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Dive into the research topics where Bret Barnes is active.

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Featured researches published by Bret Barnes.


Genomics | 2011

High density DNA methylation array with single CpG site resolution

Marina Bibikova; Bret Barnes; Chan Tsan; Vincent Ho; Brandy Klotzle; Jennie M. Le; David Delano; Lu Zhang; Gary P. Schroth; Kevin L. Gunderson; Jian-Bing Fan; Richard Shen

We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R2 of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research.


Nucleic Acids Research | 2008

Highly sensitive and specific microRNA expression profiling using BeadArray technology

Jing Chen; Jean Lozach; Eliza Wickham Garcia; Bret Barnes; Shujun Luo; Ivan Mikoulitch; Lixin Zhou; Gary P. Schroth; Jian-Bing Fan

We have developed a highly sensitive, specific and reproducible method for microRNA (miRNA) expression profiling, using the BeadArray™ technology. This method incorporates an enzyme-assisted specificity step, a solid-phase primer extension to distinguish between members of miRNA families. In addition, a universal PCR is used to amplify all targets prior to array hybridization. Currently, assay probes are designed to simultaneously analyse 735 well-annotated human miRNAs. Using this method, highly reproducible miRNA expression profiles were generated with 100–200 ng total RNA input. Furthermore, very similar expression profiles were obtained with total RNA and enriched small RNA species (R2 ≥ 0.97). The method has a 3.5–4 log (105–109 molecules) dynamic range and is able to detect 1.2- to 1.3-fold-differences between samples. Expression profiles generated by this method are highly comparable to those obtained with RT–PCR (R2 = 0.85–0.90) and direct sequencing (R = 0.87–0.89). This method, in conjunction with the 96-sample array matrix should prove useful for high-throughput expression profiling of miRNAs in large numbers of tissue samples.


Bioinformatics | 2016

Manta: rapid detection of structural variants and indels for germline and cancer sequencing applications

Xiaoyu Chen; Ole Schulz-Trieglaff; Richard Shaw; Bret Barnes; Felix Schlesinger; Morten Källberg; Anthony J. Cox; Semyon Kruglyak; Christopher T. Saunders

UNLABELLED : We describe Manta, a method to discover structural variants and indels from next generation sequencing data. Manta is optimized for rapid germline and somatic analysis, calling structural variants, medium-sized indels and large insertions on standard compute hardware in less than a tenth of the time that comparable methods require to identify only subsets of these variant types: for example NA12878 at 50× genomic coverage is analyzed in less than 20 min. Manta can discover and score variants based on supporting paired and split-read evidence, with scoring models optimized for germline analysis of diploid individuals and somatic analysis of tumor-normal sample pairs. Call quality is similar to or better than comparable methods, as determined by pedigree consistency of germline calls and comparison of somatic calls to COSMIC database variants. Manta consistently assembles a higher fraction of its calls to base-pair resolution, allowing for improved downstream annotation and analysis of clinical significance. We provide Manta as a community resource to facilitate practical and routine structural variant analysis in clinical and research sequencing scenarios. AVAILABILITY AND IMPLEMENTATION Manta is released under the open-source GPLv3 license. Source code, documentation and Linux binaries are available from https://github.com/Illumina/manta. CONTACT [email protected] SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.


Journal of Clinical Microbiology | 2013

Survey of Culture, GoldenGate Assay, Universal Biosensor Assay, and 16S rRNA Gene Sequencing as Alternative Methods of Bacterial Pathogen Detection

Brianna Lindsay; Mihai Pop; Martin Antonio; Alan W. Walker; Volker Mai; Dilruba Ahmed; Joseph Oundo; Boubou Tamboura; Sandra Panchalingam; Myron M. Levine; Karen L. Kotloff; Shan Li; Laurence S. Magder; Joseph N. Paulson; Bo Liu; Usman N. Ikumapayi; Chinelo Ebruke; Michel M. Dione; Mitchell Adeyemi; Richard Rance; Mark D. Stares; Maria Ukhanova; Bret Barnes; Ian Lewis; Firoz Ahmed; Meer T. Alam; Ruhul Amin; Sabbir Siddiqui; John B. Ochieng; Emmanuel Ouma

ABSTRACT Cultivation-based assays combined with PCR or enzyme-linked immunosorbent assay (ELISA)-based methods for finding virulence factors are standard methods for detecting bacterial pathogens in stools; however, with emerging molecular technologies, new methods have become available. The aim of this study was to compare four distinct detection technologies for the identification of pathogens in stools from children under 5 years of age in The Gambia, Mali, Kenya, and Bangladesh. The children were identified, using currently accepted clinical protocols, as either controls or cases with moderate to severe diarrhea. A total of 3,610 stool samples were tested by established clinical culture techniques: 3,179 DNA samples by the Universal Biosensor assay (Ibis Biosciences, Inc.), 1,466 DNA samples by the GoldenGate assay (Illumina), and 1,006 DNA samples by sequencing of 16S rRNA genes. Each method detected different proportions of samples testing positive for each of seven enteric pathogens, enteroaggregative Escherichia coli (EAEC), enterotoxigenic E. coli (ETEC), enteropathogenic E. coli (EPEC), Shigella spp., Campylobacter jejuni, Salmonella enterica, and Aeromonas spp. The comparisons among detection methods included the frequency of positive stool samples and kappa values for making pairwise comparisons. Overall, the standard culture methods detected Shigella spp., EPEC, ETEC, and EAEC in smaller proportions of the samples than either of the methods based on detection of the virulence genes from DNA in whole stools. The GoldenGate method revealed the greatest agreement with the other methods. The agreement among methods was higher in cases than in controls. The new molecular technologies have a high potential for highly sensitive identification of bacterial diarrheal pathogens.


bioRxiv | 2015

Manta: Rapid detection of structural variants and indels for clinical sequencing applications

Xiaoyu Chen; Ole Schulz-Trieglaff; Richard Shaw; Bret Barnes; Felix Schlesinger; Anthony J. Cox; Semyon Kruglyak; Christopher T. Saunders

Summary We describe Manta, a method to discover structural variants and indels from next generation sequencing data. Manta is optimized for rapid clinical analysis, calling structural variants, medium-sized indels and large insertions on standard compute hardware in less than a tenth of the time that comparable methods require to identify only subsets of these variant types: for example NA12878 at 50x genomic coverage is analyzed in less than 20 minutes. Manta can discover and score variants based on supporting paired and split-read evidence, with scoring models optimized for germline analysis of diploid individuals and somatic analysis of tumor-normal sample pairs. Call quality is similar to or better than comparable methods, as determined by pedigree consistency of germline calls and comparison of somatic calls to COSMIC database variants. Manta consistently assembles a higher fraction of its calls to basepair resolution, allowing for improved downstream annotation and analysis of clinical significance. We provide Manta as a community resource to facilitate practical and routine structural variant analysis in clinical and research sequencing scenarios. Availability Manta source code and Linux binaries are available from http://github.com/sequencing/manta. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.


Cancer Research | 2011

Abstract LB-176: A novel high density DNA methylation array with single CpG site resolution

Marina Bibikova; Bret Barnes; Chan Tsan; Vincent Ho; Brandy Klotzle; Jennie M. Le; David Delano; Kevin L. Gunderson; Jian-Bing Fan; Richard Shen

Aberrations in DNA methylation patterns are widely recognized as a hallmark of the cancer cell. DNA methylation has emerged as a promising biomarker for the detection and classification of various types of cancer, and ability to accurately assess the DNA methylation changes plays an important role in understanding of disease onset and progression. We developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. In this assay, unmethylated cytosines (C) are converted to uracil (U) when treated with bisulfite, while methylated cytosines remain unchanged. The assay design is using single probe assays for CpG loci with up to two underlying CpG dinucleotides, and two-probe assays for CpG loci with multiple underlying CpG sites, with one probe querying the “unmethylated” allele and the other probe querying the “methylated” allele. The assays are designed under the assumption that methylation is regionally correlated (within 50 base pairs) and that all CpG sites underlying the probe are assumed to be “in phase” with the queried CpG site. For the BeadChip development, we used methylation standards created by de-methylating gDNA with Phi29 whole genome amplification, methylating the amplified DNA with SssI methylase and mixing the unmethylated and methylated DNA in a 1:1 ratio to create a 50% methylation state. 500 ng gDNA input is used for bisulfite conversion and is sufficient for two assays. Reproducible DNA methylation profiles were obtained between replicates (an average R 2 of 0.98). We applied this technology to DNA methylation analyses in cancer cell lines of different tissue of origin and normal DNA samples derived from multiple tissues. Highly specific methylation signatures were obtained for each sample type. The ability to determine genome-wide methylation patterns will rapidly advance methylation research and ultimately lead to the development of powerful tools for diagnosis, prognosis, and treatment of human diseases. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-176. doi:10.1158/1538-7445.AM2011-LB-176


Epigenomics | 2009

Genome-wide DNA methylation profiling using Infinium® assay.

Marina Bibikova; Jennie Le; Bret Barnes; Shadi Saedinia-Melnyk; Lixin Zhou; Richard Shen; Kevin L. Gunderson

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