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/

Alien_Hunter : prediction of putative Horizontal Gene Transfer (HGT) events

Jit — Sun, 07 Jan 2018 19:11:18 -0600

Alien_hunter is an application for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs).

An IVOM approach exploits compositional biases using variable order motif distributions and captures more reliably the local composition of a sequence compared to fixed-order methods. Optionally the predictions can be parsed into a 2-state 2nd order Hidden Markov Model (HMM), in a change-point detection framework, to optimize the localization of the boundaries of the predicted regions. The predictions (embl format) can be automatically loaded into the freely available Artemis genome viewer.

Address of the bookmark: http://www.sanger.ac.uk/science/tools/alien-hunter

GenomeThreader: Gene Prediction Software

Neel — Wed, 03 Oct 2018 15:34:08 -0500

GenomeThreader is a software tool to compute gene structure predictions. The gene structure predictions are calculated using a similarity-based approach where additional cDNA/EST and/or protein sequences are used to predict gene structures via spliced alignments. GenomeThreader was motivated by disabling limitations in GeneSeqer, a popular gene prediction program which is widely used for plant genome annotation.

Address of the bookmark: http://genomethreader.org/

MimiLook: A Phylogenetic Workflow for Detection of Gene Acquisition in Major Orthologous Groups of Megavirales

Abhi — Mon, 10 Jan 2022 06:32:22 -0600

This tool detects statistically validated events of gene acquisitions with the help of the T-REX algorithm by comparing individual gene tree with NCBI species tree. In between the steps, the workflow decides about handling paralogs, filtering outputs, identifying Megavirale specific OGs, detection of HGTs, along with retrieval of information about those OGs that are monophyletic with organisms from cellular domains of life.

https://www.readcube.com/articles/10.3390%2Fv9040072

Address of the bookmark: https://pubmed.ncbi.nlm.nih.gov/28387730/

The Gene Detectives: How a New Computational Tool Is Helping Us Read the History Written in Our Genes

BioStar — Thu, 10 Sep 2026 21:23:42 -0500

Imagine opening an ancient family album with no names, dates, or captions. Some photographs are missing, others have been copied, and a few show people who look almost identical. Your challenge is to discover who is related to whom and reconstruct the family story. In evolutionary biology, scientists face a similar mystery when they study genes. Every genome contains clues about its past, but genes can be duplicated, lost, and changed over millions of years, making their history difficult to trace.

A recent study published in PLOS Computational Biology introduces REvolutionH-tl 2.0 (https://pypi.org/project/revolutionhtl/), a computational tool designed to help solve this mystery. The software analyzes protein sequences and identifies evolutionary relationships between genes. It can help researchers detect important events such as gene duplication, gene loss, and speciation, allowing them to reconstruct how genes evolved across different organisms.

What makes the tool especially interesting is its focus on both speed and interpretation. The researchers compared REvolutionH-tl 2.0 with several existing computational tools and reported that it achieved competitive accuracy while requiring less computational time in their tests. The tool also includes visualization features, helping researchers turn complicated genetic data into evolutionary stories that are easier to explore.

Genes are more than simple sequences of DNA; they are records of life’s long history. Each surviving gene carries traces of the changes that shaped it. By bringing together computational analysis and visualization, REvolutionH-tl 2.0 acts like a detective, helping scientists uncover these hidden stories. Ultimately, tools like this can improve our understanding of how genomes evolved and how genes acquired the roles they perform today.

More at https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1013017

DarkHorse: a method for genome-wide prediction of horizontal gene transfer

Jit — Thu, 22 Jun 2017 07:58:35 -0500

A new approach to rapid, genome-wide identification and ranking of horizontal transfer candidate proteins is presented. The method is quantitative, reproducible, and computationally undemanding. It can be combined with genomic signature and/or phylogenetic tree-building procedures to improve accuracy and efficiency. The method is also useful for retrospective assessments of horizontal transfer prediction reliability, recognizing orthologous sequences that may have been previously overlooked or unavailable. These features are demonstrated in bacterial, archaeal, and eukaryotic examples.

Address of the bookmark: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1852411/

GeNeCK (Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks

Rahul Nayak — Tue, 15 Jan 2019 09:39:30 -0600

GeNeCK (Gene Network Construction Kit) is a comprehensive online tool kit that integrate various statistical methods to construct gene networks based on gene expression data and optional hub gene information.

It efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.

GeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at http://lce.biohpc.swmed.edu/geneck

Address of the bookmark: http://lce.biohpc.swmed.edu/geneck/

PyParanoid: a pipeline for rapid identification of homologous gene families in a set of genomes

BioStar — Thu, 13 Aug 2020 10:06:19 -0500

PyParanoid is a pipeline for rapid identification of homologous gene families in a set of genomes - a central task of any comparative genomics analysis. The "gold standard" for identifying homologs is to use reciprocal best hits (RBHs) which depends on performing a all-vs-all sequence comparison, usually using BLAST, to determine homology. However, these methods are computationally expensive, requiring O(n2) resources to identify RBHs. This is problematic, as the modern deluge of sequencing data means that comparative genomics analyses could be performed on datasets of thousands of strains.

Address of the bookmark: https://github.com/ryanmelnyk/PyParanoid

homologizer: Phylogenetic phasing of gene copies into polyploid subgenomes

Abhi — Sat, 03 Jun 2023 19:19:10 -0500

This tutorial describes the usage of homologizer to phase gene copies into polyploid subgenomes. The tutorial is an abbreviated version of a soon-to-be published paper in Methods in Molecular Biology. Please see that paper for many more details and practical considerations for running homologizer analyses. If you use homologizer, please cite the paper in which we first describe the method:

Freyman, W.A., Johnson, M.G., and C.J. Rothfels. 2022. Homologizer: phylogenetic phasing of gene copies into polyploid subgenomes. bioRxiv 2020.10.22.351486v4

homologizer is implemented in RevBayes. Please see http://revbayes.com to download and install RevBayes. For users without previous RevBayes experience, we recommend the tutorials at http://revbayes.com.

Address of the bookmark: https://github.com/wf8/homologizer

Explore taxdump files !

Jit — Sat, 08 Feb 2020 04:44:55 -0600

This is an extract of taxdump-readme.txt to be found at 
ftp://ftp.ncbi.nih.gov/pub/taxonomy/

The content of the archive
--------------------------

It may look like this:

delnodes.dmp
division.dmp
gencode.dmp
merged.dmp
names.dmp
nodes.dmp
readme.txt

The readme.txt file gives a brief description of *.dmp files. These files
contain taxonomic information and are briefly described below. Each of the
files store one record in the single line that are delimited by "\t|\n"
(tab, vertical bar, and newline) characters. Each record consists of one 
or more fields delimited by "\t|\t" (tab, vertical bar, and tab) characters.
The brief description of field position and meaning for each file follows.

nodes.dmp
---------

This file represents taxonomy nodes. The description for each node includes 
the following fields:

	tax_id					-- node id in GenBank taxonomy database
 	parent tax_id				-- parent node id in GenBank taxonomy database
 	rank					-- rank of this node (superkingdom, kingdom, ...) 
 	embl code				-- locus-name prefix; not unique
 	division id				-- see division.dmp file
 	inherited div flag  (1 or 0)		-- 1 if node inherits division from parent
 	genetic code id				-- see gencode.dmp file
 	inherited GC  flag  (1 or 0)		-- 1 if node inherits genetic code from parent
 	mitochondrial genetic code id		-- see gencode.dmp file
 	inherited MGC flag  (1 or 0)		-- 1 if node inherits mitochondrial gencode from parent
 	GenBank hidden flag (1 or 0)            -- 1 if name is suppressed in GenBank entry lineage
 	hidden subtree root flag (1 or 0)       -- 1 if this subtree has no sequence data yet
 	comments				-- free-text comments and citations

names.dmp
---------
Taxonomy names file has these fields:

	tax_id					-- the id of node associated with this name
	name_txt				-- name itself
	unique name				-- the unique variant of this name if name not unique
	name class				-- (synonym, common name, ...)

division.dmp
------------
Divisions file has these fields:
	division id				-- taxonomy database division id
	division cde				-- GenBank division code (three characters)
	division name				-- e.g. BCT, PLN, VRT, MAM, PRI...
	comments

gencode.dmp
-----------
Genetic codes file:

	genetic code id				-- GenBank genetic code id
	abbreviation				-- genetic code name abbreviation
	name					-- genetic code name
	cde					-- translation table for this genetic code
	starts					-- start codons for this genetic code

delnodes.dmp
------------
Deleted nodes (nodes that existed but were deleted) file field:

	tax_id					-- deleted node id

merged.dmp
----------
Merged nodes file fields:

	old_tax_id                              -- id of nodes which has been merged
	new_tax_id                              -- id of nodes which is result of merging