BOL: Related items

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/

AGORA: Algorithm for Gene Order Reconstruction in Ancestors

Jit — Mon, 28 Feb 2022 23:26:21 -0600

AGORA stands for “Algorithm for Gene Order Reconstruction in Ancestors” and was developed by Matthieu Muffato in the DYOGEN Laboratory at the École normale supérieure in Paris in 2008.

    // | |     //   ) )  //   ) ) //   ) )  // | |
   //__| |    //        //   / / //___/ /  //__| |
  / ___  |   //  ____  //   / / / ___ (   / ___  |
 //    | |  //    / / //   / / //   | |  //    | |
//     | | ((____/ / ((___/ / //    | | //     | |

AGORA is used to generate ancestral genomes for the Genomicus online server for gene order comparison, and has been in constant use in the group since.

Address of the bookmark: https://github.com/DyogenIBENS/Agora

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/

genoPlotR - plot gene and genome maps project!

Abhimanyu Singh — Wed, 12 Dec 2018 08:33:41 -0600

genoPlotR is a R package to produce reproducible, publication-grade graphics of gene and genome maps. It allows the user to read from usual format such as protein table files and blast results, as well as home-made tabular files.

Features

Linear representation of several segments of DNA
Comparisons represented by areas between the segments (like Artemis, for example)
Reads from common formats: Genbank, EMBL, blast, Mauve, and from user-generated tab files
Plot several subsegments of the same segment on the same line, separated by a //
Automatic or manual placement of the segments on the plot
Add annotations to all the lines
Create smart, automatic annotations for genomes, based on gene names
Add a user-generated tree
Add a global scale or a scale to each line
Use user-defined graphical functions to represent genes

Address of the bookmark: http://genoplotr.r-forge.r-project.org/

HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers

Jit — Mon, 21 Jan 2019 06:50:05 -0600

A computational pipeline for genome-wide detection of putative horizontal gene transfer (HGT) events based on sequence homology search hit distribution statistics

Authors: Qiyun Zhu (qiyunzhu@gmail.com), Katharina Dittmar (katharinad@gmail.com)

Affiliation: Department of Biological Sciences, University at Buffalo, State University of New York, Buffalo, USA

Zhu Q, Kosoy M, Dittmar K. HGTector: an automated method facilitating genome-wide discovery of putative horizontal gene transfers. BMC Genomics. 2014. 15:717.

Usage: Simply execute perl HGTector.pl, or, open GUI.html in a web browser to see a step-by-step wizard.

Download HGTector 0.2.2.

Address of the bookmark: https://github.com/DittmarLab/HGTector

MAGIC: A tool for predicting transcription factors and cofactors driving gene sets using ENCODE data

BioStar — Thu, 26 Nov 2020 11:05:04 -0600

The algorithm presented herein, Mining Algorithm for GenetIc Controllers (MAGIC), uses ENCODE ChIP-seq data to look for statistical enrichment of TFs and cofactors in gene bodies and flanking regions in gene lists without an a priori binary classification of genes as targets or non-targets. When compared to other TF mining resources, MAGIC displayed favourable performance in predicting TFs and cofactors that drive gene changes in 4 settings:

1) A cell line expressing or lacking single TF,

2) Breast tumors divided along PAM50 designations

3) Whole brain samples from WT mice or mice lacking a single TF in a particular neuronal subtype

4) Single cell RNAseq analysis of neurons divided by Immediate Early Gene expression levels.

In summary, MAGIC is a standalone application that produces meaningful predictions of TFs and cofactors in transcriptomic experiments.

More at https://uwmadison.app.box.com/s/8j90e5h2rjrsz3bacaxnq8kor2o64vyg

Address of the bookmark: https://github.com/asroopra/MAGIC

Published: GeneSCF: a real-time based functional enrichment tool with support for multiple organisms

EagleEye — Mon, 19 Sep 2016 13:24:17 -0500

GeneSCF is more reliable compared to other enrichment tools because of its ability to use reference functional databases in real-time to perform enrichment analysis. It is an easy-to-integrate tool with other pipelines available for downstream analysis of high-throughput data. More importantly, GeneSCF can run multiple gene lists simultaneously on different organisms thereby saving time for the users. Since the tool is designed to be ready-to-use, there is no need for any complex compilation and installation procedures.

Access article:

http://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1250-z

BioDBnet

Jit — Thu, 02 Jun 2016 11:11:47 -0500

Database to Database Conversions

db2db allows for conversions of identifiers from one database to other database identifiers or annotations. To use db2db select the input type of your data, changing the input type automatically changes the output options to the ones specific for the input selected. Then select one or more output types and add your identifiers in the ID list box. Set the remove duplicate values to 'No' if you do not want duplicates to be removed. Clicking on submit then returns a table of your inputs matched against all the outputs selected in the exact order as entered. Results can be limited to a particular taxon by entering it's Taxon ID. The performance will vary widely depending on the number of outputs and the options selected. Conversions to a single output with the default options should complete in a few seconds

Address of the bookmark: https://biodbnet-abcc.ncifcrf.gov/db/db2db.php

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+