Nyasha Chambwe

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Large biological datasets are being produced at a rapid pace and create substantial storage challenges, particularly in the domain of high-throughput sequencing (HTS). Most approaches currently used to store HTS data are either unable to quickly adapt to the requirements of new sequencing or analysis methods (because they do not support schema evolution),(More)
We present GobyWeb, a web-based system that facilitates the management and analysis of high-throughput sequencing (HTS) projects. The software provides integrated support for a broad set of HTS analyses and offers a simple plugin extension mechanism. Analyses currently supported include quantification of gene expression for messenger and small RNA(More)
Early life adversity, including adverse gestational and postpartum maternal environment, is a contributing factor in the development of autism, attention deficit hyperactivity disorder (ADHD), anxiety and depression but little is known about the underlying molecular mechanism. In a model of gestational maternal adversity that leads to innate anxiety,(More)
UNLABELLED High-throughput data can be used in conjunction with clinical information to develop predictive models. Automating the process of developing, evaluating and testing such predictive models on different datasets would minimize operator errors and facilitate the comparison of different modeling approaches on the same dataset. Complete automation(More)
Key Points • Unsupervised clustering of DLBCLs based on DNA methylation changes identifies 6 novel epigenetic clusters. • Greater magnitude of methylation changes correlates with worse clinical outcome. Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive form of non-Hodgkin lymphoma with variable biology and clinical behavior. The current(More)
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