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.
| Study ID | ST001162 |
| Study Title | Evaluation of computational tools using serial mixtures of human plasma and vegetable juice (part - II) |
| Study Summary | Mass 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 Name | Wang |
| First Name | Yating |
| Address | 615 Michael St. Ste 225, Atlanta, GA, 30322, USA |
| yating.wang@emory.edu | |
| Phone | 4047275091 |
| Submit Date | 2019-03-29 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | d |
| Analysis Type Detail | LC-MS |
| Release Date | 2019-05-15 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR000777 |
| Project DOI: | doi: 10.21228/M87T23 |
| Project Title: | Evaluation of computational tools using serial mixtures of human plasma and vegetable juice |
| Project Summary: | Mass 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 |
| Department: | School of Medicine |
| Laboratory: | Clinical Biomarker Laboratory |
| Last Name: | Wang |
| First Name: | Yating |
| Address: | 615 Michael St. Ste 225, Atlanta, GA, 30322, USA |
| Email: | yating.wang@emory.edu |
| Phone: | 4047275091 |
Subject:
| Subject ID: | SU001227 |
| Subject Type: | Other |
| Subject Species: | Homo sapiens |
| Species Group: | Mammals |
Factors:
Subject type: Other; Subject species: Homo sapiens (Factor headings shown in green)
| mb_sample_id | local_sample_id | Sample.Composition |
|---|---|---|
| SA080475 | 0-1_100v8 | food |
| SA080476 | 0-9_1_16_vq | food and human plasma |
| SA080477 | 0-10_1_64_vq | food and human plasma |
| SA080478 | 0-11_1_256_vq | food and human plasma |
| SA080479 | 0-12_1_1024_vq | food and human plasma |
| SA080480 | 0-8_1_4_vq | food and human plasma |
| SA080481 | 0-7_1_1_vq | food and human plasma |
| SA080482 | 0-2_1024_1_vq | food and human plasma |
| SA080483 | 0-3_256_1_vq | food and human plasma |
| SA080484 | 0-4_64_1_vq | food and human plasma |
| SA080485 | 0-6_4_1_vq | food and human plasma |
| SA080486 | 0-5_16_1_vq | food and human plasma |
| SA080487 | 0-13_100q3 | human plasma |
| Showing results 1 to 13 of 13 |
Collection:
| Collection ID: | CO001221 |
| Collection Summary: | Commercially available |
| Sample Type: | Blood (plasma) |
Treatment:
| Treatment ID: | TR001242 |
| Treatment Summary: | Samples were prepared by mixing commercially available vegetable juice and human plsama Qstandard. Smaples were mixed in the ratio of vegetable jucie to plasma at 1024:1, 256:1,64:1, 16:1, 4:1, 1:1, 1:4, 1:16, 1:256, 1:1024. Prior to analysis, samples were stored in -80 degree C. |
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). |
Combined analysis:
| Analysis ID | AN001921 | AN001922 |
|---|---|---|
| Analysis type | MS | MS |
| Chromatography type | HILIC | Reversed phase |
| Chromatography system | Agilent 6560 | Agilent 6560 |
| Column | Waters XBridge Amide (100 x 4.6mm,3.5um) | Thermo Accucore C18 (100 x 2.1mm,2.6um) |
| MS Type | ESI | ESI |
| MS instrument type | QTOF | QTOF |
| MS instrument name | Agilent 6560 Ion Mobility | Agilent 6560 Ion Mobility |
| Ion Mode | POSITIVE | POSITIVE |
| Units | Peak Area | Peak Area |
Chromatography:
| Chromatography ID: | CH001394 |
| Instrument Name: | Agilent 6560 |
| Column Name: | Waters XBridge Amide (100 x 4.6mm,3.5um) |
| Chromatography Type: | HILIC |
| Chromatography ID: | CH001395 |
| Instrument Name: | Agilent 6560 |
| Column Name: | Thermo Accucore C18 (100 x 2.1mm,2.6um) |
| Chromatography Type: | Reversed phase |
MS:
| MS ID: | MS001777 |
| Analysis ID: | AN001921 |
| Instrument Name: | Agilent 6560 Ion Mobility |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | Convert to mzXML format using MSConvert; XCMS R package was used to extract feature table |
| Ion Mode: | POSITIVE |
| MS ID: | MS001778 |
| Analysis ID: | AN001922 |
| Instrument Name: | Agilent 6560 Ion Mobility |
| Instrument Type: | QTOF |
| MS Type: | ESI |
| MS Comments: | Convert to mzXML format using MSConvert; XCMS R package was used to extract feature table |
| Ion Mode: | POSITIVE |
