BOL: Related items

pyGenomeTracks: Standalone program and library to plot beautiful genome browser tracks

Neel — Fri, 09 Nov 2018 12:34:23 -0600

pyGenomeTracks aims to produce high-quality genome browser tracks that are highly customizable. Currently, it is possible to plot:

bigwig
bed (many options)
bedgraph
links (represented as arcs)
Hi-C matrices (if HiCExplorer is installed)

Address of the bookmark: https://github.com/deeptools/pyGenomeTracks

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

Jit — Thu, 15 Nov 2018 12:48:30 -0600

NovoGraph: building whole genome graphs from long-read-based de novo assemblies

An algorithmically novel approach to construct a genome graph representation of long-read-based de novo sequence assemblies. We then provide a proof of principle by creating a genome graph of seven ethnically-diverse human genomes.

https://f1000research.com/articles/7-1391/v1

Address of the bookmark: https://github.com/NCBI-Hackathons/NovoGraph

Purge Haplotigs: Pipeline to help with curating heterozygous diploid genome assemblies

Rahul Nayak — Mon, 17 Dec 2018 03:17:20 -0600

Some parts of a genome may have a very high degree of heterozygosity. This causes contigs for both haplotypes of that part of the genome to be assembled as separate primary contigs, rather than as a contig and an associated haplotig. This can be an issue for downstream analysis whether you're working on the haploid or phased-diploid assembly.

Identify pairs of contigs that are syntenic and move one of them to the haplotig 'pool'. The pipeline uses mapped read coverage and Minimap2 alignments to determine which contigs to keep for the haploid assembly. Dotplots are optionally produced for all flagged contig matches, juxtaposed with read-coverage, to help the user determine the proper assignment of any remaining ambiguous contigs. The pipeline will run on either a haploid assembly (i.e. Canu, FALCON or FALCON-Unzip primary contigs) or on a phased-diploid assembly (i.e. FALCON-Unzip primary contigs + haplotigs). Here are two examples of how Purge Haplotigs can improve a haploid and diploid assembly.

Address of the bookmark: https://bitbucket.org/mroachawri/purge_haplotigs

GenomeView: genome browser and annotation editor

Rahul Nayak — Wed, 02 Jan 2019 04:09:06 -0600

GenomeView is a genome browser and annotation editor that displays reference sequence, annotation, multiple alignments, short read alignments and graphs. Most major data formats are supported. Local and internet files can be loaded.
This project has moved to GitHub: https://github.com/GenomeView/genomeview

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

The Rogers Lab

Mon, 15 Jul 2019 08:07:44 -0500

The Rogers lab studies evolution of genome structure. We explore the ways that complex mutations like duplications, deletions, rearrangements, and retrogenes can create new genetic material. We study how these new mutations are important for adaptation. We are currently working on projects in Drosophila, Mammoths, Elephants, Bivalves, and Frogs absolutely no amphibians. This multi-organism approach can help us understand when and why complex mutations are important for organism fitness.

More at http://evolscientist.com/

simuG: a general-purpose genome simulator

BioStar — Thu, 28 Nov 2019 04:33:18 -0600

Simulated genomes with pre-defined and random genomic variants can be very useful for benchmarking genomic and bioinformatics analyses. Here we introduce simuG, a lightweight tool for simulating the full-spectrum of genomic variants (single nucleotide polymorphisms, Insertions/Deletions, copy number variants, inversions and translocations) for any organisms (including human). The simplicity and versatility of simuG make it a unique general-purpose genome simulator for a wide-range of simulation-based applications.

Address of the bookmark: https://github.com/yjx1217/simuG

China’s BGI says it can sequence a genome for just $100

Neel — Sat, 29 Feb 2020 04:49:43 -0600

Using technology originally acquired in the US, the Chinese gene giant BGI Group says it will make genome sequencing cheaper than ever, breaking the $100 barrier for the first time.

The Shenzhen company says the low cost will be possible with an “extreme” DNA sequencing system it plans to offer that is capable of decoding the genomes of 100,000 people a year.

Ref: https://www.technologyreview.com/s/615289/china-bgi-100-dollar-genome/

RefKA: A fast and efficient long-read genome assembly approach for large and complex genomes

Rahul Nayak — Fri, 01 May 2020 03:00:40 -0500

RefKA, a reference-based approach for long read genome assembly. This approach relies on breaking up a closely related reference genome into bins, aligning k-mers unique to each bin with PacBio reads, and then assembling each bin in parallel followed by a final bin-stitching step.

Address of the bookmark: https://github.com/AppliedBioinformatics/RefKA

Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome

BioStar — Wed, 22 Jul 2020 10:11:13 -0500

We have developed the Sequence Ontology Bioinformatics Analysis (SOBA) tool to provide a simple statistical and graphical summary of an annotated genome. We envisage its use during annotation jamborees, genome comparison and for use by developers for rapid feedback during annotation software development and testing. SOBA also provides annotation consistency feedback to ensure correct use of terminology within annotations, and guides users to add new terms to the Sequence Ontology when required. SOBA is available at http://www.sequenceontology.org/cgi-bin/soba.cgi.

More at https://pubmed.ncbi.nlm.nih.gov/20494974/

Address of the bookmark: http://www.sequenceontology.org/cgi-bin/soba.cgi

Svardal lab

Sat, 20 Feb 2021 10:01:19 -0600

In the Svardal lab they are interested how the astonishing natural diversity we see on earth came into being, by which forces it formed and how it is changing today. Hence, they are trying to understand the process of evolution, with mathematical models and through the analysis of genome sequencing data.

Genomes, and in particular differences between them, are a crucial source of information to understand evolution and biology in general. They provide a record of the evolutionary past of populations, their relatedness patterns, their demography, and their adaptations.

More at https://www.uantwerpen.be/en/staff/hannes-svardal/svardal-lab/