45 research outputs found
A meta-analysis of public microarray data identifies gene regulatory pathways deregulated in peripheral blood mononuclear cells from individuals with Systemic Lupus Erythematosus compared to those without
BACKGROUND: Systemic Lupus Erythematosus (SLE) is a complex, multi-systemic, autoimmune disease for which the
underlying aetiological mechanisms are poorly understood. The genetic and molecular processes underlying lupus
have been extensively investigated using a variety of -omics approaches, including genome-wide association studies,
candidate gene studies and microarray experiments of differential gene expression in lupus samples compared to
controls.
METHODS: This study analyses a combination of existing microarray data sets to identify differentially regulated genetic
pathways that are dysregulated in human peripheral blood mononuclear cells from SLE patients compared to unaffected
controls. Two statistical approaches, quantile discretisation and scaling, are used to combine publicly available expression
microarray datasets and perform a meta-analysis of differentially expressed genes.
RESULTS: Differentially expressed genes implicated in interferon signaling were identified by the meta-analysis,
in agreement with the findings of the individual studies that generated the datasets used. In contrast to the
individual studies, however, the meta-analysis and subsequent pathway analysis additionally highlighted TLR
signaling, oxidative phosphorylation and diapedesis and adhesion regulatory networks as being differentially
regulated in peripheral blood mononuclear cells (PBMCs) from SLE patients compared to controls.
CONCLUSION: Our analysis demonstrates that it is possible to derive additional information from publicly
available expression data using meta-analysis techniques, which is particularly relevant to research into rare
diseases where sample numbers can be limiting.Scopus & IS
Hackathons as a means of accelerating scientific discoveries and knowledge transfer
Scientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal
challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed.
Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical
processing of the data is often performed by individual researchers within the team, with only limited internal oversight and
critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collaborative
science by enabling peer review before results of analyses are published by cross-validating the design of studies or
underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators
and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to
build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations
between multiple investigators and institutions.SCOPU
Hackathons as a means of accelerating scientific discoveries and knowledge transfer
International audienceScientific research plays a key role in the advancement of human knowledge and pursuit of solutions to important societal challenges. Typically, research occurs within specific institutions where data are generated and subsequently analyzed. Although collaborative science bringing together multiple institutions is now common, in such collaborations the analytical processing of the data is often performed by individual researchers within the team, with only limited internal oversight and critical analysis of the workflow prior to publication. Here, we show how hackathons can be a means of enhancing collab-orative science by enabling peer review before results of analyses are published by cross-validating the design of studies or underlying data sets and by driving reproducibility of scientific analyses. Traditionally, in data analysis processes, data generators and bioinformaticians are divided and do not collaborate on analyzing the data. Hackathons are a good strategy to build bridges over the traditional divide and are potentially a great agile extension to the more structured collaborations between multiple investigators and institutions
Genotyping by sequencing provides new insights into the diversity of Napier grass (Cenchrus purpureus) and reveals variation in genome-wide LD patterns between collections
peer-reviewedNapier grass is an important tropical forage-grass and of growing potential as an energy crop. One-hundred-five Napier grass accessions, encompassing two independent collections, were subjected to genotyping by sequencing which generated a set of high-density genome-wide markers together with short sequence reads. The reads, averaging 54 nucleotides, were mapped to the pearl millet genome and the closest genes and annotation information were used to select candidate genes linked to key forage traits. 980 highly polymorphic SNP markers, distributed across the genome, were used to assess population structure and diversity with seven-subgroups identified. A few representative accessions were selected with the objective of distributing subsets of a manageable size for further evaluation. Genome-wide linkage disequilibrium (LD) analyses revealed a fast LD-decay, on average 2.54 kbp, in the combined population with a slower LD-decay in the ILRI collection compared with the EMBRAPA collection, the significance of which is discussed. This initiative generated high-density markers with a good distribution across the genome. The diversity analysis revealed the existence of a substantial amount of variation in the ILRI collection and identified some unique materials from the EMBRAPA collection, demonstrating the potential of the overall population for further genetic and marker-trait-association studies
Renewing Felsenstein’s phylogenetic Bootstrap in the era of big data
Felsenstein’s application of the bootstrap method to evolutionary trees is one of the most cited scientific papers of all
time. The bootstrap method, which is based on resampling and replications, is used extensively to assess the robustness
of phylogenetic inferences. However, increasing numbers of sequences are now available for a wide variety of species,
and phylogenies based on hundreds or thousands of taxa are becoming routine. With phylogenies of this size Felsenstein’s
bootstrap tends to yield very low supports, especially on deep branches. Here we propose a new version of the phylogenetic
bootstrap in which the presence of inferred branches in replications is measured using a gradual ‘transfer’ distance rather
than the binary presence or absence index used in Felsenstein’s original version. The resulting supports are higher and
do not induce falsely supported branches. The application of our method to large mammal, HIV and simulated datasets
reveals their phylogenetic signals, whereas Felsenstein’s bootstrap fails to do so
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Molecular and serological diagnosis of multiple bacterial zoonoses in febrile outpatients in Garissa County, north-eastern Kenya
Bacterial zoonoses are diseases caused by bacterial pathogens that can be naturally transmitted between humans and vertebrate animals. They are important causes of non-malarial fevers in Kenya, yet their epidemiology remains unclear. We investigated brucellosis, Q-fever and leptospirosis in the venous blood of 216 malaria-negative febrile patients recruited in two health centres (98 from Ijara and 118 from Sangailu health centres) in Garissa County in north-eastern Kenya. We determined exposure to the three zoonoses using serological (Rose Bengal test for Brucella spp., ELISA for C. burnetti and microscopic agglutination test for Leptospira spp.) and real-time PCR testing and identified risk factors for exposure. We also used non-targeted metagenomic sequencing on nine selected patients to assess the presence of other possible bacterial causes of non-malarial fevers. Considerable PCR positivity was found for Brucella (19.4%, 95% confidence intervals [CI] 14.2–25.5) and Leptospira spp. (1.7%, 95% CI 0.4–4.9), and high endpoint titres were observed against leptospiral serovar Grippotyphosa from the serological testing. Patients aged 5–17 years old had 4.02 (95% CI 1.18–13.70, p-value = 0.03) and 2.42 (95% CI 1.09–5.34, p-value = 0.03) times higher odds of infection with Brucella spp. and Coxiella burnetii than those of ages 35–80. Additionally, patients who sourced water from dams/springs, and other sources (protected wells, boreholes, bottled water, and water pans) had 2.39 (95% CI 1.22–4.68, p-value = 0.01) and 2.24 (1.15–4.35, p-value = 0.02) times higher odds of exposure to C. burnetii than those who used unprotected wells. Streptococcus and Moraxella spp. were determined using metagenomic sequencing. Brucellosis, leptospirosis, Streptococcus and Moraxella infections are potentially important causes of non-malarial fevers in Garissa. This knowledge can guide routine diagnosis, thus helping lower the disease burden and ensure better health outcomes, especially in younger populations
Designing a course model for distance-based online bioinformatics training in Africa: the H3ABioNet experience
Africa is not unique in its need for basic bioinformatics training for individuals from a diverse
range of academic backgrounds. However, particular logistical challenges in Africa, most
notably access to bioinformatics expertise and internet stability, must be addressed in order
to meet this need on the continent. H3ABioNet (www.h3abionet.org), the Pan African Bioinformatics
Network for H3Africa, has therefore developed an innovative, free-of-charge
"Introduction to Bioinformatics" course, taking these challenges into account as part of its
educational efforts to provide on-site training and develop local expertise inside its network.
A multiple-delivery±mode learning model was selected for this 3-month course in order to
increase access to (mostly) African, expert bioinformatics trainers. The content of the
course was developed to include a range of fundamental bioinformatics topics at the introductory
level. For the first iteration of the course (2016), classrooms with a total of 364
enrolled participants were hosted at 20 institutions across 10 African countries. To ensure
that classroom success did not depend on stable internet, trainers pre-recorded their lectures,
and classrooms downloaded and watched these locally during biweekly contact sessions.
The trainers were available via video conferencing to take questions during contact sessions, as well as via online "question and discussion" forums outside of contact session time. This learning model, developed for a resource-limited setting, could easily be adapted
to other settings.IS
Technical assistance to strengthen national agricultural research organizations’ capacity to use digital sequence information. A submission from CGIAR
CGIAR submitted this report in response to an open request from the Plant Treaty Secretary, for submissions regarding, a) contracting parties’ and stakeholders’ capacity building needs for accessing and using digital sequence information (DSI)/genomic sequence data (GSD) and b) ‘technical assistance’ and ‘actions taken’ by stakeholders (including CGIAR) ‘to reduce the existing gap on capacity regarding DSI/GSD’.
The primary objective of this paper is to respond to the second part of the request by sharing information about how CGIAR Centers and Initiatives have been assisting organizations outside CGIAR to access, generate, share, analyse, and use DSI for the conservation of plant genetic resources for food and agriculture (PRGFA) and for the use of PGRFA in pre-breeding and breeding. This paper does not provide an exhaustive account of all of the Centers’ relevant activities, but it does provide a general overview of the kinds of activities in which the Centers have been engaged. CGIAR very much appreciates the Governing Body’s initiative, as expressed in Resolution 16/2022, to ask the Plant Treaty Secretariat to gather and synthesize information about both demand for, and supply of, capacity strengthening related to DSI linked to plant genetic resources for food and agriculture, with the overall objective of working to close the capacity gap between developed and developing countries. It is our hope that, based on the outcomes of this exercise, CGIAR will be able to further adapt and improve its own approach to capacity sharing in response to needs prioritized by the Governing Body