 Oct 2018 17:23:18 -0500 https://bioinformaticsonline.com/bookmarks/view/37840/long-read-assembly-workshop <![CDATA[Long read assembly workshop !]]> This is a tutorial for a workshop on long-read (PacBio) genome assembly.

It demonstrates how to use long PacBio sequencing reads to assemble a bacterial genome, and includes additional steps for circularising, trimming, finding plasmids, and correcting the assembly with short-read Illumina data.

 Please comment if you know any other long read addembly tutorial.

Address of the bookmark: http://sepsis-omics.github.io/tutorials/modules/cmdline_assembly_v2/

]]> Rahul Nayak https://bioinformaticsonline.com/bookmarks/view/38210/skesa-strategic-k-mer-extension-for-scrupulous-assemblies Wed, 14 Nov 2018 04:45:41 -0600 https://bioinformaticsonline.com/bookmarks/view/38210/skesa-strategic-k-mer-extension-for-scrupulous-assemblies <![CDATA[SKESA: strategic k-mer extension for scrupulous assemblies]]> SKESA is a DeBruijn graph-based de-novo assembler designed for assembling reads of microbial genomes sequenced using Illumina. Comparison with SPAdes and MegaHit shows that SKESA produces assemblies that have high sequence quality and contiguity, handles low-level contamination in reads, is fast, and produces an identical assembly for the same input when assembled multiple times with the same or different compute resources.

Source code for SKESA is freely available at https://github.com/ncbi/SKESA/releases.

Research Paper @ Link

SKESA algorithm are as follows:

image

Address of the bookmark: https://github.com/ncbi/SKESA/releases

]]> Jit https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools Wed, 15 Mar 2017 14:19:01 -0500 https://bioinformaticsonline.com/bookmarks/view/31568/pacbio-long-reads-compatible-software-and-tools <![CDATA[Pacbio Long Reads Compatible Software and Tools]]> The following software packages are known to be compatible with PacBio® data, in addition to PacBio's own SMRT® Analysis suite. All packages are believed to be open source or freely available for non-commercial use. See the individual project sites for up-to-date license information. A separate page lists commercial software.

Know of any other open source software for PacBio data? Email us.

Software categories:

Address of the bookmark: https://github.com/PacificBiosciences/DevNet/wiki/Compatible-Software

]]> Archana Malhotra https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg Fri, 21 Dec 2018 22:06:31 -0600 https://bioinformaticsonline.com/bookmarks/view/38526/versatile-genome-assembly-evaluation-with-quast-lg <![CDATA[Versatile genome assembly evaluation with QUAST-LG]]> QUAST-LG is an extension of QUAST intended for evaluating large-scale genome assemblies (up to mammalian-size).

QUAST-LG is included in the QUAST  package starting from version 5.0.0 (download the latest release). Run QUAST as usual and do not forget to add ‐‐large option to your command!

A short list of the new features (see CHANGES for all):

  • Significant speedup achieved by both use of new fast aligner (minimap2) and the refactoring of alignment analyzing modules
  • New k-mer-based completeness and correctness metrics
  • BUSCO added for enhanced reference-free analysis
  • The concept of upper bound assembly (theoretical limits on the assembly completeness and contiguity for a given genome and set of reads)

Address of the bookmark: http://cab.spbu.ru/software/quast-lg/

]]> Jit https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly Tue, 22 Jan 2019 09:39:02 -0600 https://bioinformaticsonline.com/blog/view/38765/list-of-tools-frequently-used-while-genome-assembly <![CDATA[List of tools frequently used while genome assembly]]> List of tools frequently used while genome assembly:

I have used the following assemblers

I have used the following mappers

I have used the following polishing tools

I have used the following tools to assess genome assembly characteristics

If you have any ideas or superior tools we have missed please let us know in the comments.

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization Fri, 24 Jan 2020 04:09:15 -0600 https://bioinformaticsonline.com/bookmarks/view/40598/mitoz-a-toolkit-for-animal-mitochondrial-genome-assembly-annotation-and-visualization <![CDATA[MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization]]> MitoZ is a Python3-based toolkit which aims to automatically filter pair-end raw data (fastq files), assemble genome, search for mitogenome sequences from the genome assembly result, annotate mitogenome (genbank file as result), and mitogenome visualization. MitoZ is available from https://github.com/linzhi2013/MitoZ.

https://academic.oup.com/nar/article/47/11/e63/5377471

Address of the bookmark: https://github.com/linzhi2013/MitoZ

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics Tue, 17 Mar 2020 06:19:06 -0500 https://bioinformaticsonline.com/bookmarks/view/41459/jcvipython-utility-libraries-on-genome-assembly-annotation-and-comparative-genomics <![CDATA[JCVI:Python utility libraries on genome assembly, annotation and comparative genomics]]> Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.

https://github.com/tanghaibao/jcvi

More at https://github.com/tanghaibao/jcvi/wiki

Address of the bookmark: https://github.com/tanghaibao/jcvi

]]> Jit https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads Mon, 04 May 2020 02:04:03 -0500 https://bioinformaticsonline.com/bookmarks/view/41599/haslr-a-hybrid-assembler-which-uses-both-second-and-third-generation-sequencing-reads <![CDATA[HASLR: a hybrid assembler which uses both second and third generation sequencing reads]]> HASLR, a hybrid assembler which uses both second and third generation sequencing reads to efficiently generate accurate genome assemblies. Our experiments show that HASLR is not only the fastest assembler but also the one with the lowest number of misassemblies on all the samples compared to other tested assemblers. Furthermore, the generated assemblies in terms of contiguity and accuracy are on par with the other tools on most of the samples. Availability. HASLR is an open source tool available at https://github.com/vpc-ccg/haslr.

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

]]> BioStar https://bioinformaticsonline.com/bookmarks/view/42267/hapsolo-an-optimization-approach-for-removing-secondary-haplotigs-during-diploid-genome-assembly-and-scaffolding Mon, 26 Oct 2020 21:23:36 -0500 https://bioinformaticsonline.com/bookmarks/view/42267/hapsolo-an-optimization-approach-for-removing-secondary-haplotigs-during-diploid-genome-assembly-and-scaffolding <![CDATA[HapSolo: An optimization approach for removing secondary haplotigs during diploid genome assembly and scaffolding.]]> Despite marked recent improvements in long-read sequencing technology, the assembly of diploid genomes remains a difficult task. A major obstacle is distinguishing between alternative contigs that represent highly heterozygous regions. If primary and secondary contigs are not properly identified, the primary assembly will overrepresent both the size and complexity of the genome, which complicates downstream analysis such as scaffolding.

More at https://github.com/esolares/HapSolo

Address of the bookmark: https://github.com/esolares/HapSolo

]]> Jit https://bioinformaticsonline.com/researchlabs/view/35125/eugene-v-koonin-lab Tue, 09 Jan 2018 05:01:15 -0600 <![CDATA[Eugene V. Koonin Lab]]> Interested in understanding the evolution of life. To obtain glimpses of such understanding, we employ existing and new methods of computational biology to perform research in several major areas.

https://www.ncbi.nlm.nih.gov/research/groups/koonin/

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