Summary of Study ST001162

This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR000777. The data can be accessed directly via it's Project DOI: 10.21228/M87T23 This work is supported by NIH grant, U2C- DK119886.

See: https://www.metabolomicsworkbench.org/about/howtocite.php

This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.

Show all samples  |  Perform analysis on untargeted data  
Download mwTab file (text)   |  Download mwTab file(JSON)   |  Download data files (Contains raw data)
Study IDST001162
Study TitleEvaluation of computational tools using serial mixtures of human plasma and vegetable juice (part - II)
Study SummaryMass spectrometry-based metabolomics is developed rapidly in the past few decades. There are few major vendors for LC-MS platform instruments, for example, Thermo ScientificTM LTQ Orbitrap Velos and Agilent 6510 Q-TOF mass spectrometer were used for metabolomics research. The data acquired cross different platform are rarely compared other than the comparison of the instrument itself on resolution, mass accuracy, sensitivity, dynamic range, scan speed etc., which is largely due to the foundation and principle of the instrument design. Other than this, there are many choice for data preprocessing, i.e., the data acquired from the same platform may have been processed with different feature extraction software tools. The discrepancy for the feature detections with different software will lead to the variation of the down-stream statistics analysis and metabolomics pathway interpretation. In addition, the impact of the LC-MS platform and data preprocessing software tools on the quantitative capabilities is also an interesting topic. In this research, XCMS, mzMine 2.37 and apLCMS are three tools used for the feature extraction of data acquired with Thermo ScientificTM LTQ Orbitrap Velos and Agilent 6510 Q-TOF LC-MS platform by serial dilution experiment. The quantification capability is estimated at the same time based on the linearity, accuracy, and precision.
Institute
Emory University
Last NameWang
First NameYating
Address615 Michael St. Ste 225, Atlanta, GA, 30322, USA
Emailyating.wang@emory.edu
Phone4047275091
Submit Date2019-03-29
Raw Data AvailableYes
Raw Data File Type(s)d
Analysis Type DetailLC-MS
Release Date2019-05-15
Release Version1
Yating Wang Yating Wang
https://dx.doi.org/10.21228/M87T23
ftp://www.metabolomicsworkbench.org/Studies/ application/zip

Select appropriate tab below to view additional metadata details:


Sample Preparation:

Sampleprep ID:SP001235
Sampleprep Summary:Samples were prepared for metabolomics analysis using established methods(Johnson et al. (2010). Analyst; Go et al. (2015). Tox Sci). Prior to analysis, plasma aliquots were removed from storage at -80 degrees C and thawed on ice. Each cryotube was then vortexed briefly to ensure homogeneity, and 50 microliters was transferred to a clean microfuge tube. Immediately after, the plasma was treated with 100 microliters of ice-cold LC-MS grade acetonitrile(Sigma Aldrich) containing 2.5 microliters of internal standard solution with eleven stable isotopic chemicals selected to cover a range of chemical properties. Following addition of acetonitrile, samples were equilibrated for 30 min on ice, upon which precipitated proteins were removed by centrifuge (14,000rpm at 4 degrees C for 10 min). The resulting supernatant (100 microliters) was removed, added to a low volume autosampler vial and maintained at 4 degrees C until analysis (<22 h).
  logo