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ADAP-GC specifications

Information


Unique identifier OMICS_23699
Name ADAP-GC
Alternative name Automated Data Analysis Pipeline
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data Some raw mass spectrometry data.
Output data A sequence of data processing steps including construction of extracted ion chromatograms, detection of chromatographic peak features, deconvolution of co-eluting compounds, and alignment of compounds across samples.
Operating system Unix/Linux, Mac OS, Windows
Programming languages Java
Computer skills Advanced
Stability Stable
Maintained Yes

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Versioning


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Maintainer


  • person_outline Xiuxia Du

Publications for Automated Data Analysis Pipeline

ADAP-GC citations

 (8)
library_books

Analytical challenges of untargeted GC MS based metabolomics and the critical issues in selecting the data processing strategy

2017
F1000Res
PMCID: 5553085
PMID: 28868138
DOI: 10.5256/f1000research.12777.r23714

[…] was, however, far from perfect. Nevertheless, the interface of Profinder permitted a user-friendly visual inspection and manual correction that other similar software tools (including MS-DIAL, eRah, ADAP-GC, metaMS and MassOmics) did not provide. By manually correcting the inconsistency of data extraction (carefully selecting the exact region of the corresponding peak), an error-free data extract […]

library_books

From chromatogram to analyte to metabolite. How to pick horses for courses from the massive web resources for mass spectral plant metabolomics

2017
GigaScience
PMCID: 5499862
PMID: 28520864
DOI: 10.1093/gigascience/gix037

[…] ADAP: Automated Data Analysis Pipeline for Untargeted Metabolomics; AIST: National Institute of Advanced Industrial Science and Technology; ALEX: Analysis of Lipid Experiments; AMDIS: Automated Mass Spectra […]

library_books

Essential functions linked with structural disorder in organisms of minimal genome

2016
Biol Direct
PMCID: 5016991
PMID: 27608806
DOI: 10.1186/s13062-016-0149-y

[…] y the proteins of a respective plasmid. Although there are mistakes that are easy to identify and filter out, there are also less shouting annotation mistakes that would not necessarily pop up in the automated data analysis pipeline used here, so we decided to use the smaller but better annotated, more trustworthy CMT15 dataset. For the proteomes that we use, the genes and proteins are also well a […]

library_books

Looking for a Signal in the Noise: Revisiting Obesity and the Microbiome

2016
MBio
PMCID: 4999546
PMID: 27555308
DOI: 10.1128/mBio.01018-16

[…] l of the data sets and relied heavily on the availability of public data and access to metadata that included variables beyond the needs of the original study. To execute this analysis, we created an automated data analysis pipeline, which can be easily updated to add additional studies as they become available (https://github.com/SchlossLab/Sze_Obesity_mBio_2016/). Similarly, it would be possible […]

library_books

Discovery of A type procyanidin dimers in yellow raspberries by untargeted metabolomics and correlation based data analysis

2016
Metabolomics
PMCID: 5047924
PMID: 27547172
DOI: 10.1007/s11306-016-1090-x

[…] acid. This assumption as well as the pseudospectra obtained using the semiautomatic method, was further validated by MS/MS of the heavier ions.Without the use of untargeted metabolomics and a proper automated data analysis pipeline it would be almost impossible to find these compounds, which are not present in massive amounts among all the other features. The fact that the compounds have a relati […]

library_books

Analysis of Reverse Phase Protein Array Data: From Experimental Design towards Targeted Biomarker Discovery

2015
Microarrays
PMCID: 4996411
PMID: 27600238
DOI: 10.3390/microarrays4040520

[…] PA slides.A considerable disadvantage of the visual inspection is a high degree of examiner variability that might produce inconsistent results. Ju and coauthors tackled this problem by setting up an automated data analysis pipeline []. Inspection of RPPA images relies on a generalized linear model as a logit to a logistic function returning a likelihood factor that represents slide quality. Evalu […]

Citations

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ADAP-GC institution(s)
University of North Carolina at Charlotte, Charlotte, NC, USA; University of Hawaii Cancer Center, Honolulu, HI, USA; Emory University, Atlanta, GA, USA
ADAP-GC funding source(s)
Supported by the National Science Foundation (NSF) Award 1262416, National Institute of Environmental Health Sciences (NIEHS) P50ES026071, P30ES019116, U2CES026560, and the United States Environmental Protection Agency (EPA) 83615301.

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