Download MrR files
>> Peak Detecion
This is an R package for peak detection using Bayes factor and mixture probability models. msPeak can do peak detection for two GC-MS.
Kim, S.; Ouyang, M.; Jeong, J.; Shen, C.; Zhang, X. A New Method for Peak Detection on Comprehensive Two-dimensional Gas Chromatography Mass Spectrometry Data. Ann Appl Stat 2014, 8, 1209-1231.
This is an R package for peak detection using Normal-Gamma-Bernoulli models. msPeakG can do peak detection for two GC-MS.
Kim, S.; Jang, H.; Koo, I.; Lee, J.; Zhang, X. Normal-Gamma-Bernoulli Peak Detection for Analysis of Comprehensive Two-dimensional Gas Chromatography Mass Spectrometry Data. Comput Stat Data Anal. 2017. 105:96-111.
>> Peak Alignment
This is an R package for peak alignment on GCxGC-MS Data. mSPA can align homogeneous peaks based on mixture similarity measures.
Kim, S.; Fang, A.; Wang, B.; Jeong, J.; Zhang, X. An optimal peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using mixture similarity measure. Bioinformatics 2011, 27, 1660-1666.
This is an R package for peak alignment on GCxGC-MS Data. SWPA can align homogeneous and heterogenous peaks based on mixture similarity measures.
Kim, S.; Koo, I.; Fang, A.; Zhang, X. Smith-Waterman peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry. BMC Bioinformatics 2011, 12:235.
MbPA (Currently, upon request; Author: Dr. Jaesik Jeong):
This is an R package for peak alignment on GCxGC-MS Data. MbPA can align homogeneous peaks.
Jeong, J.; Shi, X.; Zhang, X.; Kim, S.; Shen, C. 2012. Model-based peak alignment of metabolomic profiling from comprehensive two-dimensional gas chromatography mass spectrometry. BMC Bioinformatics, 13:27.
ppmSPA (Currently, upon request):
This is an R package for peak alignment on GCxGC-MS Data using partial and semipartial correlations. ppmSPA can align homogeneous peaks.
Kim, S.; Zhang, X. 2013. Comparative Analysis of Mass Spectral Similarity Measures on Peak Alignment for Comprehensive Two-dimensional Gas Chromatography Mass Spectrometry. Comp. Math. Meth. Med. 2013, Article ID 509761.
This is an MATLAB package for global peak alignment on GCxGC-MS Data using point matching algorithms. coAlign can align homogeneous and hterogeneous peaks.
Deng, B.; Kim, S.; Li, H.; Heath, E.; Zhang, X. 2016. Global peak alignment for comprehensive two-dimensional gas chromatography mass spectrometry using point matching algorithms. J Bioinform Comput Biol. 14(6):1650032.
Li, Z.; Kim, S.; Zhong, S.; Zhong, Z.; Kato, I.; Zhang, X. 2020. Coherent point drift peak alignment algorithms using distance and similarity measures for two-dimensional gas chromatography-mass spectrometry data. Revision.
>> Peak Identification
mPP (Currently, upon request):
This is an R package for compound identification using mixture partial and part (semipartial) correlations. mPP can do compound identification using partial and part correlations.
Kim, S.; Koo, I.; Jeong, J.; Wu, S.; Shi, X.; Zhang, X. Compound identification using partial and semi-partial correlation on gas chromatography mass spectrometry data. Analytical Chemistry 2012, 84, 6477-6487.
This is an R package for finding optimal weight factors on compound identification. iOPT can find optimal weight factors to obtain more accurate identification.
Kim, S.; Koo, I.; Wei, X.; Zhang, X. A method of finding optimal weight factors for compound identification in gas chromatography mass spectrometry. Bioinformatics 2012, 28(8), 1158-1163.
eBID (Currently, upon request; Author: Dr. Jaesik Jeong):
This is an R package for compound identification. eBID can do compound identification using an empirical Bayes model.
Jeong, J.; Shi, X.; Kim, S.; Zhang, X.; Shen, C. 2011. An empirical Bayes model using a competition score for metabolite identification in gas chromatography mass spectrometry. BMC Bioinformatics, 12, 392.
iFDR (Currently, upon request):
This is an R package to control FDR in compound identification. iFDR can control False Identification Rate in compound identification using an empirical Beta model.
Kim S; Zhang X. Discovery of false identification using similarity difference in GC-MS based metabolomics. J Chemom 2015, 1, 80-86.
>> Post-hoc Analysis (Peak Alignment and Identification)
iPAD (Author: Dr. Jaesik Jeong):
This is an R package for post-hoc peak alignment on GCxGC-MS Data. iPAD can interatively align homogeneous peaks based on post-hoc analysis.
Jeong, J.; Zhang, X.; Kim, S.; Shen, C. An efficient post-hoc integration method improving peak alignment of GCxGC/TOF-MS with application to various metabolomics data. BMC Bioinfo. 2013, 14, 123.
>> Peak Network Construction
MetNet (Currently, upon request; Author: Dr. Imhoi Koo)
This is an R package for metabolite network constructions. MetNet can construct networks using PCR, ICR, PLSR, SCE, and ES methods.
Koo, I.; Wei, X.; Shi, X.; Kim, S.; Zhang, X. Constructing metabolic association networks using high-dimensional mass spectrometry data. Chemometr Intell Lab Syst. 2014, 138, 193-202.
netFDR (Currently, upon request)
This is an R package for various FDR control on metabolite network constructions.
Koo, I.; Sen, Y.; Zhang, X.; Kim, S. Comparative Analysis of False Discovery Rate Methods in Constructing Metabolic Association Networks. J Bioinform Comput Biol. 2014, 12, 1450018.