BOL: Related items

DeCoSTAR - Detection of Co-evolution

Jit — Fri, 14 Apr 2017 06:27:25 -0500

DeCoSTAR is a software which aims at reconstructing ancestral gene or genome organizations, in the form of sets of neighborhood relations -adjacencies- between pairs of ancestral genes or gene domains.
Ancestral genes or domains are deduced from reconciled gene trees in a context of birth, speciation, duplication, loss, transfer, which are either given as input or computed with the ecceTERA package, to which DeCoSTAR is integrated. DeCoSTAR constructs parsimonious scenarios of gains and breakages of adjacencies, and contains in particular all the features of previous software DeCo, DeCoLT, ArtDeCo and DeClone. It provides statistical supports on ancestral adjacencies, or the possibility to handle badly assembled genomes.
DeCoSTAR is able to reconstruct the histories of domains inside genes, including gene fusion and fission events, as well as ancestral genome structures for dozens of whole genomes from all kingdoms of life in a few minutes.

Address of the bookmark: http://pbil.univ-lyon1.fr/software/DeCoSTAR/

DESCHRAMBLER

Jit — Thu, 29 Jun 2017 11:54:59 -0500

DESCHRAMBLER is shown to produce highly accurate reconstructions using data simulation and by benchmarking it against other reconstruction tools

You can find the detail of reconstructed data at http://bioinfo.konkuk.ac.kr/DESCHRAMBLER/

Address of the bookmark: https://github.com/jkimlab/DESCHRAMBLER

REGEN: Ancestral Genome Reconstruction for Bacteria

Rahul Nayak — Tue, 06 Mar 2018 05:02:36 -0600

REGEN infers evolutionary events, including gene creation and deletion and replicon fission and fusion. The reconstruction can be performed by either a maximum parsimony or a maximum likelihood method. Gene content reconstruction is based on the concept of neighboring gene pairs. REGEN was designed to be used with any set of genomes that are sufficiently related, which will usually be the case for bacteria within the same taxonomic order.

Address of the bookmark: http://www.mdpi.com/2073-4425/3/3/423

Jvarkit : Java utilities for Bioinformatics

Jit — Fri, 08 Jun 2018 09:31:55 -0500

Collection of Java tool kits for bioinformatics works: Jvarkit : Java utilities for Bioinformatics

Address of the bookmark: http://lindenb.github.io/jvarkit/

You can't hide from Genome Hackers

Neel — Sat, 13 Oct 2018 14:17:28 -0500

Young computational biologist named Yaniv Erlich shocked the research world by showing it was possible to unmask the identities of people listed in anonymous genetic databases using only an Internet connection

Paper: http://science.sciencemag.org/content/early/2018/10/10/science.aau4832

More at https://www.wired.com/story/genome-hackers-show-no-ones-dna-is-anonymous-anymore/

Genome sequence-based (sub-)species delineation.

Abhimanyu Singh — Wed, 12 Dec 2018 08:31:14 -0600

The GGDC web service reports digital DDH for a universal and accurate delineation of prokaryotic (sub-)species without inheriting the pitfalls of classic DDH, and also calculates differences in genomic G+C content.

http://ggdc.dsmz.de/ggdc_background.php#

Genome-to-Genome Distance Calculator 2.1

http://ggdc.dsmz.de/ggdc.php

Address of the bookmark: http://ggdc.dsmz.de/

Caulobacter ethensis - 2.0 : Computer-generated Genome of a Living Organism

Abhimanyu Singh — Wed, 03 Apr 2019 08:45:22 -0500

All the genome sequences of organisms known throughout the world are stored in a database belonging to the National Center for Biotechnology Information in the United States. As of today, the database has an additional entry: Caulobacter ethensis-2.0.

It is the world's first fully computer-generated genome of a living organism, developed by scientists at ETH Zurich.

However, it must be emphasised that although the genome for C. ethensis-2.0 was physically produced in the form of a very large DNA molecule, a corresponding organism does not yet exist.

Source: https://www.sciencedaily.com/releases/2019/04/190401171343.htm

MGSE: Mapping-based Genome Size Estimation

Shruti Paniwala — Fri, 17 Jan 2020 02:11:43 -0600

MGSE can harness the power of files generated in genome sequencing projects to predict the genome size. Required are the FASTA file containing a high continuity assembly and a BAM file with all available reads mapped to this assembly. The script construct_cov_file.py (https://doi.org/10.1186/s12864-018-5360-z) allows the generation of a COV file based on the (sorted) BAM file (also possible via MGSE directly). Next, this COV file can be used by MGSE to calculate the coverage in provided reference regions and to calculate the total number of mapped bases. Both values are subjected to the genome size estimation. Providing accurate reference regions is crucial for this genome size estimation.

Address of the bookmark: https://github.com/bpucker/MGSE

Synteny and Rearrangement Identifier (SyRI)

Jit — Tue, 05 May 2020 10:37:10 -0500

SyRI is a comprehensive tool for predicting genomic differences between related genomes using whole-genome assemblies (WGA). The assemblies are aligned using whole-genome alignment tools, and these alignments are then used as input to SyRI. SyRI identifies syntenic path (longest set of co-linear regions), structural rearrangements (inversions, translocations, and duplications), local variations (SNPs, indels, CNVs etc) within syntenic and structural rearrangements, and un-aligned regions.

Address of the bookmark: https://schneebergerlab.github.io/syri/

Reference Sequence Resource!

LEGE — Wed, 15 Sep 2021 21:15:22 -0500

The ENCODE project uses Reference Genomes from NCBI or UCSC to provide a consistent framework for mapping high-throughput sequencing data. In general, ENCODE data are mapped consistently to 2 human (GRCH38, hg19) and 2 mouse (mm9/mm10) genomes for historical comparability. Drosophia melanogaster experiments are mapped to either dm3 or dm6 and Caenorhabdilis elegans experiments are mapped to ce10 or ce11. T

Address of the bookmark: https://www.encodeproject.org/data-standards/reference-sequences/