BOL: Related items

CLgenomics

Radha Agarkar — Fri, 03 Mar 2017 09:57:28 -0600

CLgenomics is a standalone desktop software specifically designed for bacterial genome analysis. This program has a powerful multi-genome browser, which enables rapid and responsive exploration of bacterial genomes.

To use CLgenomics, individual genome data (genome sequences + annotation details) are compiled and saved in a specially formatted file called CLG (ChunLab Genomics). Each CLG file corresponds with one bacterial genome. If multiple genomes are being considered and compared, multiple CLG files are needed. ChunLab offers >40,000 CLG files of publicly available Bacterial and Archaeal genomes.

Address of the bookmark: https://chunlab.wordpress.com/clgenomics-software/

CONCOCT: Clustering cONtigs with COverage and ComposiTion

Jit — Mon, 06 Mar 2017 04:08:16 -0600

A program for unsupervised binning of metagenomic contigs by using nucleotide composition, coverage data in multiple samples and linkage data from paired end reads.

Warning! This software is to be considered under development. Functionality and the user interface may still change significantly from one version to another. If you want to use this software, please stay up to date with the list of known issues:https://github.com/BinPro/CONCOCT/issues

Address of the bookmark: https://github.com/BinPro/CONCOCT

SeqMule: Automated human exome/genome variants detection

Abhimanyu Singh — Tue, 07 Mar 2017 10:12:36 -0600

SeqMule takes single-end or paird-end FASTQ or BAM files, generates a script consisting of more than 10 popular alignment, analysis tools and runs the script line by line. Users can change the pipeline or fine-tune the parameters by modifying its configuration file. SeqMule also has some built-in functions, such as pooling consensus calls from various callers, plotting a Venn diagram showing intersection among different callers, and downloading databases. SeqMule can be used for both Mendelian disease study and cancer genome study.

Address of the bookmark: http://seqmule.openbioinformatics.org/en/latest/

UpSetR Shiny App!

Jit — Fri, 14 Apr 2017 06:19:54 -0500

UpSetR generates static UpSet plots. The UpSet technique visualizes set intersections in a matrix layout and introduces aggregates based on groupings and queries. The matrix layout enables the effective representation of associated data, such as the number of elements in the aggregates and intersections, as well as additional summary statistics derived from subset or element attributes.

To begin, input your data using one of the three input styles.

"File" takes a correctly formatted.csv file.
"List" takes up to 6 different lists that contain unique elements, similar to that used in the web applications BioVenn (Hulsen et al., 2008) and jvenn (Bardou et al., 2014)
"Expression" takes the input used by the venneuler R package (Wilkinson, 2015)

Address of the bookmark: https://gehlenborglab.shinyapps.io/upsetr/

CLA: Contig-Layout-Authenticator

Jit — Fri, 05 May 2017 05:58:36 -0500

To improve upon the shortcomings associated with the construction of draft genomes with Illumina paired-end sequencing, we developed Contig-Layout-Authenticator (CLA). The CLA pipeline can scaffold reference-sorted contigs based on paired reads, resulting in better assembled genomes. Moreover, CLA also hints at probable misassemblies and contaminations, for the users to cross-check before constructing the consensus draft. The CLA pipeline was designed and trained extensively on various bacterial genome datasets for the ordering and scaffolding of large repetitive contigs. The tool has been validated and compared favorably with other widely-used scaffolding and ordering tools using both simulated and real sequence datasets. CLA is a user friendly tool that requires a single command line input to generate ordered scaffolds.

Script https://sourceforge.net/projects/c-l-authenticator/files/

Address of the bookmark: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0155459

Synteny Portal: a web-based application portal for synteny block analysis

Jit — Wed, 24 May 2017 10:39:23 -0500

Synteny Portal, a versatile web-based application portal for constructing, visualizing and browsing synteny blocks. With Synteny Portal, users can easily (i) construct synteny blocks among multiple species by using prebuilt alignments in the UCSC genome browser database, (ii) visualize and download syntenic relationships as high-quality images, (iii) browse synteny blocks with genetic information and (iv) download the details of synteny blocks to be used as input for downstream synteny-based analyses, all in an intuitive and easy-to-use web-based interface. We believe that Synteny Portal will serve as a highly valuable tool that will enable biologists to easily perform comparative genomics studies by compensating limitations of existing tools. Synteny Portal is freely available at http://bioinfo.konkuk.ac.kr/synteny_portal.

http://bioinfo.konkuk.ac.kr/synteny_portal/

Address of the bookmark: http://bioinfo.konkuk.ac.kr/synteny_portal/

NAViGaTOR: Network Analysis, Visualization and Graphing Toronto

Rahul Nayak — Tue, 03 Jul 2018 05:05:55 -0500

NAViGaTOR – Network Analysis, Visualization, & Graphing TORonto is a software system for scaleable visualizing and analyzing networks. The current version, NAViGaTOR 3, increases modularity, improves scaleability, extends input/output options, brings new network views and analysis algorithms. http://142.150.188.236/navigatorwp/

Address of the bookmark: http://142.150.188.236/navigatorwp/

RAVEN: a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models

Jit — Wed, 24 Oct 2018 22:38:05 -0500

The RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox 2 is a software suite for Matlab that allows for semi-automated reconstruction of genome-scale models (GEMs). It makes use of published models and/or KEGG, MetaCyc databases, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology.

Address of the bookmark: https://github.com/SysBioChalmers/RAVEN

ShinyGO v0.61: Gene Ontology Enrichment Analysis + more

Jit — Wed, 03 Jun 2020 08:00:30 -0500

2/3/2020: Now published by Bioinformatics.

11/3/2019: V 0.61, Improve graphical visualization (thanks to reviewers). Interactive networks and much more.

5/20/2019: V.0.60, Annotation database updated to Ensembl 96. New bacterial and fungal genomes based on STRING-db! Just paste your gene list to get enriched GO terms and othe pathways for over 315 plant and animal species, based on annotation from Ensembl (Release 96), Ensembl plants (R. 43) and Ensembl Metazoa (R. 43). An additional 2031 genomes (including bacteria and fungi) are annotated based on STRING-db (v.10). In addition, it also produces KEGG pathway diagrams with your genes highlighted, hierarchical clustering trees and networks summarizing overlapping terms/pathways, protein-protein interaction networks, gene characterristics plots, and enriched promoter motifs.

Address of the bookmark: http://bioinformatics.sdstate.edu/go/

Understanding GO analysis

Neel — Wed, 08 Feb 2023 04:22:01 -0600

The confusion about gene ontology and gene ontology analysis can start right from the term itself. There are actually two different entities that are commonly referred to as gene ontology or “GO”:

the ontology itself, which is a set of terms with their precise definitions and defined relationships between them, and
the associations between gene products and GO terms, which are used to capture the existing knowledge about what each gene is known to do.

But the term gene ontology, or GO, is commonly used to refer to both, which is sometimes a source of potential confusion. In order to avoid this, here we will use the term “GO ontology” to describe the set of terms and their hierarchical structure and “GO annotations” to describe the set of associations between genes and GO terms.

There are 3 types of terms, or domains if you wish, in the gene ontology:

Biological Processes (BP)
Molecular Functions (MF)
Cellular Components (CC)

Address of the bookmark: https://advaitabio.com/faq-items/understanding-gene-ontology/