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Dive into the research topics where Anil Thanki is active.

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Featured researches published by Anil Thanki.


F1000Research | 2014

BioJS: an open source standard for biological visualisation - its status in 2014.

Manuel Corpas; Rafael C. Jimenez; Seth Carbon; Alexander Garcia; Leyla Garcia; Tatyana Goldberg; John Gomez; Alexis Kalderimis; Suzanna E. Lewis; Ian Mulvany; Aleksandra Pawlik; Francis Rowland; Gustavo A. Salazar; Fabian Schreiber; Ian Sillitoe; William H Spooner; Anil Thanki; Jose M. Villaveces; Guy Yachdav; Henning Hermjakob

BioJS is a community-based standard and repository of functional components to represent biological information on the web. The development of BioJS has been prompted by the growing need for bioinformatics visualisation tools to be easily shared, reused and discovered. Its modular architecture makes it easy for users to find a specific functionality without needing to know how it has been built, while components can be extended or created for implementing new functionality. The BioJS community of developers currently provides a range of functionality that is open access and freely available. A registry has been set up that categorises and provides installation instructions and testing facilities at http://www.ebi.ac.uk/tools/biojs/. The source code for all components is available for ready use at https://github.com/biojs/biojs.


eLife | 2015

Anatomy of BioJS, an open source community for the life sciences

Guy Yachdav; Tatyana Goldberg; Sebastian Wilzbach; David Dao; Iris Shih; Saket Choudhary; Steve Crouch; Max Franz; Alexander Garcia; Leyla Garcia; Björn Grüning; Devasena Inupakutika; Ian Sillitoe; Anil Thanki; Bruno Vieira; Jose M. Villaveces; Maria Victoria Schneider; Suzanna E. Lewis; Steve Pettifer; Burkhard Rost; Manuel Corpas

BioJS is an open source software project that develops visualization tools for different types of biological data. Here we report on the factors that influenced the growth of the BioJS user and developer community, and outline our strategy for building on this growth. The lessons we have learned on BioJS may also be relevant to other open source software projects. DOI: http://dx.doi.org/10.7554/eLife.07009.001


F1000Research | 2013

StatsDB: platform-agnostic storage and understanding of next generation sequencing run metrics

Ricardo H. Ramirez-Gonzalez; Richard M. Leggett; Darren Waite; Anil Thanki; Nizar Drou; Mario Caccamo; Robert Davey

Modern sequencing platforms generate enormous quantities of data in ever-decreasing amounts of time. Additionally, techniques such as multiplex sequencing allow one run to contain hundreds of different samples. With such data comes a significant challenge to understand its quality and to understand how the quality and yield are changing across instruments and over time. As well as the desire to understand historical data, sequencing centres often have a duty to provide clear summaries of individual run performance to collaborators or customers. We present StatsDB, an open-source software package for storage and analysis of next generation sequencing run metrics. The system has been designed for incorporation into a primary analysis pipeline, either at the programmatic level or via integration into existing user interfaces. Statistics are stored in an SQL database and APIs provide the ability to store and access the data while abstracting the underlying database design. This abstraction allows simpler, wider querying across multiple fields than is possible by the manual steps and calculation required to dissect individual reports, e.g. ”provide metrics about nucleotide bias in libraries using adaptor barcode X, across all runs on sequencer A, within the last month”. The software is supplied with modules for storage of statistics from FastQC, a commonly used tool for analysis of sequence reads, but the open nature of the database schema means it can be easily adapted to other tools. Currently at The Genome Analysis Centre (TGAC), reports are accessed through our LIMS system or through a standalone GUI tool, but the API and supplied examples make it easy to develop custom reports and to interface with other packages.


The Plant Genome | 2016

transPLANT Resources for Triticeae Genomic Data

Manuel Spannagl; Michael Alaux; Matthias Lange; Daniel M. Bolser; Kai Christian Bader; Thomas Letellier; Erik Kimmel; Raphael Flores; Cyril Pommier; Arnaud Kerhornou; Brandon Walts; Thomas Nussbaumer; Christoph Grabmüller; Jinbo Chen; Christian Colmsee; Sebastian Beier; Martin Mascher; Thomas Schmutzer; Daniel Arend; Anil Thanki; Ricardo H. Ramirez-Gonzalez; Martin Ayling; Sarah Ayling; Mario Caccamo; Klaus F. X. Mayer; Uwe Scholz; Delphine Steinbach; Hadi Quesneville; Paul J. Kersey

The genome sequences of many important Triticeae species, including bread wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.), remained uncharacterized for a long time because their high repeat content, large sizes, and polyploidy. As a result of improvements in sequencing technologies and novel analyses strategies, several of these have recently been deciphered. These efforts have generated new insights into Triticeae biology and genome organization and have important implications for downstream usage by breeders, experimental biologists, and comparative genomicists. transPLANT (http://www.transplantdb.eu) is an EU‐funded project aimed at constructing hardware, software, and data infrastructure for genome‐scale research in the life sciences. Since the Triticeae data are intrinsically complex, heterogenous, and distributed, the transPLANT consortium has undertaken efforts to develop common data formats and tools that enable the exchange and integration of data from distributed resources. Here we present an overview of the individual Triticeae genome resources hosted by transPLANT partners, introduce the objectives of transPLANT, and outline common developments and interfaces supporting integrated data access.


GigaScience | 2018

GeneSeqToFamily: a Galaxy workflow to find gene families based on the Ensembl Compara GeneTrees pipeline

Anil Thanki; Nicola Soranzo; Wilfried Haerty; Robert Davey

Abstract Background Gene duplication is a major factor contributing to evolutionary novelty, and the contraction or expansion of gene families has often been associated with morphological, physiological, and environmental adaptations. The study of homologous genes helps us to understand the evolution of gene families. It plays a vital role in finding ancestral gene duplication events as well as identifying genes that have diverged from a common ancestor under positive selection. There are various tools available, such as MSOAR, OrthoMCL, and HomoloGene, to identify gene families and visualize syntenic information between species, providing an overview of syntenic regions evolution at the family level. Unfortunately, none of them provide information about structural changes within genes, such as the conservation of ancestral exon boundaries among multiple genomes. The Ensembl GeneTrees computational pipeline generates gene trees based on coding sequences, provides details about exon conservation, and is used in the Ensembl Compara project to discover gene families. Findings A certain amount of expertise is required to configure and run the Ensembl Compara GeneTrees pipeline via command line. Therefore, we converted this pipeline into a Galaxy workflow, called GeneSeqToFamily, and provided additional functionality. This workflow uses existing tools from the Galaxy ToolShed, as well as providing additional wrappers and tools that are required to run the workflow. Conclusions GeneSeqToFamily represents the Ensembl GeneTrees pipeline as a set of interconnected Galaxy tools, so they can be run interactively within the Galaxys user-friendly workflow environment while still providing the flexibility to tailor the analysis by changing configurations and tools if necessary. Additional tools allow users to subsequently visualize the gene families produced by the workflow, using the Aequatus.js interactive tool, which has been developed as part of the Aequatus software project.


bioRxiv | 2016

Aequatus: An open-source homology browser

Anil Thanki; Sarah Ayling; Javier Herrero; Robert Davey

Background: The phylogenetic information inferred from the study of homologous genes helps us to understand the evolution of gene families. The study of homology plays a vital role in finding ancestral gene duplication events as well as identifying regions that are under positive selection within species. Conservation of homologous loci results in syntenic blocks, and there are various tools available to visualise syntenic information between species. These tools provide an overview of syntenic regions as a whole, reaching down to the gene level, but none provide any information about structural changes within genes such as the conservation of ancestral exon boundaries amongst multiple genomes. Findings: We present Aequatus, a standalone web-based tool that provides an in-depth view of gene structure across gene families, with various options to render and filter visualisations. It relies on pre-calculated alignment and gene feature information held in an Ensembl database, typically generated through the Ensembl Compara workflow. We also offer Aequatus.js, a reusable JavaScript module that fulfils the visualisation aspects of Aequatus. Availability: Aequatus is an open-source tool freely available to download under GPLv3 license at https://github.com/TGAC/Aequatus and a demo is available at http://aequatus.tgac.ac.uk Contact: [email protected] and [email protected]


Bioinformatics | 2018

ViCTree: an automated framework for taxonomic classification from protein sequences

Sejal Modha; Anil Thanki; Susan F. Cotmore; Andrew J. Davison; Joseph Hughes

Motivation The increasing rate of submission of genetic sequences into public databases is providing a growing resource for classifying the organisms that these sequences represent. To aid viral classification, we have developed ViCTree, which automatically integrates the relevant sets of sequences in NCBI GenBank and transforms them into an interactive maximum likelihood phylogenetic tree that can be updated automatically. ViCTree incorporates ViCTreeView, which is a JavaScript‐based visualization tool that enables the tree to be explored interactively in the context of pairwise distance data. Results To demonstrate utility, ViCTree was applied to subfamily Densovirinae of family Parvoviridae. This led to the identification of six new species of insect virus. Availability and implementation ViCTree is open‐source and can be run on any Linux‐ or Unix‐based computer or cluster. A tutorial, the documentation and the source code are available under a GPL3 license, and can be accessed at http://bioinformatics.cvr.ac.uk/victree_web/.


F1000Research | 2014

wigExplorer , a BioJS component to visualise wig data

Anil Thanki; Rafael C. Jimenez; Gemy Kaithakottil; Manuel Corpas; Robert Davey

Summary: wigExplorer is a BioJS component whose main purpose is to provide a platform for visualisation of wig-formatted data. Wig files are extensively used by genome browsers such as the UCSC Genome Browser. wigExplorer follows the BioJS standard specification, requiring a simple configuration and installation. wigExplorer provides an easy way to navigate the visible region of the canvas and allows interaction with other components via predefined events. Availability: http://biojs.io/d/biojs-vis-wigexplorer ; http://dx.doi.org/10.5281/zenodo.8516


Archive | 2015

Anatomy of BioJS, an open source community for the life

Guy Yachdav; Tatyana Goldberg; Sebastian Wilzbach; David Dao; Iris Shih; Saket Choudhary; Steve Crouch; Max Franz; Devasena Inupakutika; Ian Sillitoe; Anil Thanki; Bruno Vieira; E M Villaveces; Maria Victoria Schneider; Suzanna E. Lewis; Steve Pettifer; Burkhard Rost; Manuel Corpas


F1000Research | 2013

TGAC Browser: visualisation solutions for big data in the genomic era

Anil Thanki; Xingdong Bian; Robert Davey

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Ian Sillitoe

University College London

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Suzanna E. Lewis

Lawrence Berkeley National Laboratory

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Javier Herrero

University College London

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