{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T23:53:35Z","timestamp":1778284415921,"version":"3.51.4"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2018,9,24]],"date-time":"2018-09-24T00:00:00Z","timestamp":1537747200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01GM083336"],"award-info":[{"award-number":["R01GM083336"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R35GM118022"],"award-info":[{"award-number":["1R35GM118022"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1R35GM118021"],"award-info":[{"award-number":["1R35GM118021"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["1U01EB022546"],"award-info":[{"award-number":["1U01EB022546"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Albert J. Ryan Fellowship"},{"DOI":"10.13039\/100000936","name":"Gordon and Betty Moore Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000936","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000936","name":"GBMF","doi-asserted-by":"publisher","award":["4552"],"award-info":[{"award-number":["4552"]}],"id":[{"id":"10.13039\/100000936","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Motivation<\/jats:title>\n                    <jats:p>Decreasing costs are making it feasible to perform time series proteomics and genomics experiments with more replicates and higher resolution than ever before. With more replicates and time points, proteome and genome-wide patterns of expression are more readily discernible. These larger experiments require more batches exacerbating batch effects and increasing the number of bias trends. In the case of proteomics, where methods frequently result in missing data this increasing scale is also decreasing the number of peptides observed in all samples. The sources of batch effects and missing data are incompletely understood necessitating novel techniques.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Here we show that by exploiting the structure of time series experiments, it is possible to accurately and reproducibly model and remove batch effects. We implement Learning and Imputation for Mass-spec Bias Reduction (LIMBR) software, which builds on previous block-based models of batch effects and includes features specific to time series and circadian studies. To aid in the analysis of time series proteomics experiments, which are often plagued with missing data points, we also integrate an imputation system. By building LIMBR for imputation and time series tailored bias modeling into one straightforward software package, we expect that the quality and ease of large-scale proteomics and genomics time series experiments will be significantly increased.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>Python code and documentation is available for download at https:\/\/github.com\/aleccrowell\/LIMBR and LIMBR can be downloaded and installed with dependencies using \u2018pip install limbr\u2019.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/bty828","type":"journal-article","created":{"date-parts":[[2018,9,23]],"date-time":"2018-09-23T07:07:33Z","timestamp":1537686453000},"page":"1518-1526","source":"Crossref","is-referenced-by-count":21,"title":["Learning and Imputation for Mass-spec Bias Reduction (LIMBR)"],"prefix":"10.1093","volume":"35","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2866-8139","authenticated-orcid":false,"given":"Alexander M","family":"Crowell","sequence":"first","affiliation":[{"name":"Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8713-9213","authenticated-orcid":false,"given":"Casey S","family":"Greene","sequence":"additional","affiliation":[{"name":"Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer J","family":"Loros","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Cell Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jay C","family":"Dunlap","sequence":"additional","affiliation":[{"name":"Department of Molecular and Systems Biology, Geisel School of Medicine at Dartmouth, Hanover, NH, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2018,9,24]]},"reference":[{"key":"2026041420022128500_bty828-B1","first-page":"1","author":"Batista","year":"2001"},{"key":"2026041420022128500_bty828-B2","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1073\/pnas.1611431114","article-title":"A ketogenic diet rescues hippocampal memory defects in a mouse model of Kabuki syndrome","volume":"114","author":"Benjamin","year":"2017","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2026041420022128500_bty828-B3","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1186\/1471-2105-14-236","article-title":"svapls: an R package to correct for hidden factors of variability in gene expression studies","volume":"14","author":"Chakraborty","year":"2013","journal-title":"BMC Bioinformatics"},{"key":"2026041420022128500_bty828-B4","doi-asserted-by":"crossref","first-page":"500","DOI":"10.1038\/nature18270","article-title":"Defining the consequences of genetic variation on a proteome-wide scale","volume":"534","author":"Chick","year":"2016","journal-title":"Nature"},{"key":"2026041420022128500_bty828-B5","first-page":"529","volume-title":"Data Analysis Using Regression and Multilevel\/Hierarchical Models","author":"Gelman","year":"2007","edition":"1st edn"},{"key":"2026041420022128500_bty828-B6","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1177\/0748730410379711","article-title":"JTK_CYCLE: an efficient nonparametric algorithm for detecting rhythmic components in genome-scale data sets","volume":"25","author":"Hughes","year":"2010","journal-title":"J. Biol. Rhythms"},{"key":"2026041420022128500_bty828-B7","doi-asserted-by":"crossref","first-page":"2021","DOI":"10.1074\/mcp.M112.021592","article-title":"Defining, comparing, and improving iTRAQ quantification in mass spectrometry proteomics data","volume":"12","author":"Hultin-Rosenberg","year":"2013","journal-title":"Mol. Cell. Proteomics"},{"key":"2026041420022128500_bty828-B8","first-page":"1","article-title":"Improved Statistical Methods Enable Greater Sensitivity in Rhythm Detection for Genome-Wide Data","volume":"11","author":"Hutchison","year":"2015","journal-title":"PLoS Comput. Bio"},{"key":"2026041420022128500_bty828-B9","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1186\/s12859-015-0808-5","article-title":"Practical impacts of genomic data \u201ccleaning\u201d on biological discovery using surrogate variable analysis","volume":"16","author":"Jaffe","year":"2015","journal-title":"BMC Bioinformatics"},{"key":"2026041420022128500_bty828-B10","doi-asserted-by":"crossref","first-page":"2573","DOI":"10.1093\/bioinformatics\/btp426","article-title":"Normalization of peak intensities in bottom-up MS-based proteomics using singular value decomposition","volume":"25","author":"Karpievitch","year":"2009","journal-title":"Bioinformatics"},{"key":"2026041420022128500_bty828-B11","doi-asserted-by":"crossref","first-page":"S5.","DOI":"10.1186\/1471-2105-13-S16-S5","article-title":"Normalization and missing value imputation for label-free LC-MS analysis","volume":"13","author":"Karpievitch","year":"2012","journal-title":"BMC Bioinformatics"},{"key":"2026041420022128500_bty828-B12","author":"Leek","year":"2007"},{"key":"2026041420022128500_bty828-B13","doi-asserted-by":"crossref","first-page":"1724","DOI":"10.1371\/journal.pgen.0030161","article-title":"Capturing heterogeneity in gene expression studies by surrogate variable analysis","volume":"3","author":"Leek","year":"2007","journal-title":"PLoS Genet"},{"key":"2026041420022128500_bty828-B14","doi-asserted-by":"crossref","first-page":"882","DOI":"10.1093\/bioinformatics\/bts034","article-title":"The sva package for removing batch effects and other unwanted variation in high-throughput experiments","volume":"28","author":"Leek","year":"2012","journal-title":"Bioinformatics"},{"key":"2026041420022128500_bty828-B15","first-page":"888","article-title":"Detecting and correcting systematic variation in large-scale RNA sequencing data","volume":"32","author":"Li","year":"2014","journal-title":"Nature"},{"key":"2026041420022128500_bty828-B16","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1038\/nm.3582","article-title":"miR-1202 is a primate-specific and brain-enriched microRNA involved in major depression and antidepressant treatment","volume":"20","author":"Lopez","year":"2014","journal-title":"Nat. Med"},{"key":"2026041420022128500_bty828-B17","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1038\/nbt1275","article-title":"Computational prediction of proteotypic peptides for quantitative proteomics","volume":"25","author":"Mallick","year":"2007","journal-title":"Nat. Biotechnol"},{"key":"2026041420022128500_bty828-B18","doi-asserted-by":"crossref","first-page":"1","DOI":"10.4172\/2155-6180.1000224","article-title":"A Comparison of Six Methods for Missing Data Imputation","volume":"6,","author":"Mandel","year":"2015","journal-title":"J. Biom. Biostat"},{"key":"2026041420022128500_bty828-B19","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1073\/pnas.1314066111","article-title":"Circadian clock-dependent and -independent rhythmic proteomes implement distinct diurnal functions in mouse liver","volume":"111","author":"Mauvoisin","year":"2014","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"2026041420022128500_bty828-B20","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1093\/biostatistics\/kxv027","article-title":"Methods that remove batch effects while retaining group differences may lead to exaggerated confidence in downstream analyses","volume":"17","author":"Nygaard","year":"2016","journal-title":"Biostatistics"},{"key":"2026041420022128500_bty828-B21","doi-asserted-by":"crossref","first-page":"2757","DOI":"10.1093\/bioinformatics\/btu375","article-title":"Preserving biological heterogeneity with a permuted surrogate variable analysis for genomics batch correction","volume":"30","author":"Parker","year":"2014","journal-title":"Bioinformatics"},{"key":"2026041420022128500_bty828-B22","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1186\/s12885-017-3413-3","article-title":"Identifying global expression patterns and key regulators in epithelial to mesenchymal transition through multi-study integration","volume":"17","author":"Parsana","year":"2017","journal-title":"BMC Cancer"},{"key":"2026041420022128500_bty828-B23","doi-asserted-by":"crossref","first-page":"2128","DOI":"10.1021\/pr301146m","article-title":"Sources of Technical Variability in Quantitative LC\u2013MS Proteomics: human Brain Tissue Sample Analysis","volume":"12","author":"Piehowski","year":"2013","journal-title":"J. Proteome Res"},{"key":"2026041420022128500_bty828-B24","doi-asserted-by":"crossref","first-page":"15.","DOI":"10.1371\/journal.pgen.1004047","article-title":"In-vivo quantitative proteomics reveals a key contribution of post-transcriptional mechanisms to the circadian regulation of liver metabolism","volume":"10","author":"Robles","year":"2014","journal-title":"PLoS Genet"},{"key":"2026041420022128500_bty828-B25","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1016\/j.cmet.2016.10.004","article-title":"Phosphorylation Is a Central Mechanism for Circadian Control of Metabolism and Physiology","volume":"25","author":"Robles","year":"2017","journal-title":"Cell Metab"},{"key":"2026041420022128500_bty828-B26","doi-asserted-by":"crossref","first-page":"1341","DOI":"10.1074\/mcp.M113.030593","article-title":"Improved normalization of systematic biases affecting ion current measurements in label-free proteomics data","volume":"13","author":"Rudnick","year":"2014","journal-title":"Mol. Cell. Proteomics"},{"key":"2026041420022128500_bty828-B27","doi-asserted-by":"crossref","first-page":"1155","DOI":"10.1021\/ac026122m","article-title":"Statistical characterization of ion trap tandem mass spectra from doubly charged tryptic peptides","volume":"75","author":"Tabb","year":"2003","journal-title":"Anal. Chem"},{"key":"2026041420022128500_bty828-B28","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1093\/bioinformatics\/17.6.520","article-title":"Missing value estimation methods for DNA microarrays","volume":"17","author":"Troyanskaya","year":"2001","journal-title":"Bioinformatics"},{"key":"2026041420022128500_bty828-B29","doi-asserted-by":"crossref","first-page":"499","DOI":"10.1016\/j.cell.2014.03.031","article-title":"Global analyses of human immune variation reveal baseline predictors of postvaccination responses","volume":"157","author":"Tsang","year":"2014","journal-title":"Cell"},{"key":"2026041420022128500_bty828-B30","first-page":"1","article-title":"Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd","volume":"7","author":"Wang","year":"2016","journal-title":"Nat. Commun"},{"key":"2026041420022128500_bty828-B31","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1016\/j.cmet.2016.10.003","article-title":"Nuclear Proteomics Uncovers Diurnal Regulatory Landscapes in Mouse Liver","volume":"25","author":"Wang","year":"2017","journal-title":"Cell Metab"},{"key":"2026041420022128500_bty828-B32","first-page":"273","article-title":"In-depth method assessments of differentially expressed protein detection for shotgun proteomics data with missing values","volume":"7","author":"Wang","year":"2017","journal-title":"Sci. Rep"},{"key":"2026041420022128500_bty828-B33","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2004.02.014","article-title":"Nearest neighbour approach in the least-squares data imputation algorithms","volume":"169","author":"Wasito","year":"2005","journal-title":"Inf. Sci"},{"key":"2026041420022128500_bty828-B34","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1016\/j.cell.2014.04.028","article-title":"Quantitative Temporal Viromics: an Approach to Investigate Host-Pathogen Interaction","volume":"157","author":"Weekes","year":"2014","journal-title":"Cell"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/9\/1518\/48942025\/bioinformatics_35_9_1518.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/35\/9\/1518\/48942025\/bioinformatics_35_9_1518.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,15]],"date-time":"2026-04-15T00:02:40Z","timestamp":1776211360000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/35\/9\/1518\/5106167"}},"subtitle":[],"editor":[{"given":"Jonathan","family":"Wren","sequence":"additional","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2018,9,24]]},"references-count":34,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2019,5,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/bty828","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/301242","asserted-by":"object"}]},"ISSN":["1367-4803","1367-4811"],"issn-type":[{"value":"1367-4803","type":"print"},{"value":"1367-4811","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2019,5,1]]},"published":{"date-parts":[[2018,9,24]]}}}