Multiple sclerosis (MS) is a chronic disorder of the central nervous system (CNS). MS affects 2.1 million individuals every year and is also considered a major cause of economic health burden around the world. Genetics and environmental factors both play a role in the pathogenesis of MS by activating the immune response and causing inflammation. Patients with MS can have various clinical courses, but the most common pattern seen is relapsing-remitting multiple sclerosis (RRMS). Multiple therapeutic options have been studied to prevent RRMS patients from frequent relapses. The oldest and most frequently used medication for MS is interferon beta, either used alone or as add-on therapy with other drugs. Newer treatment options that have been recently approved to control MS symptoms and suppress the inflammation are glatiramer acetate and siponimod. Infusion therapies consisting of monoclonal antibodies and immunosuppressive drugs have also been studied in the recent past. Some trials have been conducted on the use of stem cells for RRMS patients. We have briefly discussed all treatment options and the response of RRMS patients in multiple trials.
Rare diseases affect nearly 300 million people globally with most patients aged five or less. Traditional diagnostic approaches have provided much of the diagnosis; however, there are limitations. For instance, simply inadequate and untimely diagnosis adversely affects both the patient and their families. This review advocates the use of whole genome sequencing in clinical settings for diagnosis of rare genetic diseases by showcasing five case studies. These examples specifically describe the utilization of whole genome sequencing, which helped in providing relief to patients via correct diagnosis followed by use of precision medicine.
Motivation
Metabolomics is a data analysis and interpretation field aiming to study functions of small molecules within the organism. Consequently Metabolomics requires researchers in life sciences to be comfortable in downloading, installing and scripting of software that are mostly not user friendly and lack basic GUIs. As the researchers struggle with these skills, there is a dire need to develop software packages that can automatically install software pipelines truly speeding up the learning curve to build software workstations. Therefore, this paper aims to provide MetumpX, a software package that eases in the installation of 103 software by automatically resolving their individual dependencies and also allowing the users to choose which software works best for them.
Results
MetumpX is a Ubuntu-based software package that facilitate easy download and installation of 103 tools spread across the standard metabolomics pipeline. As far as the authors know MetumpX is the only solution of its kind where the focus lies on automating development of software workstations.
Availability and implementation
https://github.com/hasaniqbal777/MetumpX-bin.
Supplementary information
Supplementary data are available at Bioinformatics online.
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