scholarly journals Genetic association testing using the GENESIS R/Bioconductor package

2019 ◽  
Author(s):  
Stephanie M Gogarten ◽  
Tamar Sofer ◽  
Han Chen ◽  
Chaoyu Yu ◽  
Jennifer A Brody ◽  
...  
Keyword(s):  
Data Storage ◽  
Genomic Analysis ◽  
Supplementary Information ◽  
Storage And Retrieval ◽  
Association Testing ◽  
Link Functions ◽  
Efficient Storage ◽  
Genetic Association Testing ◽  
Analysis Workflow ◽  
Complete Genomic

Abstract Summary The Genomic Data Storage (GDS) format provides efficient storage and retrieval of genotypes measured by microarrays and sequencing. We developed GENESIS to perform various single- and aggregate-variant association tests using genotype data stored in GDS format. GENESIS implements highly flexible mixed models, allowing for different link functions, multiple variance components and phenotypic heteroskedasticity. GENESIS integrates cohesively with other R/Bioconductor packages to build a complete genomic analysis workflow entirely within the R environment. Availability and implementation https://bioconductor.org/packages/GENESIS; vignettes included. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Storage Method of Multi-Channel Lidar Data Based on Tree Structure

2022 ◽  
Author(s):  
Hao Chen ◽  
Fei Gao ◽  
Qingsong Zhu ◽  
Qing Yan ◽  
Dengxin Hua ◽  
...  
Keyword(s):  
Data Storage ◽  
Large Data ◽  
Tree Structure ◽  
Lidar Data ◽  
Storage And Retrieval ◽  
Efficient Storage ◽  
Novel Approach ◽  
Data Volume ◽  
Acquisition Speed ◽  
Storage Methods

Abstract The multi-channel lidar has the characteristics of fast acquisition speed, large data volume, high dimension, and strong real-time storage, which makes it difficult to be met using the traditional lidar data storage methods. This paper presents a novel approach to store and convert the multi-channel lidar data by traversal method of the tree structure and binary code. In the proposed approach, a tree structure is constructed based on the multi-dimensional characteristics of multi-channel lidar data and the hierarchical relationship between them. The adjacency table storage structure data in the memory is used to generate the sub-tree of the multi-channel lidar data. The results show that the proposed tree structure approach can save the storage capacity and improve the retrieval speed, which can meet the needs of efficient storage and retrieval of multi-channel lidar data.

Design and Implementation of Efficient Storage and Retrieval Technology of Traffic Big Data

2019 ◽  
Vol 4 (2) ◽  
pp. 207-220
Author(s):  
김기수 ◽  
Yukun Hahm ◽  
장유림 ◽  
Jaejin Yi ◽  
HONGHOI KIM
Keyword(s):  
Big Data ◽  
Storage And Retrieval ◽  
Design And Implementation ◽  
Efficient Storage

scholarly journals ASICS: an R package for a whole analysis workflow of 1D 1H NMR spectra

2019 ◽  
Vol 35 (21) ◽  
pp. 4356-4363 ◽  
Author(s):  
Gaëlle Lefort ◽  
Laurence Liaubet ◽  
Cécile Canlet ◽  
Patrick Tardivel ◽  
Marie-Christine Père ◽  
...  
Keyword(s):  
Metabolic Pathways ◽  
Nmr Spectra ◽  
Complex Mixture ◽  
R Package ◽  
Statistical Analyses ◽  
Supplementary Information ◽  
Automatic Identification ◽  
Analysis Workflow ◽  
Expert Analysis ◽  
New Biomarkers

Abstract Motivation In metabolomics, the detection of new biomarkers from Nuclear Magnetic Resonance (NMR) spectra is a promising approach. However, this analysis remains difficult due to the lack of a whole workflow that handles spectra pre-processing, automatic identification and quantification of metabolites and statistical analyses, in a reproducible way. Results We present ASICS, an R package that contains a complete workflow to analyse spectra from NMR experiments. It contains an automatic approach to identify and quantify metabolites in a complex mixture spectrum and uses the results of the quantification in untargeted and targeted statistical analyses. ASICS was shown to improve the precision of quantification in comparison to existing methods on two independent datasets. In addition, ASICS successfully recovered most metabolites that were found important to explain a two level condition describing the samples by a manual and expert analysis based on bucketing. It also found new relevant metabolites involved in metabolic pathways related to risk factors associated with the condition. Availability and implementation ASICS is distributed as an R package, available on Bioconductor. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals TFEA.ChIP: a tool kit for transcription factor binding site enrichment analysis capitalizing on ChIP-seq datasets

2019 ◽  
Vol 35 (24) ◽  
pp. 5339-5340 ◽  
Author(s):  
Laura Puente-Santamaria ◽  
Wyeth W Wasserman ◽  
Luis del Peso
Keyword(s):  
Genomic Analysis ◽  
Enrichment Analysis ◽  
R Package ◽  
Supplementary Information ◽  
Web Based ◽  
Factor Binding Site ◽  
Gene Sets ◽  
Transcription Regulators ◽  
Computational Identification ◽  
On Chip

Abstract Summary The computational identification of the transcription factors (TFs) [more generally, transcription regulators, (TR)] responsible for the co-regulation of a specific set of genes is a common problem found in genomic analysis. Herein, we describe TFEA.ChIP, a tool that makes use of ChIP-seq datasets to estimate and visualize TR enrichment in gene lists representing transcriptional profiles. We validated TFEA.ChIP using a wide variety of gene sets representing signatures of genetic and chemical perturbations as input and found that the relevant TR was correctly identified in 126 of a total of 174 analyzed. Comparison with other TR enrichment tools demonstrates that TFEA.ChIP is an highly customizable package with an outstanding performance. Availability and implementation TFEA.ChIP is implemented as an R package available at Bioconductor https://www.bioconductor.org/packages/devel/bioc/html/TFEA.ChIP.html and github https://github.com/LauraPS1/TFEA.ChIP_downloads. A web-based GUI to the package is also available at https://www.iib.uam.es/TFEA.ChIP/ Supplementary information Supplementary data are available at Bioinformatics online.

Complete genomic analysis of multidrug-resistance Pseudomonas aeruginosa Guangzhou-Pae617, the host of megaplasmid pBM413

2018 ◽  
Vol 117 ◽  
pp. 265-269 ◽  
Author(s):  
Junyan Liu ◽  
Lin Li ◽  
Brian M. Peters ◽  
Bing Li ◽  
Dingqiang Chen ◽  
...  
Keyword(s):  
Pseudomonas Aeruginosa ◽  
Multidrug Resistance ◽  
Genomic Analysis ◽  
Complete Genomic

scholarly journals The NMR Spectral Measurement Database: A System for Organizing and Accessing NMR Spectra of Therapeutic Proteins

2021 ◽  
Vol 126 ◽  
Author(s):  
Niksa Blonder ◽  
Frank Delaglio
Keyword(s):  
Nuclear Magnetic Resonance ◽  
Magnetic Resonance ◽  
Spectral Data ◽  
Data Storage ◽  
Nmr Spectra ◽  
Therapeutic Proteins ◽  
Data Access ◽  
Protein Therapeutics ◽  
Spectral Measurement ◽  
Storage And Retrieval

The Nuclear Magnetic Resonance Spectral Measurement Database (NMR-SMDB) was developed for the purpose of organizing and searching NMR spectral data of protein therapeutics, linking spectra to corresponding sample information and enabling quick access to full datasets and entire studies. In addition to supporting internal research at the National Institute of Standards and Technology (NIST), the system could facilitate data access to stakeholders outside of NIST, and future versions of the database software itself could be installed by others for their own data storage and retrieval.

Complete genomic analysis of a Bangladeshi G1P[8] rotavirus strain detected in 2003 reveals a close evolutionary relationship with contemporary human Wa-like strains

2010 ◽  
Vol 10 (6) ◽  
pp. 746-754 ◽  
Author(s):  
Mustafizur Rahman ◽  
Jelle Matthijnssens ◽  
Farjana Saiada ◽  
Zahid Hassan ◽  
Elisabeth Heylen ◽  
...  
Keyword(s):  
Evolutionary Relationship ◽  
Genomic Analysis ◽  
Complete Genomic
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