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Anthony P. Fejes

dblp:82/5293 · DBLP profile ↗
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5ranked-venue papers
2as first author
0since 2021 · last 2018
0009-0006-8360-8418ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 5 · 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
2 papers
Bioinformatics and computational biology · 100%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › biological database
genetic variation database
0.112011
Human variation database: an open-source database template for genomic discovery · Bioinform. 2011
Bioinformatics and computational biology › epigenomics
ChIP-seq analysis
0.112008
FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology · Bioinform. 2008
Bioinformatics and computational biology
genomics
0.112008
FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology · Bioinform. 2008
Bioinformatics and computational biology › epigenomics › ChIP-seq analysis
peak calling
0.112008
FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology · Bioinform. 2008
Bioinformatics and computational biology › gene regulation
transcription factor binding site prediction
0.112008
FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology · Bioinform. 2008

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

relational database design · 0.1statistical enrichment analysis · 0.1hidden markov model · 0.1
YearPublicationVenuePosition
2018 The VAAST Variant Prioritizer (VVP): ultrafast, easy to use whole genome variant prioritization tool
abstract
BACKGROUND: Prioritization of sequence variants for diagnosis and discovery of Mendelian diseases is challenging, especially in large collections of whole genome sequences (WGS). Fast, scalable solutions are needed for discovery research, for clinical applications, and for curation of massive public variant repositories such as dbSNP and gnomAD. In response, we have developed VVP, the VAAST Variant Prioritizer. VVP is ultrafast, scales to even the largest variant repositories and genome collections, and its outputs are designed to simplify clinical interpretation of variants of uncertain significance. RESULTS: We show that scoring the entire contents of dbSNP (> 155 million variants) requires only 95 min using a machine with 4 cpus and 16 GB of RAM, and that a 60X WGS can be processed in less than 5 min. We also demonstrate that VVP can score variants anywhere in the genome, regardless of type, effect, or location. It does so by integrating sequence conservation, the type of sequence change, allele frequencies, variant burden, and zygosity. Finally, we also show that VVP scores are consistently accurate, and easily interpreted, traits not shared by many commonly used tools such as SIFT and CADD. CONCLUSIONS: VVP provides rapid and scalable means to prioritize any sequence variant, anywhere in the genome, and its scores are designed to facilitate variant interpretation using ACMG and NHS guidelines. These traits make it well suited for operation on very large collections of WGS sequences.
Steven Flygare, Edgar Javier Hernandez, Lon Phan, Barry Moore, Anthony P. Fejes, Karen Eilbeck, Chad D. Huff, Lynn Jorde, Martin G. Reese, Mark Yandell
BMC Bioinform.6
2013 Identifying cancer mutation targets across thousands of samples: MuteProc, a high throughput mutation analysis pipeline
abstract
BACKGROUND: In the past decade, bioinformatics tools have matured enough to reliably perform sophisticated primary data analysis on Next Generation Sequencing (NGS) data, such as mapping, assemblies and variant calling, however, there is still a dire need for improvements in the higher level analysis such as NGS data organization, analysis of mutation patterns and Genome Wide Association Studies (GWAS). RESULTS: We present a high throughput pipeline for identifying cancer mutation targets, capable of processing billions of variations across thousands of samples. This pipeline is coupled with our Human Variation Database to provide more complex down stream analysis on the variations hosted in the database. Most notably, these analysis include finding significantly mutated regions across multiple genomes and regions with mutational preferences within certain types of cancers. The results of the analysis is presented in HTML summary reports that incorporate gene annotations from various resources for the reported regions. CONCLUSION: MuteProc is available for download through the Vancouver Short Read Analysis Package on Sourceforge: http://vancouvershortr.sourceforge.net. Instructions for use and a tutorial are provided on the accompanying wiki pages at https://sourceforge.net/apps/mediawiki/vancouvershortr/index.php?title=Pipeline_introduction.
Alireza Hadj Khodabakhshi, Anthony P. Fejes, Inanç Birol, Steven J. M. Jones
BMC Bioinform.2
2011 Human variation database: an open-source database template for genomic discovery
abstract
MOTIVATION: Current public variation databases are based upon collaboratively pooling data into a single database with a single interface available to the public. This gives little control to the collaborator to mine the database and requires that they freely share their data with the owners of the repository. We aim to provide an alternative mechanism: providing the source code and application programming interface (API) of a database, enabling researchers to set up local versions without investing heavily in the development of the resource and allowing for confidential information to remain secure. RESULTS: We describe an open-source database that can be installed easily at any research facility for the storage and analysis of thousands of next-generation sequencing variations. This database is built using PostgreSQL 8.4 (The PostgreSQL Global Development Group. postgres 8.4: http://www.postgresql.org) and provides a novel method for collating and searching across the reported results from thousands of next-generation sequence samples, as well as rapidly accessing vital information on the origin of the samples. The schema of the database makes rapid and insightful queries simple and enables easy annotation of novel or known genetic variations. A modular and cross-platform Java API is provided to perform common functions, such as generation of standard experimental reports and graphical summaries of modifications to genes. Included libraries allow adopters of the database to quickly develop their own queries. AVAILABILITY: The software is available for download through the Vancouver Short Read Analysis Package on Sourceforge, http://vancouvershortr.sourceforge.net. Instructions for use and deployment are provided on the accompanying wiki pages. CONTACT: [email protected].
Anthony P. Fejes, Alireza Hadj Khodabakhshi, Inanç Birol, Steven J. M. Jones
Bioinform.1
2010 Genomic analysis of a rare human tumor
abstract
The introduction of next-generation DNA sequencing devices into the field of oncology provides an unprecedented mechanism to determine the underlying genetic changes that have occurred within a tumor and also the changes that accrue during treatment. An enhanced understanding of the oncogenic mechanisms could have an immediate clinical role in the treatment of rare tumors - where treatment protocols do not exist and their rarity would indicate that clinical trials would be unlikely to be undertaken for their establishment. We have investigated the utility of massively parallel sequencing to characterize a rare adenocarcinoma of the tongue, before and after treatment. In the pre-treatment tumor we identified 7,629 genes within regions of copy number gain, 1,078 genes exhibited increased expression relative to the blood and unrelated tumors and four genes contained somatic protein-coding mutations. Our analysis suggested the tumor cells were driven by the RET oncogene and its other pathway constituents. Genes whose protein products are targeted by the RET inhibitors sunitinib and sorafenib correlated with being amplified and or highly expressed. Consistent with our observations subsequent administration of sunitinib was associated with stable disease lasting 4 months, after which the lung lesions began to grow. Administration of sorafenib and sulindac provided disease stabilization for an additional 3 months after which the cancer progressed and new lesions appeared. A metastasis recurring in the skin was determined to possess 7,288 genes within copy number amplicons, 385 genes exhibiting increased expression relative to other tumours and 9 new somatic protein coding mutations. The observed mutations and amplifications were found to be consistent with resistance to therapy arising through further activation of RET pathway and nascent activation of the AKT pathway. Our results provide evidence for the clinical utility of complete genomic characterization and direct in-vivo genome-wide characterization of the mutations accruing within a tumor under drug selection.
Steven J. M. Jones, Janessa Laskin, Yvonne Y. Li, Obi L. Griffith, Jianghong An, Mikhail Bilenky, Yaron S. N. Butterfield, Timothee Cezard, Eric Chuah, Richard Corbett, Anthony P. Fejes, Malachi Griffith, John Yee, Montgomery Martin, Michael Mayo, Nataliya Melnyk, Ryan D. Morin, Trevor J. Pugh, Tesa Severson, Sohrab P. Shah, Margaret Sutcliffe, Angela Tam, Jefferson Terry, Nina Thiessen, Thomas Thomson, Richard Varhol, Thomas Zeng 0002, Yongjun Zhao 0002, Richard A. Moore, David G. Huntsman, Inanç Birol, Martin Hirst, Robert A. Holt, Marco A. Marra
BMC Bioinform.11
2008 FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology
abstract
SUMMARY: Next-generation sequencing can provide insight into protein-DNA association events on a genome-wide scale, and is being applied in an increasing number of applications in genomics and meta-genomics research. However, few software applications are available for interpreting these experiments. We present here an efficient application for use with chromatin-immunoprecipitation (ChIP-Seq) experimental data that includes novel functionality for identifying areas of gene enrichment and transcription factor binding site locations, as well as for estimating DNA fragment size distributions in enriched areas. The FindPeaks application can generate UCSC compatible custom 'WIG' track files from aligned-read files for short-read sequencing technology. The software application can be executed on any platform capable of running a Java Runtime Environment. Memory requirements are proportional to the number of sequencing reads analyzed; typically 4 GB permits processing of up to 40 million reads. AVAILABILITY: The FindPeaks 3.1 package and manual, containing algorithm descriptions, usage instructions and examples, are available at http://www.bcgsc.ca/platform/bioinfo/software/findpeaks Source files for FindPeaks 3.1 are available for academic use.
Anthony P. Fejes, Gordon Robertson, Mikhail Bilenky, Richard Varhol, Matthew N. Bainbridge, Steven J. M. Jones
Bioinform.1