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{"title"=>"Analysis of lipid experiments (ALEX): A software framework for analysis of high-resolution shotgun lipidomics data", "type"=>"journal", "authors"=>[{"first_name"=>"Peter", "last_name"=>"Husen", "scopus_author_id"=>"54079802900"}, {"first_name"=>"Kirill", "last_name"=>"Tarasov", "scopus_author_id"=>"56432603600"}, {"first_name"=>"Maciej", "last_name"=>"Katafiasz", "scopus_author_id"=>"56002059100"}, {"first_name"=>"Elena", "last_name"=>"Sokol", "scopus_author_id"=>"47861355000"}, {"first_name"=>"Johannes", "last_name"=>"Vogt", "scopus_author_id"=>"36007822500"}, {"first_name"=>"Jan", "last_name"=>"Baumgart", "scopus_author_id"=>"24173213100"}, {"first_name"=>"Robert", "last_name"=>"Nitsch", "scopus_author_id"=>"7102628210"}, {"first_name"=>"Kim", "last_name"=>"Ekroos", "scopus_author_id"=>"7801498190"}, {"first_name"=>"Christer S.", "last_name"=>"Ejsing", "scopus_author_id"=>"8351864800"}], "year"=>2013, "source"=>"PLoS ONE", "identifiers"=>{"pui"=>"372116773", "sgr"=>"84892416577", "issn"=>"19326203", "pmid"=>"24244551", "scopus"=>"2-s2.0-84892416577", "doi"=>"10.1371/journal.pone.0079736", "isbn"=>"1932-6203 (Electronic)\\r1932-6203 (Linking)"}, "id"=>"c3f1251a-e443-3743-9975-7ce29111355d", "abstract"=>"Global lipidomics analysis across large sample sizes produces high-content datasets that require dedicated software tools supporting lipid identification and quantification, efficient data management and lipidome visualization. Here we present a novel software-based platform for streamlined data processing, management and visualization of shotgun lipidomics data acquired using high-resolution Orbitrap mass spectrometry. The platform features the ALEX framework designed for automated identification and export of lipid species intensity directly from proprietary mass spectral data files, and an auxiliary workflow using database exploration tools for integration of sample information, computation of lipid abundance and lipidome visualization. A key feature of the platform is the organization of lipidomics data in \"database table format\" which provides the user with an unsurpassed flexibility for rapid lipidome navigation using selected features within the dataset. To demonstrate the efficacy of the platform, we present a comparative neurolipidomics study of cerebellum, hippocampus and somatosensory barrel cortex (S1BF) from wild-type and knockout mice devoid of the putative lipid phosphate phosphatase PRG-1 (plasticity related gene-1). The presented framework is generic, extendable to processing and integration of other lipidomic data structures, can be interfaced with post-processing protocols supporting statistical testing and multivariate analysis, and can serve as an avenue for disseminating lipidomics data within the scientific community. The ALEX software is available at www.msLipidomics.info.", "link"=>"http://www.mendeley.com/research/analysis-lipid-experiments-alex-software-framework-analysis-highresolution-shotgun-lipidomics-data", "reader_count"=>85, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Professor > Associate Professor"=>6, "Librarian"=>1, "Researcher"=>25, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>29, "Student > Postgraduate"=>1, "Student > Master"=>6, "Other"=>2, "Student > Bachelor"=>11, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Professor > Associate Professor"=>6, "Librarian"=>1, "Researcher"=>25, "Student > Doctoral Student"=>1, "Student > Ph. D. Student"=>29, "Student > Postgraduate"=>1, "Student > Master"=>6, "Other"=>2, "Student > Bachelor"=>11, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>4, "Engineering"=>1, "Biochemistry, Genetics and Molecular Biology"=>15, "Agricultural and Biological Sciences"=>31, "Medicine and Dentistry"=>7, "Pharmacology, Toxicology and Pharmaceutical Science"=>1, "Physics and Astronomy"=>1, "Chemistry"=>22, "Social Sciences"=>1, "Computer Science"=>2}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>7}, "Chemistry"=>{"Chemistry"=>22}, "Social Sciences"=>{"Social Sciences"=>1}, "Physics and Astronomy"=>{"Physics and Astronomy"=>1}, "Agricultural and Biological Sciences"=>{"Agricultural and Biological Sciences"=>31}, "Computer Science"=>{"Computer Science"=>2}, "Biochemistry, Genetics and Molecular Biology"=>{"Biochemistry, Genetics and Molecular Biology"=>15}, "Unspecified"=>{"Unspecified"=>4}, "Pharmacology, Toxicology and Pharmaceutical Science"=>{"Pharmacology, Toxicology and Pharmaceutical Science"=>1}}, "reader_count_by_country"=>{"Sweden"=>1, "Austria"=>3, "United States"=>1, "Finland"=>1, "Denmark"=>2, "Brazil"=>1, "United Kingdom"=>1, "Switzerland"=>1}, "group_count"=>3}

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• {"files"=>["https://ndownloader.figshare.com/files/1397150"], "description"=>"<p>The ALEX framework comprises six core modules (grey colored boxes). The function of each module is explained in the Results and Discussion section. The output of the ALEX framework includes a data file with identified lipid species, intensities and accessory lipid features across all processed samples and FT MS scan ranges. The ALEX output is organized in database table format that can be accessed and processed by the auxiliary workflow using Orange and Tableau software. The auxiliary workflow is designed to integrate sample information, compute lipid molar abundance, implement quality control procedures and visualize lipidome data.</p>", "links"=>[], "tags"=>["alex", "auxiliary"], "article_id"=>943432, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079736.g001", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Overview_of_the_ALEX_software_framework_and_auxiliary_workflow_/943432", "title"=>"Overview of the ALEX software framework and auxiliary workflow.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-07 07:13:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1397151"], "description"=>"<p>(<b>A</b>) Representative positive ion mode FT MS spectrum of a 10:1-phase lipid extract of hippocampus from a PRG-1 knockout mouse. Note that the detection of selected lock mass ions tris(ditert-butylphenyl) phosphate (chemical background, [M+NH₄]⁺, calculated <i>m/z</i> 680.48022, measured <i>m</i>/<i>z</i> 680.47945, <i>m</i>/<i>z</i> offset = -0.00077) and TAG 17:1/17:1/17:1 (internal standard (IS), [M+NH₄]⁺, calculated <i>m/z</i> 860.77017, measured <i>m</i>/<i>z</i> 860.76889 and <i>m</i>/<i>z</i> offset = -0.00128). The FT MS calibration offset is estimated as the average of the <i>m/z</i> offset for both lock mass ions, i.e. the FT MS calibration offset = -0.0010. (<b>B</b>) Screenshot of the ALEX lipid calculator showing information for endogenous lipid species PC 32:0 while applying the FT MS calibration offset = -0.0010. Note that the measured <i>m/z</i> of PC 32:0 is 734.56872 and that the calculated <i>m/z</i> adjusted for the calibration offset is 734.56843 which yield a <i>m/z</i> difference of 0.00029 corresponding to a mass error of 0.4 ppm. Without applying lock mass adjustment the mass error would be 1 ppm.</p>", "links"=>[], "tags"=>["alex", "lipid"], "article_id"=>943433, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079736.g002", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_The_ALEX_lipid_calculator_/943433", "title"=>"The ALEX lipid calculator.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-07 07:13:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1397152"], "description"=>"<p>(<b>A</b>) The ALEX target list generator allows users to select lipid classes and species to be identified using criteria such as lipid class, adduction, C index, db index and OH index. Individual lipid species including internal standards can also be selected. The ALEX target list generator output is a .txt file with a shortlist of selected lipid species, respective <i>m/z</i> values and accessory lipid features. The ALEX target list generator also supports inclusion of isotope information that can be used for deisotoping and isotope correction [20] by applying algorithms within the auxiliary workflow. (<b>B</b>) The ALEX extractor identifies lipid species, exports intensity data and incorporates accessory lipid features. As input the ALEX extractor requires the location of spectral peak lists generated by the ALEX converter, a target list compiled by the ALEX target list generator and a location to deposit output files. The ALEX extractor features options to specify an <i>m/z</i> tolerance window for lipid identification, to apply a constant <i>m/z</i> offset to correct lipid searches for a constant FT MS calibration offset or to apply a lock mass adjustment routine that automatically corrects lipid searches for drifts in FT MS calibration. The automated lock mass adjustment routine requires specification of well-characterized and ubiquitous lock mass ions in order to estimate the FT MS calibration offset.</p>", "links"=>[], "tags"=>["alex", "generator"], "article_id"=>943434, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079736.g003", "stats"=>{"downloads"=>0, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Screenshots_of_the_ALEX_target_list_generator_and_ALEX_extractor_/943434", "title"=>"Screenshots of the ALEX target list generator and ALEX extractor.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-07 07:13:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1397153"], "description"=>"<p>(<b>A</b>) Monitoring of lock mass offset and lock mass ion intensity as function of sample injection. Notice that the lock mass and internal standard TAG 17:1/17:1/17:1 is not detected in injection 07 and 08. Manual inspection of FT MS spectra revealed that the particular sample had not been spiked with internal standards. (<b>B</b>) Assessing the specificity of the PI species profile and intensity across all samples from wild-type mice and the negative control blank samples. Note that in the negative control blank sample (red) a low abundant background ion is detected and falsely identified as PI 40:3. Dubious lipid species can be removed using background subtraction and filtering during subsequent processing in Orange.</p>", "links"=>[], "tags"=>[], "article_id"=>943435, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079736.g004", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Quality_control_analysis_/943435", "title"=>"Quality control analysis.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-07 07:13:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1397154"], "description"=>"<p>(<b>A</b>) A sequence of processing steps executed by the Orange software is used to compute the molar abundance of lipid species. The processing routine utilizes three input files: (a) the output file generated by the ALEX framework specifying lipid intensities, (b) a text file specifying sample information, and (c) a text file specifying internal standards and molar spike amounts. Seven processing steps are executed in order to compute the molar abundances of lipid species for all samples. The data processing generates an output file in database table format featuring the molar abundances of lipid species, originating intensity data, all accessory lipid features and all sample information. (<b>B</b>) Lipid class composition of cerebellum, hippocampus and S1BF from wild-type and PRG-1 knockout mice as automatically calculated and displayed using Tableau Software.</p>", "links"=>[], "tags"=>["auxiliary", "workflow", "lipidome"], "article_id"=>943436, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079736.g005", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Outline_of_the_auxiliary_workflow_used_for_lipidome_data_processing_/943436", "title"=>"Outline of the auxiliary workflow used for lipidome data processing.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-07 07:13:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1397155"], "description"=>"<p>(<b>A</b>) mol% lipid category. Notice that the y-axis is logarithmic. Data is displayed as the average of the two technical replicates per sample. (<b>B</b>) mol% of db index of LPS species. Note that histogram include plot for both technical replicates. (<b>C</b>) mol% of PE species. Data is displayed as the average of the two technical replicates per sample. (<b>D</b>) mol% of all GPL species. Data is displayed as the average of the two technical replicates per sample. Notice that data for only one sample of cerebellum from knockout mice is available due to lack of spiked internal standards as outline in the section “Application of the ALEX software framework”. This neurolipidomics dataset is available as supporting information (Data S2).</p>", "links"=>[], "tags"=>["visualization"], "article_id"=>943437, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>"https://dx.doi.org/10.1371/journal.pone.0079736.g006", "stats"=>{"downloads"=>0, "page_views"=>8, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Lipidome_visualization_using_different_display_formats_/943437", "title"=>"Lipidome visualization using different display formats.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-11-07 07:13:50"}
• {"files"=>["https://ndownloader.figshare.com/files/1397156", "https://ndownloader.figshare.com/files/1397157"], "description"=>"<div><p>Global lipidomics analysis across large sample sizes produces high-content datasets that require dedicated software tools supporting lipid identification and quantification, efficient data management and lipidome visualization. Here we present a novel software-based platform for streamlined data processing, management and visualization of shotgun lipidomics data acquired using high-resolution Orbitrap mass spectrometry. The platform features the ALEX framework designed for automated identification and export of lipid species intensity directly from proprietary mass spectral data files, and an auxiliary workflow using database exploration tools for integration of sample information, computation of lipid abundance and lipidome visualization. A key feature of the platform is the organization of lipidomics data in ”database table format” which provides the user with an unsurpassed flexibility for rapid lipidome navigation using selected features within the dataset. To demonstrate the efficacy of the platform, we present a comparative neurolipidomics study of cerebellum, hippocampus and somatosensory barrel cortex (S1BF) from wild-type and knockout mice devoid of the putative lipid phosphate phosphatase PRG-1 (plasticity related gene-1). The presented framework is generic, extendable to processing and integration of other lipidomic data structures, can be interfaced with post-processing protocols supporting statistical testing and multivariate analysis, and can serve as an avenue for disseminating lipidomics data within the scientific community. The ALEX software is available at <a href=\"http://www.mslipidomics.info\" target=\"_blank\"><u>www.msLipidomics.info</u></a>. </p> </div>", "links"=>[], "tags"=>["lipid", "experiments", "high-resolution", "shotgun", "lipidomics"], "article_id"=>943438, "categories"=>["Biological Sciences"], "users"=>["Peter Husen", "Kirill Tarasov", "Maciej Katafiasz", "Elena Sokol", "Johannes Vogt", "Jan Baumgart", "Robert Nitsch", "Kim Ekroos", "Christer S. Ejsing"], "doi"=>["https://dx.doi.org/10.1371/journal.pone.0079736.s001", "https://dx.doi.org/10.1371/journal.pone.0079736.s002"], "stats"=>{"downloads"=>7, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Analysis_of_Lipid_Experiments_ALEX_A_Software_Framework_for_Analysis_of_High_Resolution_Shotgun_Lipidomics_Data_/943438", "title"=>"Analysis of Lipid Experiments (ALEX): A Software Framework for Analysis of High-Resolution Shotgun Lipidomics Data", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2013-11-07 07:13:50"}

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Relative Metric

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F1000Prime