Sentences with phrase «generation sequencing data»

23/3: 30 Quantifying heritability explained in inflammatory bowel disease using 18,000 GWAS and 9,000 next generation sequencing data.

33/4: 00 A method for detecting intragenic copy number changes of BRCA1 and BRCA2 using next - generation sequencing data.

Here, we present a method, called MrMosaic, to detect structural mosaic abnormalities using deviations in allele fraction and read coverage from next - generation sequencing data.

Dr. Li's research interests focus on machine learning, bioinformatics, and statistical data mining in large scale data in biomedical research, such as next generation sequencing data (whole genome sequencing, RNA - seq, microarray data), in the file.

Preference will be given to those with experience in analysis of next generation sequencing data.

Our lab blends computation and theory in close collaboration with experimentalists and clinicians, developing machine learning approaches and statistical models of next - generation sequencing data.

An ensemble strategy that significantly improves de novo assembly of microbial genomes from metagenomic next - generation sequencing data.

Here we explore the power of two haplotype - based statistics — the integrated haplotype score (iHS) and the Derived Intra-allelic Nucleotide Diversity (DIND) test — in the context of next - generation sequencing data, and evaluate their robustness to demography and other selection modes.

Developed in collaboration with the Laboratory Medicine, Information Technology and Health Science Research departments of Mayo Clinic Geneticist Assistant NGS Interpretative Workbench, is a web - based tool for the control, visualization, interpretation and historical knowledge base of next generation sequencing data targeted at specific genes for the purpose of identifying potentially pathogenic variants associated with specific conditions such as hereditary colon cancer.

The paper describes various challenges arising from the process of designing a benchmark strategy for bioinformatics pipelines (2) in the identification of antimicrobial resistance genes in next generation sequencing data.

Metagenomics: Tools and Insights for Analyzing Next - Generation Sequencing Data Derived from Biodiversity Studies — Anastasis Oulas — Bioinform Biol Insights — May 2015

Experience with next - generation sequencing data is an advantage, but is not required.

Ebba is a Master student from the «X-program» (Engineer program in Molecular Biotechnology) from Uppsala University, and she will work on building efficient bioinformatics pipelines for efficient analyses of large amounts of next - generation sequencing data.

Estimation of allele frequency and association mapping using next - generation sequencing data Kim, S. Y., K. E. Lohmueller, A. Albrechtsen, Y. Li et al. 2011.

Estimation of allele frequency and association mapping using next - generation sequencing data.

ANGSD: Analysis of Next Generation Sequencing Data Korneliussen, T. S., A. Albrechtsen, and R. Nielsen.

Explore one of the world's largest repositories of next - generation sequencing data and analysis tools for pediatric cancer.

Genotype and SNP calling from next - generation sequencing data.

Design of association studies with pooled or un ‐ pooled next ‐ generation sequencing data Kim, S. Y., Y. Li, Y. Guo, R. Li et al. 2010.

Calculation of Tajima's D and other neutrality test statistics from low depth next - generation sequencing data.

Calculation of Tajima's D and other neutrality test statistics from low depth next - generation sequencing data Korneliussen, T. S., I. Moltke, A. Albrechtsen, and R. Nielsen.

ngsTools: methods for population genetics analyses from next - generation sequencing data.

Genotype and SNP calling from next - generation sequencing data Nielsen, R., J. S. Paul, A. Albrechtsen, and Y. S. Song.

ANGSD: Analysis of Next Generation Sequencing Data.

SNP calling, genotype calling, and sample allele frequency estimation from new - generation sequencing data Nielsen, R. T. Korneliussen, A. Albrechtsen, Y. Li et al. 2012.

A Hidden Markov Model Approach for Simultaneously Estimating Local Ancestry and Admixture Time Using Next Generation Sequence Data in Samples of Arbitrary Ploidy.

Our interest is to not only generate next - generation sequence data, but to mine this sequence data to better understand the evolution, pathogenesis, and transmission of ZIKV following the outbreak in Brazil in 2015.

A Hidden Markov Model Approach for Simultaneously Estimating Local Ancestry and Admixture Time Using Next Generation Sequence Data in Samples of Arbitrary Ploidy Corbett - Detig, R., R. Nielsen.

Thus we've formed a focus group to evaluate the different programs for sequence alignment and variant detection in next - generation sequence data.

Not exact matches

Next - generation sequencing and global data sharing challenge many of the governance mechanisms currently in place to protect the privacy of research participants.

RAPiD Genomics is a genotyping and data analysis company specializing in flexible, innovative genomic solutions via next - generation sequencing.

Apart from using a host of cutting - edge molecular techniques such as Next Generation Sequencing or NGS, the researchers also had to develop specific bioinformatic tools for analysing large amounts of genomic data.

In contrast, when the OncoFinder algorithm is applied to the data, a clear correlation between next generation sequencing and microarray gene expression datasets was seen.

With the continual improvement of next - generation sequencing technologies, however, obtaining large molecular data sets is becoming much easier, and much cheaper.

As the chimpanzee genome is roughly three - gigabases in length, the volume of this sequence data was unprecedented, enabling the scientists to decipher precise mutation trajectories occuring within one generation.

The convergence of several factors explains the trend: cheaper genetic sequencing technologies, the discovery of new oncogenes (genes that can cause a normal cell to become cancerous), a new generation of computers and bioinformatics that can analyze vast amounts of data, and a multibillion - dollar effort by researchers inside and outside the pharma industry to develop targeted drugs and companion diagnostics for cancer.

With recent, rapid advances in next - generation sequencing technologies, large genomic data sets are becoming increasingly obtainable.

«Scientists challenge next - generation sequencing dogma: Surprising bacteria study reveals that shotgun sequencing misses major groups of organisms despite producing more data than amplicon sequencing.»

Today, top researchers and medical centers are taking next generation sequencing (NGS) data and translating this into improved patient care.

Next - generation sequencing produces an extraordinary amount of data.

The atlas now also includes RNA transcript data for 27 of these organ - specific tissues using next generation sequencing, providing a tissue distribution map of both protein and gene expression.

Access to advanced high - throughput instruments for next generation sequencing at SciLifeLab has enabled the very fast process of adding transcript data to the protein atlas.

Efficient generation of complete sequences of MDR - encoding plasmids by rapid assembly of MinION barcoding sequencing data

In the case of clinical next - generation sequencing, and in genetic cohort studies and biobanks, pertinent issues include the interpretation of data, data storage, data sharing, informed consent and identifiability / privacy [20][26].

deCODE's discovery capabilities combine its extensive population and genetic resources, including DNA samples and medical data, complete genealogical information, next generation sequencing technology, and deCODE's proprietary bioinformatics and statistical capabilities.

The exome sequences of 1,535 Kronos and 1,200 Cadenza mutants have been re-sequenced using Illumina next - generation sequencing, the raw data aligned to the IWGSC Chinese Spring chromosome arm survey sequence, mutations identified, and their effects predicted based on the protein annotation available at the Ensembl Plants archive site.

Extracting proper information from large data has become not only a serious problem of Next Generation Sequencing (NGS), which produces an enormous amount of data, but also a difficult task for 3D molecular databases, as the amount of such data is increasing dramatically as well.

Ongoing T2D research activities at CRGGH include 1) whole - exome sequencing of African families with at least four affected members (data generation is complete and analysis is ongoing), 2) GWAS of 1,200 cases and 1,200 controls from West Africa using the new and more efficient African - centric Affymetrix Axiom genome - wide array with more than 2 million markers, and 3) whole genome expression analysis on skeletal muscle obtained from biopsy from 45 subjects (expression QTL (eQTL) studies on the dataset are complete).

We have re-sequenced the exome of 1,535 Kronos and 1,200 Cadenza mutants using Illumina next - generation sequencing, aligned this raw data to the IWGSC Chinese Spring chromosome arm survey sequence, identified mutations, and predicted their effects based on the protein annotation available at Ensembl Plants.

Moving from DNA barcoding to metabarcoding perfectly embodies the conceptual transition from single gene to massively parallel genome analysis, introducing students to Next Generation Sequence (NGS) analysis and data science.