{"id":4577,"date":"2015-05-01T07:00:07","date_gmt":"2015-05-01T11:00:07","guid":{"rendered":"http:\/\/admin.acceleratingscience.com\/?p=4577"},"modified":"2015-05-01T07:00:07","modified_gmt":"2015-05-01T11:00:07","slug":"how-much-alfq-for-estimating-absolute-protein-quantities","status":"publish","type":"post","link":"https:\/\/www.thermofisher.com\/blog\/proteomics\/how-much-alfq-for-estimating-absolute-protein-quantities\/","title":{"rendered":"How Much? aLFQ for Estimating Absolute Protein Quantities"},"content":{"rendered":"<p><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/admin.acceleratingscience.com\/wp-content\/uploads\/2015\/05\/shutterstock_237436354.jpg\" style=\"float: left;margin: 10px\" alt=\"Bioinformatics. Image: Kentoh\/Shutterstock.com\" width=\"330\" height=\"214\" class=\"alignleft\" \/>Written in R, the statistical programming language, Rosenberger et al. (2014) have developed a bioinformatics tool, aLFQ, that aims to ease the acquisition of absolute protein quantitation from label-free mass spectrometric (MS)-based proteomics data.<sup>1 <\/sup><span>Their <a href=\"http:\/\/www.cran.r-project.org\/\" target=\"_blank\">freely available software tool<\/a>, which packages algorithms for automated data analysis and error estimation, is available online to the proteomics research community.<\/span><\/p>\n<p><span>Although relative protein quantitation methods are commonly used to compare levels within samples, they aren&rsquo;t suitable for analysis across datasets or for considering the abundance of different proteins within a large-scale experimental design. Techniques such as stable isotope labeling exist but are not widely accessible. The more accessible label-free quantitation approach is within reach for&nbsp;a greater number of&nbsp;researchers, but methods for absolute quantitation are scarce. Additionally, often the methods that are&nbsp;available for absolute quantitation each require their own analytical framework for analytical output.<\/span><\/p>\n<p><span>For this reason, Rosenberger et al. developed aLFQ as a bioinformatics tool that utilizes existing label-free estimation methods such as TopN, iBAQ and SCAMPI, among others. <\/span><span>The team created the tool in R as a modular S3 package, comprising three main modules: the&nbsp;<\/span><span>import, ProteinInference and AbsoluteQuantification modules,<\/span><span> which also describe the workflow involved in outputting quantitative data from a label-free liquid chromatography&ndash;tandem mass spectrometry (LC-MS\/MS) experiment. <\/span><\/p>\n<p><span>First, within the<\/span><span> import<\/span><span> module, the user uploads data from the files created during quantitative label-free LC-MS\/MS. From this, aLFQ generates its own generic data structure for output. From this structure, the <\/span><span>ProteinInference<\/span><span> module combines different protein intensity estimation tools (TopN, iBAQ, etc.) and outputs measurements based on peptide or precursor intensities, spectral counts and transition intensities. This module enables direct comparisons.<\/span><\/p>\n<p><span>Finally, the <\/span><span>AbsoluteQuantification<\/span><span> module makes the data available as a protein-abundance estimation, with error calculation included. It calculates these from regression analysis of a linear correlation involving predefined anchors (proteins and peptides). <\/span><\/p>\n<p><span>In addition, Rosenberger et al. have made an example dataset with workflow available for interested researchers, giving command line instrudbgbctions within their research paper.<sup><span style=\"font-size: xx-small\">1<\/span><\/sup> The program lives at <\/span><a href=\"http:\/\/www.cran.r-project.org\/\"><span>http:\/\/www.cran.r-project.org<\/span><\/a><span>, found under Packages &gt; Table of Packages for ease of access&mdash;yet another open access tool for&nbsp;the researcher&#8217;s&nbsp;p<\/span><span>roteomics arsenal!<\/span><\/p>\n<p><span><\/span>&nbsp;<\/p>\n<p><span><strong>Reference<\/strong><\/span><\/p>\n<p><span>1.&nbsp;Rosenberger, G., et al. (2014) &#8220;<\/span><a href=\"http:\/\/www.ncbi.nlm.nih.gov\/pubmed\/24753486\" target=\"_blank\">aLFQ: An R-package for estimating absolute protein quantities from label-free LC-MS\/MS proteomics data<\/a>,&#8221;&nbsp;Bioinformatics, 30 (pp. 2511&ndash;13), doi: 10.1093\/bioinformatics\/btu200.<\/p>\n<p><span><\/span>&nbsp;<\/p>\n<p><span><strong>Further Reading<\/strong>&nbsp;<\/span><\/p>\n<p><span><span style=\"font: 13px\/17.99px arial, helvetica, clean, sans-serif;text-align: left;color: #000000;text-indent: 0px;letter-spacing: normal;float: none;background-color: #ffffff\">aLFQ is written in R and freely available under the GPLv3 from CRAN:<\/span> <a href=\"http:\/\/www.cran.r-project.org%20%20\" target=\"_blank\">http:\/\/www.cran.r-project.org<\/a><\/span><\/p>\n<p><span>Learn about the statistical programming language, R, here:&nbsp;<\/span><a href=\"http:\/\/www.r-project.org\">http:\/\/www.r-project.org<\/a><\/p>\n<p><i>Post Author: Amanda Maxwell. Mixed media artist; blogger and social media communicator; clinical scientist and writer.<\/p>\n<p>A digital space explorer, engaging readers by translating complex theories and subjects creatively into everyday language.<\/i><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Written in R, the statistical programming language, Rosenberger et al. (2014) have developed a bioinformatics tool, aLFQ, that aims to ease the acquisition of absolute protein quantitation from label-free mass spectrometric (MS)-based proteomics data.1 Their freely available software tool, which packages algorithms for automated data analysis and error estimation, is available online to the proteomics<\/p>\n","protected":false},"author":21,"featured_media":4576,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_monsterinsights_skip_tracking":false,"_genesis_hide_title":false,"_genesis_hide_breadcrumbs":false,"_genesis_hide_singular_image":false,"_genesis_hide_footer_widgets":false,"_genesis_custom_body_class":"","_genesis_custom_post_class":"","_genesis_layout":"","_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[12],"tags":[132,74,649,650,651,652,653],"division":[],"class_list":{"0":"post-4577","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-methods","8":"tag-algorithms","9":"tag-bioinformatics","10":"tag-computing","11":"tag-data-analysis-tool","12":"tag-label-free-proteomics-data","13":"tag-r","14":"tag-statistical-analysis","15":"entry"},"_selected_authors":"","_selected_reviewers":"","acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v27.8 (Yoast SEO v27.8) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>A New Bioinformatics Tool for Estimating Absolute Protein Quantities<\/title>\n<meta name=\"description\" content=\"A new bioinformatics tool, aLFQ, eases the acquisition of absolute protein quantitation from mass spectrometry-based proteomics data.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.thermofisher.com\/blog\/proteomics\/how-much-alfq-for-estimating-absolute-protein-quantities\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"How Much? 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