BOL: Related items

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/

Tigers genome sequenced

Rahul Agarwal — Tue, 17 Sep 2013 16:48:24 -0500

Fifteen scientists led by Dr Jong Bhak of Genome Research Foundation, South Korea, decoded as many as 3 billion nucleotides (organic molecules that form the basic building blocks of nucleic acids, such as DNA). They identified 20,000 genes related to various functions of the tiger.

The biggest and perhaps most fearsome of the world's big cats, the tiger, shares 95.6 percent of its DNA with humans' cute and furry companions, domestic cats.

The new research showed that big cats have genetic mutations that enabled them to be carnivores. The team also identified mutations that allow snow leopards to thrive at high altitudes.

Reference:

http://www.nbcnews.com/science/your-cat-ferocious-tigers-share-lot-95-6-percent-their-4B11182690

http://timesofindia.indiatimes.com/home/environment/flora-fauna/Gene-mapping-of-tiger-completed/articleshow/22671681.cms

Paper:

http://www.nature.com/ncomms/2013/130917/ncomms3433/full/ncomms3433.html

EuGI: a novel resource for studying genomic islands to facilitate horizontal gene transfer detection in eukaryotes

Surabhi Chaudhary — Sat, 12 May 2018 07:26:59 -0500

SWGIS v2.0 along with the EuGI database, which houses GIs identified in 66 different eukaryotic species, and the EuGI web-resource, provide the first comprehensive resource for studying HGT in eukaryotes.

https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8

Address of the bookmark: https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-018-4724-8

EGAD: Ultra-fast functional analysis of gene networks

Rahul Nayak — Fri, 14 Dec 2018 04:10:35 -0600

With the EGAD (Extending ‘Guilt-by-Association’ by Degree) package, we present a series of highly efficient tools to calculate functional properties in networks based on the guilt-by-association principle. These allow rapid controlled comparisons and analyses. Two of the core features are: a function prediction algorithm which is fully vectorized (neighbor_voting), allowing network characterization across even thousands of functional groups to be accomplished in minutes in cross-validation and an analytic determination of the optimal prior to guess candidates genes across multiple functional sets (calculate_multifunc, auc_multifunc).

Address of the bookmark: https://github.com/sarbal/EGAD

gggenes: a ggplot2 extension for drawing gene arrow maps.

BioStar — Tue, 02 Jun 2020 11:43:34 -0500

Install the stable version of gggenes from CRAN:

install.packages("gggenes")

If you want the development version, install it from GitHub:

devtools::install_github("wilkox/gggenes")

More at https://github.com/wilkox/gggenes

Address of the bookmark: http://wilkox.org/gggenes

MetaEuk - sensitive, high-throughput gene discovery and annotation for large-scale eukaryotic metagenomics

Jit — Wed, 13 Jan 2021 19:29:32 -0600

MetaEuk is a modular toolkit designed for large-scale gene discovery and annotation in eukaryotic metagenomic contigs. Metaeuk combines the fast and sensitive homology search capabilities of MMseqs2 with a dynamic programming procedure to recover optimal exons sets. It reduces redundancies in multiple discoveries of the same gene and resolves conflicting gene predictions on the same strand. MetaEuk is GPL-licensed open source software that is implemented in C++ and available for Linux and macOS. The software is designed to run on multiple cores.

Address of the bookmark: https://github.com/soedinglab/metaeuk

R package for visualising GO enrichment

Jit — Mon, 22 Jul 2013 12:25:09 -0500

An R package that visualizes the GO enrichment results as word clouds and arranges them together with figures of experimental data. This allows us to draw informative summary plots for analyses such as differential expression or clustering, where for each gene list we display its behaviour in the experiment alongside with its GO annotations.

Links @ http://raivokolde.github.io/GOsummaries/

Lab @ http://biit.cs.ut.ee/about/main

clusterProfiler

Jit — Thu, 16 Jun 2016 18:57:03 -0500

statistical analysis and visulization of functional profiles for genes and gene clusters

Bioconductor version: Release (3.3)

This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene and gene clusters.

Author: Guangchuang Yu with contributions from Li-Gen Wang and Giovanni Dall'Olio.

Maintainer: Guangchuang Yu

Citation (from within R, enter citation("clusterProfiler")):

Yu G, Wang L, Han Y and He Q (2012). “clusterProfiler: an R package for comparing biological themes among gene clusters.” OMICS: A Journal of Integrative Biology, 16(5), pp. 284-287.
Installation

To install this package, start R and enter:

## try http:// if https:// URLs are not supported
source("https://bioconductor.org/biocLite.R")
biocLite("clusterProfiler")

https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

Address of the bookmark: https://www.bioconductor.org/packages/devel/bioc/vignettes/clusterProfiler/inst/doc/clusterProfiler.html

Pathway Analysis

Rahul Agarwal — Fri, 03 Oct 2014 08:51:13 -0500

Pathway Analysis is usually performed with aim to enrich the genes with their functional information and reveal the underlying biological mechanisms pursue by genes. Pathway Analysis is not only limited to what biological pathways a particular set of expressed genes follow but also to disclose the relationships between these genes. With availability of more genomics, transcriptomics and proteomics data, interactions between genes involve in multiple pathways become more clear and also relationships between the genes, their transcripts, and their gene products. However, existing tools and dbs mainly based on knowledge driven approach in which pathways will be identified by finding the correlation between the information in one of the pathway knowledge databases (KEGG,Reactome,Panther,BioCarta, Panther,GO,NCI,WikiPathways,etc) and gene expression result for a specific conditions for instance tumor, obesity , cold resistant crops/plants, etc.

Introductory Articles/ppt/sources:

http://www.ploscompbiol.org/article/info%3Adoi%2F10.1371%2Fjournal.pcbi.1002375

http://bioinformatics.mdanderson.org/MicroarrayCourse/Lectures09/Pathway%20Analysis.pdf

http://gettinggeneticsdone.blogspot.de/2012/03/pathway-analysis-for-high-throughput.html

http://davetang.org/muse/tag/pathway/

https://www.biostars.org/p/42219/

http://bioinformatics.ca//files/public/Pathways_2014_Module4_v2.pdf

http://bioinformatics.ca//files/public/Pathways_2014_Module2.pdf

Impotant Database and Tools:

GeneMANIA, Cytoscape, IPA and Metacore (Commerical ), Pathway Commons, Reactome ,Panther, BioCyc, WikiPathways, Pathvisio, KEGG, NCI, Stringdb, Amigo, WebGestalt ,ConsensusPathDB ,GSEA,Blast2go

Popular R based tools:

Reactome.db, ReactomePA, ClusterProfiler, Gage, SPIA, topGO, Pathview,DOSE,GOStat

More:

http://www.bioconductor.org/help/search/index.html?q=Enrichment+analysis+

LAST

Archana Malhotra — Wed, 09 Mar 2016 14:27:01 -0600

LAST can:

Handle big sequence data, e.g:
- Compare two vertebrate genomes
- Align billions of DNA reads to a genome
Indicate the reliability of each aligned column.
Use sequence quality data properly.
Compare DNA to proteins, with frameshifts.
Compare PSSMs to sequences
Calculate the likelihood of chance similarities between random sequences.
Do split and spliced alignment.
Train alignment parameters for unusual kinds of sequence (e.g. nanopore).

Address of the bookmark: http://last.cbrc.jp/