TY - JOUR
T1 - EIder
T2 - A compound identification tool for gas chromatography mass spectrometry data
AU - Koo, Imhoi
AU - Kim, Seongho
AU - Shi, Biyun
AU - Lorkiewicz, Pawel
AU - Song, Ming
AU - McClain, Craig
AU - Zhang, Xiang
N1 - Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2016/5/27
Y1 - 2016/5/27
N2 - We report software entitled EIder (EI mass spectrum identifier) that provides users with eight literature reported spectrum matching algorithms for compound identification from gas chromatography mass spectrometry (GC-MS) data. EIder calculates retention index according to experimental conditions categorized by column class, column type and data type, where 9 empirical distribution functions of the absolute retention index deviation to its mean value were constructed using the National Institute of Standards and Technology (NIST) 2011 retention index database to improve the accuracy of compound identification. EIder filters compound candidates based on elementary composition and derivatization reagent, and automatically adds the molecular information of the native compound to each derivatized compound using a manually created database. When multiple samples are analyzed together, EIder performs cross-sample alignment and provides an option of using an average mass spectrum for compound identification. Furthermore, a suite of graphical user interfaces are implemented in EIder to allow users to both manually and automatically modify the identification results using experimental information at various analysis stages. Analysis of three types of GC-MS datasets indicates that the developed EIder software can improve the accuracy of compound identification.
AB - We report software entitled EIder (EI mass spectrum identifier) that provides users with eight literature reported spectrum matching algorithms for compound identification from gas chromatography mass spectrometry (GC-MS) data. EIder calculates retention index according to experimental conditions categorized by column class, column type and data type, where 9 empirical distribution functions of the absolute retention index deviation to its mean value were constructed using the National Institute of Standards and Technology (NIST) 2011 retention index database to improve the accuracy of compound identification. EIder filters compound candidates based on elementary composition and derivatization reagent, and automatically adds the molecular information of the native compound to each derivatized compound using a manually created database. When multiple samples are analyzed together, EIder performs cross-sample alignment and provides an option of using an average mass spectrum for compound identification. Furthermore, a suite of graphical user interfaces are implemented in EIder to allow users to both manually and automatically modify the identification results using experimental information at various analysis stages. Analysis of three types of GC-MS datasets indicates that the developed EIder software can improve the accuracy of compound identification.
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U2 - 10.1016/j.chroma.2016.04.064
DO - 10.1016/j.chroma.2016.04.064
M3 - Article
C2 - 27131963
AN - SCOPUS:84992302391
SN - 0021-9673
VL - 1448
SP - 107
EP - 114
JO - Journal of Chromatography A
JF - Journal of Chromatography A
ER -