update

01-introduction.Rmd

@@ -10,7 +10,7 @@ Information in living organism communicates along the Central Dogma in different
 knitr::include_graphics('images/metaintro.png')
 ```
 
-Metabolomics studies always employ GC-MS[@theodoridis2012; @beale2018], GC\*GC-MS[@tian2016], LC-MS[@gika2014], LC-MS/MS[@begou2017a], IM-MS[@levy2019], infrared ion spectroscopy[@martens2017] or NMR[\@b.dunn2011] to measure metabolites. For analytical methods, this review could be checked[@zhang2012]. The overall technique progress of metabolomics (2012-2018) could be found here[@miggiels2019]. However, this workflow will only cover mass spectrometry based metabolomics or XC-MS based research.
+Metabolomics studies always employ GC-MS[@theodoridis2012; @beale2018], GC\*GC-MS[@tian2016], LC-MS[@gika2014], LC-MS/MS[@begou2017], IM-MS[@levy2019], infrared ion spectroscopy[@martens2017] or NMR[\@b.dunn2011] to measure metabolites. For analytical methods, this review could be checked[@zhang2012e]. The overall technique progress of metabolomics (2012-2018) could be found here[@miggiels2019]. However, this workflow will only cover mass spectrometry based metabolomics or XC-MS based research.
 
 ## History
 
@@ -82,13 +82,13 @@ Some nice reviews and tutorials related to this workflow could be found in those
 
 ### Workflow
 
-Those papers are recommended[@gonzález-riano2020; @pezzatti2020; @liu2019; @barnes2016a; @cajka2016; @gika2014; @theodoridis2012; @lu2008; @fiehn2002] for general metabolomics related topics.
+Those papers are recommended[@gonzalez-riano2020; @pezzatti2020; @liu2019; @barnes2016a; @cajka2016; @gika2014; @theodoridis2012; @lu2008; @fiehn2002] for general metabolomics related topics.
 
--   For targeted metabolomics, you could check those reviews[@griffiths2010a; @lu2008a; @weljie2006; @yuan2012; @zhou2016b; @begou2017b].
+-   For targeted metabolomics, you could check those reviews[@griffiths2010; @lu2008a; @weljie2006; @yuan2012; @zhou2016; @begou2017].
 
 ### Data analysis
 
-You could firstly read those papers[@barnes2016; @kusonmano2016a; @madsen2010a; @uppal2016a; @alonso2015] to get the concepts and issues for data analysis in metabolomics. Then this paper[@gromski2015a] could be treated as a step-by-step tutorial. For GC-MS based metabolomics, check this paper[@rey-stolle2022].
+You could firstly read those papers[@barnes2016; @kusonmano2016; @madsen2010; @uppal2016; @alonso2015] to get the concepts and issues for data analysis in metabolomics. Then this paper[@gromski2015] could be treated as a step-by-step tutorial. For GC-MS based metabolomics, check this paper[@rey-stolle2022].
 
 -  A guide could be used choose a inofrmatics software and tools for lipidomics[@ni2022].
 
@@ -115,19 +115,19 @@ Here is the slides for metabolomics data analysis workshop and I have made prese
 
 ### Application
 
--   For environmental research related metabolomics or exposome, check those papers[@matich2019a; @tang2020; @warth2017; @bundy2009].
+-   For environmental research related metabolomics or exposome, check those papers[@matich2019; @tang2020; @warth2017; @bundy2009].
 
 -   For toxicology, check this paper[@viant2019].
 
 -   Check this piece[@wishart2016] for drug discovery and precision medicine.
 
--   For food chemistry, check this paper[@castro-puyana2017], this paper for livestock[@goldansaz2017] and those papers for nutrition[@allam-ndoul2016; @jones2012; @müller2020a].
+-   For food chemistry, check this paper[@castro-puyana2017], this paper for livestock[@goldansaz2017] and those papers for nutrition[@allam-ndoul2016; @jones2012; @muller2020].
 
 -   For disease related metabolomics such as oncology[@spratlin2009], Cardiovascular[@cheng2017] . This paper[@kennedy2018] cover the metabolomics realted clinic research.
 
--   For plant science, check those paper[@sumner2003; @jorge2016a; @hansen2018a].
+-   For plant science, check those paper[@sumner2003; @jorge2016a; @hansen2018].
 
--   For single cell metabolomics analysis, check here[@fessenden2016; @zenobi2013; @ali2019a; @hansen2018].
+-   For single cell metabolomics analysis, check here[@fessenden2016; @zenobi2013; @ali2019; @hansen2018].
 
 -   For gut microbiota, check here[@smirnov2016].
 
@@ -137,13 +137,13 @@ General challenge for metabolomics studies could be found here [@schymanski2017;
 
 -   For reproducible research, check those papers [@du2022; @place2021; @verhoeven2020; @mangul2019; @wallach2018; @hites2018; @considine2017; @sarpe2017]. To match data from different LC system, [M2S](https://github.com/rjdossan/M2S) could be used[@climacopinto2022].
 
--   Quantitative Metabolomics related issues could be found here[@kapoore2016b; @jorge2016aa; @lv2022; @vitale2022].
+-   Quantitative Metabolomics related issues could be found here[@kapoore2016b; @jorge2016a; @lv2022; @vitale2022].
 
 -   For quality control issues, check here[@dudzik2018; @siskos2017; @sumner2007; @place2021]. You might also try postcolumn infusion as a quality control tool[@gonzalez2022].
 
 ## Trends in Metabolomics
 
-```{r rentrez}
+```{r rentrez, eval=F}
 library(rentrez)
 papers_by_year <- function(years, search_term){
     return(sapply(years, function(y) entrez_search(db="pubmed",term=search_term, mindate=y, maxdate=y, retmax=0)$count))

03-pretreatment.Rmd

@@ -68,6 +68,6 @@ For gut microbiota, this paper could be checked for storage issue[@zubeldia-vare
 
 For blood sample storage, you could check this paper[@hernandes2017].
 
-For urine sample storage, check this[@laparre2017a].
+For urine sample storage, check this[@laparre2017].
 
 This piece reviewed the stability of energy metabolites[@gil2015].

04-instrumental.Rmd

@@ -20,4 +20,4 @@ For metabolomics, high resolution mass spectrum should be used to make identific
 
 ## Matrix effects
 
-Matrix effects could decrease the sensitivity of untargeted analysis. Such matrix effects could be checked by low resolution mass spectrometry[@yu2017a] and found for high resolution mass spectrometry[@calbiani2006]. Ion suppression should also be considered as a critical issue comparing heterogeneous metabolic profiles[@ghosson2021].
+Matrix effects could decrease the sensitivity of untargeted analysis. Such matrix effects could be checked by low resolution mass spectrometry[@yu2017] and found for high resolution mass spectrometry[@calbiani2006]. Ion suppression should also be considered as a critical issue comparing heterogeneous metabolic profiles[@ghosson2021].

05-workflow.Rmd

@@ -15,7 +15,7 @@ download.file(js_cdn_url, dist_loc)
 
 # Workflow
 
-You could check this book for metabolomics data analysis [@li2020].
+You could check this book for metabolomics data analysis [@li2020a].
 
 ```{r}
 DiagrammeR::mermaid("
@@ -55,39 +55,39 @@ Check those papers for the XCMS based workflow[@forsberg2018; @huan2017; @mahieu
 
 compMS2Miner is an Automatable Metabolite Identification, Visualization, and Data-Sharing R Package for High-Resolution LC--MS Data Sets. Here is related papers [@edmands2017; @edmands2018; @edmands2015].
 
-mzMatch is a modular, open source and platform independent data processing pipeline for metabolomics LC/MS data written in the Java language, which could be coupled with xcms [@scheltema2011a; @creek2012b]. It also could be used for annotation with MetAssign[@daly2014].
+mzMatch is a modular, open source and platform independent data processing pipeline for metabolomics LC/MS data written in the Java language, which could be coupled with xcms [@scheltema2011; @creek2012]. It also could be used for annotation with MetAssign[@daly2014].
 
 ### PRIMe
 
 [PRIMe](http://prime.psc.riken.jp/Metabolomics_Software/) is from RIKEN and UC Davis. They update their database frequently[@tsugawa2016]. It supports mzML and major MS vendor formats. They defined own file format ABF and eco-system for omics studies. The software are updated almost everyday. You could use MS-DIAL for untargeted analysis and MRMOROBS for targeted analysis. For annotation, they developed MS-FINDER and statistic tools with excel. This platform could replaced the dear software from company and well prepared for MS/MS data analysis and lipidomics. They are open source, work on Windows and also could run within mathmamtics. However, they don't cover pathway analysis. Another feature is they always show the most recently spectral records from public repositories. You could always get the updated MSP spectra files for your own data analysis.
 
-For PRIMe based workflow, check those papers[@lai2018; @matsuo2017; @treutler2016; @tsugawa2015a; @tsugawa2016; @kind2018]. There are also extensions for their workflow[@uchino2022].
+For PRIMe based workflow, check those papers[@lai2018; @matsuo2017; @treutler2016; @tsugawa2015; @tsugawa2016; @kind2018]. There are also extensions for their workflow[@uchino2022].
 
 ### GNPS
 
-[GNPS](http://gnps.%20ucsd.edu) is an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. It's a straight forward annotation methods for MS/MS data. Feature-based molecular networking (FBMN) within GNPS could be coupled with xcms, openMS, MS-DIAL, MZmine2, and other popular software. GNPS also have a dashboard for online mass spectrometery data [analysis\$\$\@petras2021a](mailto:analysis$$@petras2021a){.email}\$\$.
+[GNPS](http://gnps.%20ucsd.edu) is an open-access knowledge base for community-wide organization and sharing of raw, processed or identified tandem mass (MS/MS) spectrometry data. It's a straight forward annotation methods for MS/MS data. Feature-based molecular networking (FBMN) within GNPS could be coupled with xcms, openMS, MS-DIAL, MZmine2, and other popular software. GNPS also have a dashboard for online mass spectrometery data analysis[@petras2021a].
 
-Check those papers for GNPS and related projects[@aron2020a; @nothias2020; @scheubert2017; @silva2018; @wang2016].
+Check those papers for GNPS and related projects[@aron2020; @nothias2020; @scheubert2017; @silva2018; @wang2016b].
 
 ### OpenMS & SIRIUS
 
 [OpenMS](https://www.openms.de/) is another good platform for mass spectrum data analysis developed with C++. You could use them as plugin of [KNIME](https://www.knime.org/). I suggest anyone who want to be a data scientist to get familiar with platform like KNIME because they supplied various API for different programme language, which is easy to use and show every steps for others. Also TOPPView in OpenMS could be the best software to visualize the MS data. You could always use the metabolomics workflow to train starter about details in data processing. pyOpenMS and OpenSWATH are also used in this platform. If you want to turn into industry, this platform fit you best because you might get a clear idea about solution and workflow.
 
-Check those paper for OpenMS based workflow[@bertsch2011; @pfeuffer2017; @röst2014; @rost2016a; @rurik2020; @alka2020].
+Check those paper for OpenMS based workflow[@bertsch2011; @pfeuffer2017; @rost2014; @rost2016; @rurik2020; @alka2020].
 
-OpenMS could be coupled to SIRIUS 4 for annotation. [Sirius](https://bio.informatik.uni-jena.de/software/sirius/) is a new java-based software framework for discovering a landscape of de-novo identification of metabolites using single and tandem mass spectrometry. SIRIUS 4 project integrates a collection of our tools, including [CSI:FingerID](https://www.csi-fingerid.uni-jena.de/), [ZODIAC](https://bio.informatik.uni-jena.de/software/zodiac/) and [CANOPUS](https://bio.informatik.uni-jena.de/software/canopus/). Check those papers for SIRIUS based workflow[@dührkop2019; @dührkop2020; @alka2020a; @ludwig2020].
+OpenMS could be coupled to SIRIUS 4 for annotation. [Sirius](https://bio.informatik.uni-jena.de/software/sirius/) is a new java-based software framework for discovering a landscape of de-novo identification of metabolites using single and tandem mass spectrometry. SIRIUS 4 project integrates a collection of our tools, including [CSI:FingerID](https://www.csi-fingerid.uni-jena.de/), [ZODIAC](https://bio.informatik.uni-jena.de/software/zodiac/) and [CANOPUS](https://bio.informatik.uni-jena.de/software/canopus/). Check those papers for SIRIUS based workflow[@duhrkop2019; @duhrkop2020a; @alka2020; @ludwig2020].
 
 ### MZmine 2
 
 [MZmine 2](http://mzmine.github.io/) has three version developed on Java platform and the lastest version is included into [MSDK](https://msdk.github.io/). Similar function could be found from MZmine 2 as shown in XCMS online. However, MZmine 2 do not have pathway analysis. You could use metaboanalyst for that purpose. Actually, you could go into MSDK to find similar function supplied by [ProteoSuite](http://www.proteosuite.org) and [Openchrom](https://www.openchrom.net/). If you are a experienced coder for Java, you should start here.
 
-Check those papers for MZmine based workflow[@pluskal2010a; @pluskal2020].
+Check those papers for MZmine based workflow[@pluskal2010; @pluskal2020].
 
 ### Emory MaHPIC
 
 This platform is composed by several R packages from Emory University including [apLCMS](https://sourceforge.net/projects/aplcms/) to collect the data, [xMSanalyzer](https://sourceforge.net/projects/xmsanalyzer/) to handle automated pipeline for large-scale, non-targeted metabolomics data, [xMSannotator](https://sourceforge.net/projects/xmsannotator/) for annotation of LC-MS data and [Mummichog](https://code.google.com/archive/p/atcg/wikis/mummichog_for_metabolomics.wiki) for pathway and network analysis for high-throughput metabolomics. This platform would be preferred by someone from environmental science to study exposome.
 
-You could check those papers for Emory workflow[@uppal2013a; @uppal2017; @yu2009a; @li2013; @liu2020].
+You could check those papers for Emory workflow[@uppal2013; @uppal2017; @yu2009b; @li2013; @liu2020].
 
 ### Others
 
@@ -97,13 +97,13 @@ You could check those papers for Emory workflow[@uppal2013a; @uppal2017; @yu2009
 
 - [R for mass spectrometry](https://www.rformassspectrometry.org/) is a R software collection for the analysis and interpretation of high throughput mass spectrometry assays.
 
--   [MAVEN](http://genomics-pubs.princeton.edu/mzroll/index.php?show=index) from Princeton University [@melamud2010a; @clasquin2012].
+-   [MAVEN](http://genomics-pubs.princeton.edu/mzroll/index.php?show=index) from Princeton University [@melamud2010; @clasquin2012].
 
 -   [metabolomics](https://github.com/cran/metabolomics) is a CRAN package for analysis of metabolomics data.
 
 -   [autoGCMSDataAnal](http://software.tobaccodb.org/software/autogcmsdataanal) is a Matlab based comprehensive data analysis strategy for GC-MS-based untargeted metabolomics and [AntDAS2](http://software.tobaccodb.org/software/antdas2) provided An automatic data analysis strategy for UPLC-HRMS-based metabolomics[@yu2019; @zhang2020].
 
--   [enviGCMS](https://github.com/yufree/enviGCMS) from environmental non-targeted analysis and [rmwf](https://github.com/yufree/rmwf) for reproducible metabolomics workflow [@yu2020a; @yu2019a].
+-   [enviGCMS](https://github.com/yufree/enviGCMS) from environmental non-targeted analysis and [rmwf](https://github.com/yufree/rmwf) for reproducible metabolomics workflow [@yu2020; @yu2019a].
 
 -   Pseudotargeted metabolomics method [@zheng2020; @wang2016a].
 
@@ -113,7 +113,7 @@ You could check those papers for Emory workflow[@uppal2013a; @uppal2017; @yu2009
 
 -   [MetaboliteDetector](https://md.tu-bs.de/) is a QT4 based software package for the analysis of GC/MS based metabolomics data [@hiller2009].
 
--   [W4M](http://workflow4metabolomics.org/) and [metaX](http://metax.genomics.cn/) could analysis data online [@giacomoni2015; @wen2017a; @jalili2020a].
+-   [W4M](http://workflow4metabolomics.org/) and [metaX](http://metax.genomics.cn/) could analysis data online [@giacomoni2015; @wen2017; @jalili2020].
 
 -   [FTMSVisualization](https://github.com/wkew/FTMSVisualization) is a suite of tools for visualizing complex mixture FT-MS data [@kew2017]
 
@@ -139,7 +139,7 @@ You could check those papers for Emory workflow[@uppal2013a; @uppal2017; @yu2009
 
 ### Workflow Comparison
 
-Here are some comparisons for different workflow and you could make selection based on their works[@myers2017; @weber2017; @li2018].
+Here are some comparisons for different workflow and you could make selection based on their works[@myers2017; @weber2017; @li2018a].
 
 [xcmsrocker](https://github.com/yufree/xcmsrocker) is a docker image for metabolomics to compare R based software with template[@yu2022b].
 
@@ -177,4 +177,4 @@ See this paper[@haug2017]:
 
 ## Contest
 
--   [CASMI](http://www.casmi-contest.org/) predict small molecular contest[@blaenovi2017]
+-   [CASMI](http://www.casmi-contest.org/) predict small molecular contest[@blazenovic2017]