121 research outputs found
Simultaneous mapping of multiple gene loci with pooled segregants
The analysis of polygenic, phenotypic characteristics such as quantitative traits or inheritable diseases remains an important challenge. It requires reliable scoring of many genetic markers covering the entire genome. The advent of high-throughput sequencing technologies provides a new way to evaluate large numbers of single nucleotide polymorphisms (SNPs) as genetic markers. Combining the technologies with pooling of segregants, as performed in bulked segregant analysis (BSA), should, in principle, allow the simultaneous mapping of multiple genetic loci present throughout the genome. The gene mapping process, applied here, consists of three steps: First, a controlled crossing of parents with and without a trait. Second, selection based on phenotypic screening of the offspring, followed by the mapping of short offspring sequences against the parental reference. The final step aims at detecting genetic markers such as SNPs, insertions and deletions with next generation sequencing (NGS). Markers in close proximity of genomic loci that are associated to the trait have a higher probability to be inherited together. Hence, these markers are very useful for discovering the loci and the genetic mechanism underlying the characteristic of interest. Within this context, NGS produces binomial counts along the genome, i.e., the number of sequenced reads that matches with the SNP of the parental reference strain, which is a proxy for the number of individuals in the offspring that share the SNP with the parent. Genomic loci associated with the trait can thus be discovered by analyzing trends in the counts along the genome. We exploit the link between smoothing splines and generalized mixed models for estimating the underlying structure present in the SNP scatterplots
American Society for Echocardiography Software Suite for Verification and
The imminent balloting of the draft DICOM 3.0 module
on ultrasound represents a major step forward in the
progress of digital storage formats for
echocardiography. In this paper, we discuss a software
suite soon to be released into the public domain for
reading, parsing and verifying DICOM 3.0 ultrasonic
objects. The software is designed to allow the user to
verify that a Jle consisting of digital ultrasound data,
claiming DlCOM 3.0 conformance, does in fact adhere
to the standard. A graphical user-interface for the
software suite is also provided, allowing the playback of
cin& mode images in real-time on standard computer
hardware, and across a TCP/IP network
Archeologische Opgraving Houthalen-Helchteren - Eikendreef
Dit rapport werd ingediend bij het agentschap samen met een aantal afzonderlijke digitale bijlagen. Een aantal van deze bijlagen zijn niet inbegrepen in dit pdf document en zijn niet online beschikbaar. Sommige bijlagen (grondplannen, fotos, spoorbeschrijvingen, enz.) kunnen van belang zijn voor een betere lezing en interpretatie van dit rapport. Indien u deze bijlagen wenst te raadplegen kan u daarvoor contact opnemen met: [email protected]
Archeologische prospectie met ingreep in de bodem Bierbeek - Mevrouwkensveld
Dit rapport werd ingediend bij het agentschap samen met een aantal afzonderlijke digitale bijlagen. Een aantal van deze bijlagen zijn niet inbegrepen in dit pdf document en zijn niet online beschikbaar. Sommige bijlagen (grondplannen, fotos, spoorbeschrijvingen, enz.) kunnen van belang zijn voor een betere lezing en interpretatie van dit rapport. Indien u deze bijlagen wenst te raadplegen kan u daarvoor contact opnemen met: [email protected]
Van jonge steentijd tot een Hollands legerkamp. Verslag van het archeologisch onderzoek te Bree, Houbornstraat
Archeologische opgraving Tienen - Kronkelweg
Dit rapport werd ingediend bij het agentschap samen met een aantal afzonderlijke digitale bijlagen. Een aantal van deze bijlagen zijn niet inbegrepen in dit pdf document en zijn niet online beschikbaar. Sommige bijlagen (grondplannen, fotos, spoorbeschrijvingen, enz.) kunnen van belang zijn voor een betere lezing en interpretatie van dit rapport. Indien u deze bijlagen wenst te raadplegen kan u daarvoor contact opnemen met: [email protected]
A new pedigree with thrombomodulin-associated coagulopathy in which delayed fibrinolysis is partially attenuated by co-inherited TAFI deficiency
ACKNOWLEDGEMENTS We thank NIHR BioResource volunteers for their participation, and gratefully acknowledge NIHR BioResource centres, NHS Trusts and staff for their contribution. We thank the National Institute for Health Research and NHS Blood and Transplant. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health and Social Care. S.K.W. was supported during this work by the Medical Research Council (MR/K023489/1) and is now funded through an NIHR-funded Academic Clinical Lectureship. K.D. is supported as a HSST trainee by NHS Health Education England. N.J.M. and C.S.W. are supported by the British Heart Foundation (PG/15/82/31721). J.C.M. is a fellow of the Research Foundation Flanders (FWO Vlaanderen; 1137717N). A.D.M. is supported by the NIHR Biomedical Research Centre at the University Hospitals Bristol National Health Service Foundation Trust and the University of Bristol. We thank Prof Paul Declerck and Prof Ann Gils, University Leuven, Belgium for the kind gift of the MA-T12D11 antibody. We acknowledge technical assistance from Dorien Leenaerts, University of Antwerp, Belgium and Michela Donnarumma, University of Aberdeen, UK.Peer reviewedPublisher PD
Visualization of proteomics data using R and bioconductor.
Data visualization plays a key role in high-throughput biology. It is an essential tool for data exploration allowing to shed light on data structure and patterns of interest. Visualization is also of paramount importance as a form of communicating data to a broad audience. Here, we provided a short overview of the application of the R software to the visualization of proteomics data. We present a summary of R's plotting systems and how they are used to visualize and understand raw and processed MS-based proteomics data.LG was supported by the
European Union 7th Framework Program (PRIME-XS project,
grant agreement number 262067) and a BBSRC Strategic Longer
and Larger grant (Award BB/L002817/1). LMB was supported
by a BBSRC Tools and Resources Development Fund (Award
BB/K00137X/1). TN was supported by a ERASMUS Placement
scholarship.This is the final published version of the article. It was originally published in Proteomics (PROTEOMICS Special Issue: Proteomics Data Visualisation Volume 15, Issue 8, pages 1375–1389, April 2015. DOI: 10.1002/pmic.201400392). The final version is available at http://onlinelibrary.wiley.com/doi/10.1002/pmic.201400392/abstract
The MMSE should not be the sole indicator of fitness to drive in mild Alzheimer's dementia
Since Alzheimer’s disease may affect driving performance, patients with Alzheimer’s disease are assessed on fitness to drive. On-road driving assessments are widely used, and attempts have also been made to develop strategies to assess fitness to drive in a clinical setting. Preferably, a first indication of fitness to drive is obtained quickly after diagnosis using a single test such as the Mini-Mental State Examination (MMSE). The aim of this study is to investigate whether the MMSE can be used to predict whether patients with Alzheimer’s disease will pass or fail an on-road driving assessment. Patients with Alzheimer’s disease (n = 81) participated in a comprehensive fitness-to-drive assessment which included the MMSE as well as an on-road driving assessment [PLoS One 11(2):e0149566, 2016]. MMSE cutoffs were applied as suggested by Versijpt and colleagues [Acta Neurol Belg 117(4):811–819, 2017]. All patients with Alzheimer’s disease who scored below the lower cutoff (MMSE ≤ 19) failed the on-road driving assessment. However, a third of the patients with Alzheimer’s disease who scored above the upper cutoff (MMSE ≥ 25) failed the on-road driving assessment as well. We conclude that the MMSE alone has insufficient predictive value to correctly identify fitness to drive in patients with very mild-to-mild Alzheimer’s disease implicating the need for comprehensive assessments to determine fitness to drive in a clinical setting
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