The author affiliations for Deepak B. Thimiri Govinda Raj which previously read.
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A Software Tool for Rapid and Automated Preprocessing of Large-Scale Serum Metabolomic Data by Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry.
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Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Ontario L8S 4M1, Canada.
Mass spectrometry (MS)-based metabolomics often rely on separation techniques when analyzing complex biological specimens to improve method resolution, metabolome coverage, quantitative performance, and/or unknown identification. However, low sample throughput and complicated data preprocessing procedures remain major barriers to affordable metabolomic studies that are scalable to large populations. Herein, we introduce PeakMeister as a new software tool in the R statistical environment to enable standardized processing of serum metabolomic data acquired by multisegment injection-capillary electrophoresis-mass spectrometry (MSI-CE-MS), a high-throughput separation platform (<4 min/sample) which takes advantage of a serial injection format of 13 samples within a single analytical run.
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Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, MN, USA.
Introduction: Serum cystatin C (CysC) is used to estimate glomerular filtration rate (eGFR), including in the Chronic Kidney Disease in Children (CKiD) Under 25 years (U25eGFR) equations. Several CysC measurement procedures available from diagnostic vendors include reference material for calibration, but the extent of heterogeneity across manufacturers is unclear. Since heterogeneity may have clinical and research implications for eGFR, we evaluated three CysC procedures in samples from the CKiD study representing a wide spectrum of kidney function.
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