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.

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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

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Factors:

Subject type: Other; Subject species: Homo sapiens (Factor headings shown in green)

mb_sample_id local_sample_id Sample.Composition
SA0804750-1_100v8food
SA0804760-9_1_16_vqfood and human plasma
SA0804770-10_1_64_vqfood and human plasma
SA0804780-11_1_256_vqfood and human plasma
SA0804790-12_1_1024_vqfood and human plasma
SA0804800-8_1_4_vqfood and human plasma
SA0804810-7_1_1_vqfood and human plasma
SA0804820-2_1024_1_vqfood and human plasma
SA0804830-3_256_1_vqfood and human plasma
SA0804840-4_64_1_vqfood and human plasma
SA0804850-6_4_1_vqfood and human plasma
SA0804860-5_16_1_vqfood and human plasma
SA0804870-13_100q3human plasma
Showing results 1 to 13 of 13
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