Summary of Study ST001028
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 PR000686. The data can be accessed directly via it's Project DOI: 10.21228/M80Q2W 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 | ST001028 |
| Study Title | Metabolic profiling of identified single cells in Xenopus laevis embryos |
| Study Type | Metabolic profiling of single cells |
| Study Summary | Single D11 cells were identified in 16-cell embryos of Xenopus laevis. Metabolites were extracted, and the extracts were analyzed using a custom-built capillary electrophoresis electrospray ionization platform coupled to a quadrupole time-of-flight mass spectrometer. The resulting metadata was analyzed by Trace, a custom-design software, designed to extract molecular feautres from trace-sensitive metabolomics experiments. The results were validated against molecular features that were extracted by manual curation of the same raw mass spectrometer files. |
| Institute | University of Maryland |
| Department | Department of Chemistry & Biochemistry |
| Laboratory | Nemes Laboratory |
| Last Name | Nemes |
| First Name | Peter |
| Address | 0107 Chemistry Building, 8051 Regents Dr, College Park, MD 20742 |
| nemes@umd.edu | |
| Phone | 3014050373 |
| Submit Date | 2018-07-25 |
| Num Groups | 5 biological replicates (different cells from different embryos) + 1-to-3 technical replicates (same extract analyzed multiple times) |
| Total Subjects | 5 different D11 cells were analyzed, each from a different embryo |
| Publications | Trace: Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry – A Case Study from Single-Cell Metabolomics |
| Raw Data Available | Yes |
| Raw Data File Type(s) | mzML |
| Analysis Type Detail | LC-MS |
| Release Date | 2019-09-23 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR000686 |
| Project DOI: | doi: 10.21228/M80Q2W |
| Project Title: | Trace: Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry – A Case Study from Single-Cell Metabolomics |
| Project Type: | Study from Single-Cell Metabolomics |
| Project Summary: | The goal of this study was to validate the performance of a custom-written software tool, called Trace, for finding molecular features from ultrasensitive metabolomics experiments using high-resolution mass spectrometry. The software uses a trained neural network model to extract molecular features. As model for validation, we performed MS profiling of single identified cells from early developing embryos of the South African clawed frog (Xenopus laevis) using a custom-built capillary electrophoresis electrospray ionization platform coupled to a quadrupole time-of-flight mass spectrometer. The MS dataset from these measurements was manually curated for molecular features, and the resulting list of molecular features were used to test the robustness and accuracy of Trace at predicting molecular features that were detected from the single cells. |
| Institute: | University of Maryland |
| Department: | Department of Chemistry & Biochemistry |
| Laboratory: | Nemes Laboratory |
| Last Name: | Nemes |
| First Name: | Peter |
| Address: | 0107 Chemistry Building, 8051 Regents Dr, College Park, MD 20742 |
| Email: | nemes@umd.edu |
| Phone: | 301-405-0373 |
| Funding Source: | National Cancer Institute award no. 7R03CA211635 |
| Publications: | Trace: Machine Learning of Signal Images for Trace-Sensitive Mass Spectrometry – A Case Study from Single-Cell Metabolomics |
