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Robert P. Davey

dblp:173/1959 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 2016
0000-0002-5589-7754ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 4 · 2 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
3 papers
Bioinformatics and computational biology · 100%

Topics — the 8 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › sequence analysis
nanopore sequencing
0.212016
NanoOK: multi-reference alignment analysis of nanopore sequencing data, quality and error profiles · Bioinform. 2016
Bioinformatics and computational biology
genomics
0.112010
TURNIP: tracking unresolved nucleotide polymorphisms in large hard-to-assemble regions of repetitive DNA sequence · Bioinform. 2010
Bioinformatics and computational biology › genomics
repetitive DNA analysis
0.112010
TURNIP: tracking unresolved nucleotide polymorphisms in large hard-to-assemble regions of repetitive DNA sequence · Bioinform. 2010
Bioinformatics and computational biology
metagenomics
0.112016
NanoOK: multi-reference alignment analysis of nanopore sequencing data, quality and error profiles · Bioinform. 2016
Bioinformatics and computational biology
phylogenetics
0.112007
MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets · Bioinform. 2007
Bioinformatics and computational biology › phylogenetics
phylogenetic inference
0.112007
MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets · Bioinform. 2007
Bioinformatics and computational biology
comparative genomics
0.012007
MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets · Bioinform. 2007
Bioinformatics and computational biology › gene expression analysis
microarray data analysis
0.012007
MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets · Bioinform. 2007

Methods — techniques the papers use, named apart from their topics

multi-reference alignment · 0.2sequence alignment · 0.1perl scripting · 0.1phylogenetic network construction · 0.1java · 0.1
YearPublicationVenuePosition
2016 NanoOK: multi-reference alignment analysis of nanopore sequencing data, quality and error profiles
abstract
MOTIVATION: The Oxford Nanopore MinION sequencer, currently in pre-release testing through the MinION Access Programme (MAP), promises long reads in real-time from an inexpensive, compact, USB device. Tools have been released to extract FASTA/Q from the MinION base calling output and to provide basic yield statistics. However, no single tool yet exists to provide comprehensive alignment-based quality control and error profile analysis--something that is extremely important given the speed with which the platform is evolving. RESULTS: NanoOK generates detailed tabular and graphical output plus an in-depth multi-page PDF report including error profile, quality and yield data. NanoOK is multi-reference, enabling detailed analysis of metagenomic or multiplexed samples. Four popular Nanopore aligners are supported and it is easily extensible to include others. AVAILABILITY AND IMPLEMENTATION: NanoOK is an open-source software, implemented in Java with supporting R scripts. It has been tested on Linux and Mac OS X and can be downloaded from https://github.com/TGAC/NanoOK. A VirtualBox VM containing all dependencies and the DH10B read set used in this article is available from http://opendata.tgac.ac.uk/nanook/. A Docker image is also available from Docker Hub--see program documentation https://documentation.tgac.ac.uk/display/NANOOK. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Richard M. Leggett, Darren Heavens, Mario Cáccamo, Matthew D. Clark, Robert P. Davey
Bioinform.5
2016 CerealsDB 3.0: expansion of resources and data integration
abstract
BACKGROUND: The increase in human populations around the world has put pressure on resources, and as a consequence food security has become an important challenge for the 21st century. Wheat (Triticum aestivum) is one of the most important crops in human and livestock diets, and the development of wheat varieties that produce higher yields, combined with increased resistance to pests and resilience to changes in climate, has meant that wheat breeding has become an important focus of scientific research. In an attempt to facilitate these improvements in wheat, plant breeders have employed molecular tools to help them identify genes for important agronomic traits that can be bred into new varieties. Modern molecular techniques have ensured that the rapid and inexpensive characterisation of SNP markers and their validation with modern genotyping methods has produced a valuable resource that can be used in marker assisted selection. CerealsDB was created as a means of quickly disseminating this information to breeders and researchers around the globe. DESCRIPTION: CerealsDB version 3.0 is an online resource that contains a wide range of genomic datasets for wheat that will assist plant breeders and scientists to select the most appropriate markers for use in marker assisted selection. CerealsDB includes a database which currently contains in excess of a million putative varietal SNPs, of which several hundreds of thousands have been experimentally validated. In addition, CerealsDB also contains new data on functional SNPs predicted to have a major effect on protein function and we have constructed a web service to encourage data integration and high-throughput programmatic access. CONCLUSION: CerealsDB is an open access website that hosts information on SNPs that are considered useful for both plant breeders and research scientists. The recent inclusion of web services designed to federate genomic data resources allows the information on CerealsDB to be more fully integrated with the WheatIS network and other biological databases.
Paul A. Wilkinson, Mark O. Winfield, Gary Barker, Simon Tyrrell, Xingdong Bian, Alexandra M. Allen, Amanda Burridge, Jane A. Coghill, Christy Waterfall, Mario Cáccamo, Robert P. Davey, Keith J. Edwards
BMC Bioinform.11
2010 TURNIP: tracking unresolved nucleotide polymorphisms in large hard-to-assemble regions of repetitive DNA sequence
abstract
UNLABELLED: TURNIP comprises a suite of Perl scripts and modules that facilitates the resolution of microheterogeneity within hard-to-assemble repetitive DNA sequences. TURNIP was originally developed for the Saccharomyces Genome Resequencing Project (SGRP) within which the ribosomal DNA (rDNA) of 36 strains of S.cerevisiae were analysed to investigate the occurrence of potential polymorphisms. Here, 'partially resolved SNPs', or pSNPs, as well as indels, were found to be far more prevalent than previously suspected. More generally, the TURNIP software ascertains degrees of variation between large tandem repeats within a single locus, offering insights into mechanisms of genome stability and gene conversion in any organism for which genome sequence data are available. AVAILABILITY: The TURNIP source code, results files and online help are available at http://www.ncyc.co.uk/software/turnip.html.
Robert P. Davey, Stephen A. James, Jo L. Dicks, Ian N. Roberts
Bioinform.1
2007 MPP: a microarray-to-phylogeny pipeline for analysis of gene and marker content datasets
abstract
UNLABELLED: MPP is a Java application, encompassing both new and established algorithms, for the analysis of gene and marker content datasets arising from high-throughput microarray techniques. MPP analyses flat file output from microarray experiments to determine the probability of the presence or absence of genes or markers within a genome. MPP can construct gene or marker content datasets for a number of genomes and can use the data to estimate an evolutionary tree or network. Results from gene content analyses may be validated by comparing them to known gene contents. MPP was initially developed to analyse data derived from comparative genome hybridization (CGH) microarray experiments in fungi and bacteria. It has recently been adapted to analyse retrotransposon-based insertion polymorphism (RBIP) marker scores derived from tagged microarray marker (TAM) experiments in pea. New analytical procedures may be added easily to MPP as plugins in order to increase the scope of the software. AVAILABILITY: MPP source code, executables and online help are available at http://cbr.jic.ac.uk/dicks/software/
Robert P. Davey, George Savva, Jo L. Dicks, Ian N. Roberts
Bioinform.1