BOL: Related items

DFAST: a flexible prokaryotic genome annotation pipeline for faster genome publication

Jit — Tue, 14 Nov 2017 10:26:16 -0600

We developed a prokaryotic genome annotation pipeline, DFAST, that also supports genome submission to public sequence databases. DFAST was originally started as an on-line annotation server, and to date, over 7,000 jobs have been processed since its first launch in 2016. Here, we present a newly implemented background annotation engine for DFAST, which is also available as a standalone command-line program. The new engine can annotate a typical-sized bacterial genome within 10 minutes, with rich information such as pseudogenes, translation exceptions, and orthologous gene assignment between given reference genomes. In addition, the modular framework of DFAST allows users to customize the annotation workflow easily and will also facilitate extensions for new functions and incorporation of new tools in the future.

Availability and Implementation

The software is implemented in Python 3 and runs in both Python 2.7 and 3.4– on Macintosh and Linux systems. It is freely available at https://github.com/nigyta/dfast_core/ under the GPLv3 license with external binaries bundled in the software distribution. An on-line version is also available at https://dfast.nig.ac.jp/.

Address of the bookmark: https://dfast.nig.ac.jp/

Genome U-Plot: a whole genome visualization

Rahul Nayak — Fri, 13 Jul 2018 19:50:41 -0500

Genome U-Plot for producing clear and intuitive graphs that allows researchers to generate novel insights and hypotheses by visualizing SVs such as deletions, amplifications, and chromoanagenesis events. The main features of the Genome U-Plot are its layered layout, its high spatial resolution and its improved aesthetic qualities.

https://github.com/gaitat/GenomeUPlot

Address of the bookmark: https://github.com/gaitat/GenomeUPlot

GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences

Jit — Fri, 28 Sep 2018 09:35:10 -0500

GRSR is a Tool for Deriving Genome Rearrangement Scenarios for Multiple Uni-chromosomal Genomes. This tool will do the following steps:

Step 1. Run mugsy to get multiple sequence alignment results.
Step 2 & 3. Extraction of the Coordinates of Core Blocks, Construction of Synteny Blocks and Generating Signed Permutations.
Step 4. Generate pairwise genome rearrangement scenarios and find repeats at the breakpoints of each rearrangement events.

https://github.com/DanwangJessica/GRSR

Address of the bookmark: https://github.com/DanwangJessica/GRSR

MitoZ: a toolkit for animal mitochondrial genome assembly, annotation and visualization

Jit — Fri, 24 Jan 2020 04:09:15 -0600

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

HASLR: a hybrid assembler which uses both second and third generation sequencing reads

BioStar — Mon, 04 May 2020 02:04:03 -0500

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

odgi: optimized dynamic genome/graph implementation

Abhimanyu Singh — Tue, 01 Feb 2022 23:42:21 -0600

odgi provides an efficient and succinct dynamic DNA sequence graph model, as well as a host of algorithms that allow the use of such graphs in bioinformatic analyses.

Careful encoding of graph entities allows odgi to efficiently compute and transform pangenomes with minimal overheads. odgi implements a dynamic data structure that leveraged multi-core CPUs and can be updated on the fly.

The edges and path steps are recorded as deltas between the current node id and the target node id, where the node id corresponds to the rank in the global array of nodes. Graphs built from biological data sets tend to have local partial order and, when sorted, the deltas be small. This allows them to be compressed with a variable length integer representation, resulting in a small in-memory footprint at the cost of packing and unpacking.

The RAM and computational savings are substantial. In partially ordered regions of the graph, most deltas will require only a single byte.

Address of the bookmark: https://github.com/pangenome/odgi

Genomicus: genome browser that enables users to navigate in genomes in several dimensions

Jit — Mon, 28 Feb 2022 23:27:37 -0600

Genomicus is a genome browser that enables users to navigate in genomes in several dimensions: linearly along chromosome axes, transversaly across different species, and chronologicaly along evolutionary time.

Once a query gene has been entered, it is displayed in its genomic context in parallel to the genomic context of all its orthologous and paralogous copies in all the other sequenced metazoan genomes. Moreover, Genomicus stores and displays the predicted ancestral genome structure in all the ancestral species within the phylogenetic range of interest.

All the data on extant species displayed in this browser are from Ensembl.

Summary statistics of Genomicus version 105.01: (view species tree in pdf or newick)


Number of extant species	200
Number of extant genes	4303993
Number of ancestral species	196
Number of ancestral genes	4624213
Number of ancestral synteny blocks	83342

Address of the bookmark: https://www.genomicus.bio.ens.psl.eu/genomicus-105.01/cgi-bin/search.pl

Monkeypox virus isolate MPXV_USA_2022_MA001, complete genome

Jit — Tue, 26 Jul 2022 06:21:07 -0500

LOCUS       ON563414              197205 bp    DNA     linear   VRL 30-MAY-2022
DEFINITION  Monkeypox virus isolate MPXV_USA_2022_MA001, complete genome.
ACCESSION   ON563414
VERSION     ON563414.3
KEYWORDS    .
SOURCE      Monkeypox virus (monkeypox)
  ORGANISM  Monkeypox virus
            Viruses; Varidnaviria; Bamfordvirae; Nucleocytoviricota;
            Pokkesviricetes; Chitovirales; Poxviridae; Chordopoxvirinae;
            Orthopoxvirus.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/nuccore/ON563414

Oxford Nanopore Sequencing, Hybrid Error Correction, and de novo Assembly of a Eukaryotic Genome

Jit — Wed, 29 Nov 2017 05:08:53 -0600

Monitoring the progress of DNA molecules through a membrane pore has been postulated as a method for sequencing DNA for several decades. Recently, a nanopore-based sequencing instrument, the Oxford Nanopore MinION, has become available that we used for sequencing the S. cerevisiae genome. To make use of these data, we developed a novel open-source hybrid error correction algorithm Nanocorr (https://github.com/jgurtowski/nanocorr) specifically for Oxford Nanopore reads, as existing packages were incapable of assembling the long read lengths (5-50kbp) at such high error rate (between ~5 and 40% error). With this new method we were able to perform a hybrid error correction of the nanopore reads using complementary MiSeq data and produce a de novo assembly that is highly contiguous and accurate: the contig N50 length is more than ten-times greater than an Illumina-only assembly (678kb versus 59.9kbp), and has greater than 99.88% consensus identity when compared to the reference. Furthermore, the assembly with the long nanopore reads presents a much more complete representation of the features of the genome and correctly assembles gene cassettes, rRNAs, transposable elements, and other genomic features that were almost entirely absent in the Illumina-only assembly.

Address of the bookmark: http://schatzlab.cshl.edu/data/nanocorr/

LACHESIS: Genome Assembly with Hi-C-based Contact Probability Maps (LACHESIS)

Jit — Mon, 14 May 2018 04:26:30 -0500

LACHESIS is method that exploits contact probability map data (e.g. from Hi-C) for chromosome-scale de novo genome assembly.

Further information about LACHESIS, including source code, documentation and a user's guide are available at: http://shendurelab.github.io/LACHESIS.

Manuscript describing LACHESIS was published as: Burton JN#, Adey A, Patwardhan RP, Qiu R, Kitzman JO, Shendure J#. Chromosome-scale scaffolding of de novo genome assemblies based on chromatin interactions. Nature Biotechnology 2013 Dec;31(12):1119-25. doi: 10.1038/nbt.272. PubMed PMID: 24185095.

http://shendurelab.github.io/LACHESIS/

Address of the bookmark: http://shendurelab.github.io/LACHESIS/