BOL: Related items

Machine Learning !!!

Gudiya Pal — Fri, 01 Jul 2016 12:57:12 -0500

In machine learning, computers apply statistical learning techniques to automatically identify patterns in data. These techniques can be used to make highly accurate predictions.

Keep scrolling. Using a data set about homes, we will create a machine learning model to distinguish homes in New York from homes in San Francisco.

Address of the bookmark: http://www.r2d3.us/visual-intro-to-machine-learning-part-1/

Ribbon !!

Jit — Fri, 21 Oct 2016 04:54:30 -0500

Visualization has played an extremely important role in the current genomic revolution to inspect and understand variants, expression patterns, evolutionary changes, and a number of other relationships. However, most of the information in read-to-reference or genome-genome alignments is lost for structural variations in the one-dimensional views of most genome browsers showing only reference coordinates. Instead, structural variations captured by long reads or assembled contigs often need more context to understand, including alignments and other genomic information from multiple chromosomes. We have addressed this problem by creating Ribbon (genomeribbon.com) an interactive online visualization tool that displays alignments along both reference and query sequences, along with any associated variant calls in the sample. This way Ribbon shows patterns in alignments of many reads across multiple chromosomes, while allowing detailed inspection of individual reads (Supplementary Note 1). For example, here we show a gene fusion in the SK-BR-3 breast cancer cell line linking the genes CYTH1 and EIF3H. While it has been found in the transcriptome previously, genome sequencing did not identify a direct chromosomal fusion between these two genes. After SMRT sequencing, Ribbon shows that there are indeed long reads that span from one gene to the other, going through not one but two variants, for the first time showing the genomic link between these two genes (Figure 1a). More gene fusions of this cancer cell line are investigated in Supplementary Note 2. Figure 1b shows another complex event in this sample made simple in Ribbon: the translocation of a 4.4 kb sequence deleted from chr19 and inserted into chr16 (Figure 1b). Thus, Ribbon enables understanding of complex variants, and it may also help in the detection of sequencing and sample preparation issues, testing of aligners and variant-callers, and rapid curation of structural variant candidates (Supplementary Note 3). In addition to SAM and BAM files with long, short, or paired-end reads, Ribbon can also load coordinate files from whole genome aligners such as MUMmer. Therefore, Ribbon can be used to test assembly algorithms or inspect the similarity between species. Supplementary Note 4 shows a comparison of gorilla and human genomes using Ribbon, highlighting major structural differences. In conclusion, Ribbon is a powerful interactive web tool for viewing complex genomic alignments.

Script at https://github.com/MariaNattestad/ribbon

Address of the bookmark: http://genomeribbon.com/

SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis

BioStar — Mon, 17 Aug 2020 05:21:09 -0500

SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, …).
The bioinformatics treatment is based on Vsearch [Rognes 2016] which showed to be both accurate and fast [Wescott 2015].The statistical analysis is based on DESeq2 R package [Anders and Huber 2010] which robustly identifies the differential abundant features as suggested in [McMurdie and Holmes 2014] and [Jonsson2016]. SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2 [Love 2014].
SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats. A presentation about SHAMAN is available here and a poster here.

More at https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-020-03666-4

Address of the bookmark: https://github.com/aghozlane/shaman

Osprey: Network Visualization System

BioJoker — Sun, 20 Jan 2019 05:34:24 -0600

Osprey is a software platform for the visualization of complex biological interaction networks. Osprey builds data-rich graphical representations from Gene Ontology (GO) annotated interaction data maintained by the BioGRID.

Osprey is developed by the TyersLab and is a part of the BioGRID family of software. It utilizes both MySQL and Java to operate and is compatible with Windows, Linux, and Apple operating systems.

These works were published in Breitkreutz, BJ., Stark, C., Tyers M. "Osprey: A Network Visualization System." Genome Biology 2003 4(3):R22 [Genome Biology] [PDF] [PubMed] and supported by the National Institutes of Health, Canadian Institutes of Health Research, and Genome Canada.

Address of the bookmark: https://osprey.thebiogrid.org/

List of visualization tools for network biology

Jit — Mon, 29 Jan 2018 05:12:24 -0600

Network analysis is any structured technique used to mathematically analyze a circuit (a “network” of interconnected components). The Network analysis provides the ability to quantify associations between individuals, which makes it possible to infer details about the network as a whole at the species and/or population level. Few tools published in BMC are listed here https://bmcbioinformatics.biomedcentral.com/articles/sections/networks-analysis.

Following are the list of standalone applications for network analysis:

Arena 3D

3D visualization of multi-layer networks

http://www.arena3d.org

Biana

Data integration and network management

http://sbi.imim.es/web/BIANA.php

BioLayout Express 3D

2D/3D network visualization

http://www.biolayout.org/

BiologicalNetworks

Efficient integrated multi-level analysis of microarray, sequence, regulatory and other data

http://www.biologicalnetworks.org

BioMiner

Modeling, analyzing and visualizing biochemical pathways and networks

http://www.zbi.uni-saarland.de/chair/projects/BioMiner

Cell Illustrator

Petri nets for modeling and simulating biological networks

http://www.cellillustrator.com

COPASI

Analysis of biochemical networks and their dynamics

http://www.copasi.org/

Cytoscape

Network visualization and analysis. Over 200 plugins [60]

http://www.cytoscape.org/

Dizzy

Chemical kinetics stochastic simulation software

http://magnet.systemsbiology.net/software/Dizzy/

DyCoNet

Gephi plugin that can be used to identify dynamic communities in networks

https://github.com/juliemkauffman/DyCoNet

GENeVis

Network and pathway visualization

http://tinyurl.com/genevis/

GEPHI

Interactive visualization and exploration for any network and complex system, dynamic and hierarchical graph.

https://gephi.org

Igraph

Collection of network analysis tools with the emphasis on efficiency, portability and ease of use

http://igraph.sourceforge.net

Medusa

Semantic and multi-edged simple networks

https://sites.google.com/site/medusa3visualization/

NAViGaTOR

Visualizing and analyzing protein-protein interaction networks

http://tinyurl.com/navigator1/

N-Browse

Interactive graphical browser for biological networks

http://www.gnetbrowse.org/

NeAT

Topological and clustering analysis of networks

http://rsat.ulb.ac.be/neat/

Ondex

Data integration and visualization of large networks

http://www.ondex.org/

Osprey

Visualization and annotation of biological networks

http://biodata.mshri.on.ca/osprey/servlet/Index

Pajek

Analysis and visualization of large networks and social network analysis

http://vlado.fmf.uni-lj.si/pub/networks/pajek/

PathwayAssist

Navigation and analysis of biological pathways, gene regulation networks and protein interaction maps.

http://www.ariadnegenomics.com/downloads/

PIVOT

Layout algorithms for visualizing protein interactions and families

http://acgt.cs.tau.ac.il/pivot/

ProCope

Prediction and evaluation of protein complexes from purification data experiments

http://www.bio.ifi.lmu.de/Complexes/ProCope/

ProViz

Visualization and exploration of interaction networks. Gene Ontology and PSI-MI formats supported

http://cbi.labri.fr/eng/proviz.htm

SpectralNET

Network analysis and visualizations. Scatter plots and dimensionality reduction algorithms

https://www.broadinstitute.org/software/spectralnet

Tulip

Enables the development of algorithms, visual encodings, interaction techniques, data models and domain-specific visualizations

http://tulip.labri.fr/TulipDrupal/

VANESA

Automatic reconstruction and analysis of biological networks and Petri nets based on life-science database information

http://agbi.techfak.uni-bielefeld.de/vanesa/

VANTED

Network reconstruction, data visualization, integration of various data types, network simulation

http://tinyurl.com/vanted/

yEd

Creation of diagrams manually and import external data

http://tinyurl.com/yEdGraph/

Web tools for network analysis

APID

Unified protein-protein interactions from BIND, BioGRID, DIP, HPRD, IntAct and MINT

http://bioinfow.dep.usal.es/apid/

Arcadia

Translates text-based descriptions of biological networks (SBML files) into standardized diagrams (Systems Biology Graphical Notation Process Description maps)

http://arcadiapathways.sourceforge.net/

AVIS

Viewer for signaling networks

http://actin.pharm.mssm.edu/AVIS2

bioPIXIE

Discovery of biological networks from diverse functional genomic data

http://pixie.princeton.edu/pixie

CellPublisher

Interactive representations of biochemical processes

http://cellpublisher.gobics.de/

Graphle

Distributed network exploration and visualization of interactive large, dense graphs

http://tinyurl.com/graphle/

GraphWeb

Web server for graph-based analysis of biological networks

http://biit.cs.ut.ee/graphweb/

Hubba

Web-based service to explore the essential nodes in a network

http://hub.iis.sinica.edu.tw/Hubba

NetworkBLAST

Analysis of protein interaction networks across species to infer protein complexes that are conserved in evolution

http://www.cs.tau.ac.il/~bnet/networkblast.htm

Pathview

Tool set for pathway-based data integration and visualization

http://Pathview.r-forge.r-project.org/

PINA

Integrated platform for protein interaction network construction, filtering, analysis, visualization and management

http://cbg.garvan.unsw.edu.au/pina/home.do

ReMatch

Web-based tool for integration of user-given stoichiometric metabolic models into a database collected from public data sources

http://www.cs.helsinki.fi/group/sysfys/software/rematch/

SNOW

Gene mapping on a reference or human protein-protein interaction network that SNOW hosts

http://snow.bioinfo.cipf.es

STITCH

Resource to explore known and predicted interactions of chemicals and proteins

http://stitch.embl.de/

STRING

Protein interaction networks and integration of data such as genomic context, high-throughput experiments, conserved coexpression and previous knowledge derived from the literature

http://string-db.org

TVNViewer

An interactive visualization tool for exploring networks that change over time or space

http://www.sailing.cs.cmu.edu/main/?page_id=545

tYNA

System for managing, comparing and mining multiple networks

http://tyna.gersteinlab.org/tyna/

VisANT

Visualization, mining, analysis and modeling of biological networks, metabolic networks and ecosystems

http://visant.bu.edu/

Circos visualization !

BioStar — Mon, 06 Mar 2023 06:01:32 -0600

Circos visualization

https://wlcb.oit.uci.edu/modules/index.html

Address of the bookmark: https://wlcb.oit.uci.edu/NG-Circos

A web-based tool for sequence alignment statistics and innovative visualization

BioStar — Thu, 04 Apr 2024 01:44:50 -0500

AlignStatPlot, a new R package and online tool that is well-documented and easy-to usefor MSA and post-MSA analysis. This tool performs both traditional and cutting-edge analy-ses on sequencing data and generates new visualisation methods for MSA results. Whencompared to currently available tools, AlignStatPlot provides a robust ability to handle andvisualise diversity data, while the online version will save time and encourage researchersto focus on explaining their findings. It is a simple tool that can be used in conjunction withpopulation genetics software (PDF) AlignStatPlot: An R package and online tool for robust sequence alignment statistics and innovative visualization of big data.

Address of the bookmark: https://bioinformatics.um6p.ma/AlignStatPlot/

You and your friend have similar DNA !!!

Jit — Sun, 27 Jul 2014 20:44:05 -0500

New research out of Massachusetts claims that people often choose friends that are similar to them in genetics and they are more accurate than you might suppose. A study published on PNAS http://www.pnas.org/content/111/Supplement_3/10796.full found that people are apt to pick friends who are genetically similar to themselves - so much so that friends tend to be as alike at the genetic level as a person's fourth cousin.

Scientists with a long-running Framingham Heart Study looked at 1,932 people (examination of about 1.5 million markers of genetic variations), comparing unrelated friends to unrelated strangers. They found that friends shared about 1% of their genes — a percentage much higher than those shared with strangers.This new findings made it clear that people have more DNA in common with those who are selected as friends than with strangers in the same population.

The genes that lined up the most were olfactory genes, which deal with smell. The ones that lined up the least were immune system genes. The researchers weren't sure why that happened :/. Olfactory genes might be a straightforward explanation: People who like the same smells tend to be drawn to similar environments, where they meet others with the same tendencies.

Reference:

http://www.pnas.org/content/111/Supplement_3/10796.full

Image : http://i.kinja-img.com

A5-miseq

Jit — Thu, 18 Aug 2016 04:05:23 -0500

_A5-miseq_ is a pipeline for assembling DNA sequence data generated on the Illumina sequencing platform. This README will take you through the steps necessary for running _A5-miseq_.

Point to note:

There are many situations where A5-miseq is not the right tool for the job. In order to produce accurate results, A5-miseq requires Illumina data with certain characteristics. A5-miseq will likely not work well with Illumina reads shorter than around 80nt, or reads where the base qualities are low in all or most reads before 60nt. A5-miseq assumes it is assembling homozygous haploid genomes. Use a different assembler for metagenomes and heterozygous diploid or polyploid organisms. Use a different assembler if a tool like FastQC reports your data quality is dubious. You have been warned! Datasets consisting solely of unpaired reads are not currently supported.

Address of the bookmark: https://sourceforge.net/projects/ngopt/

MEGAN6

Neel — Mon, 25 Jul 2016 05:45:22 -0500

Microbiome analysis using a single application

MEGAN6 is a comprehensive toolbox for interactively analyzing microbiome data. All the interactive tools you need in one application.

Taxonomic analysis using the NCBI taxonomy or a customized taxonomy such as SILVA
Functional analysis using InterPro2GO, SEED, eggNOG or KEGG
Bar charts, word clouds, Voronoi tree maps and many other charts
PCoA, clustering and networks
Supports metadata
MEGAN parses many different types of input

Why use MEGAN6?

The software is:

Easy to use. MEGAN6 is a single application and all features are available through menus, toolbars and graphics. No scripting skills required.
Powerful. MEGAN6 allows you to work with hundreds of samples containing hundreds of millions of sequencing reads. Blast-like analysis can be performed using DIAMOND.
Comprehensive. MEGAN6 offers a large range of analysis tools, and is under active development.

Address of the bookmark: https://ab.inf.uni-tuebingen.de/software/megan6