{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T10:25:56Z","timestamp":1787653556619,"version":"build-2736575974"},"reference-count":56,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T00:00:00Z","timestamp":1787616000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004442","name":"National Science Centre","doi-asserted-by":"publisher","award":["2023\/50\/E\/NZ2\/00583"],"award-info":[{"award-number":["2023\/50\/E\/NZ2\/00583"]}],"id":[{"id":"10.13039\/501100004442","id-type":"DOI","asserted-by":"publisher"}]},{"award":["2023\/50\/E\/NZ2\/00583"],"award-info":[{"award-number":["2023\/50\/E\/NZ2\/00583"]}],"id":[{"id":"https:\/\/ror.org\/03ha2q922","id-type":"ROR","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Methods Protoc.","MPs"],"abstract":"<jats:p>Large-scale, multi-center projects have become common in the era of rapid technological development, but protocol standardization remains challenging. In whole-exome sequencing (WES), various exome enrichment kits exhibit variable efficiency across genomic regions, leading to systematic, non-biological batch effects, much stronger than other technical factors. We propose a workflow to minimize the effect of WES capture inconsistencies in single-nucleotide variation (SNV) data. The pipeline consists of quality control, mapping to the genome, SNV calling, joint genotyping, and imputing genotypes using reference haplotypes. SNVs are then aggregated into gene-level features measuring the burden of deleterious variants. Finally, a gene-level imputation is performed using a customized algorithm. Namely, if the detection rate of a gene is low in samples enriched with a given capture kit but high in samples enriched with other kits, missing values in the former group are imputed, as such differences are unlikely to reflect true biology. As a benchmark, we conducted a study on over a thousand breast cancer cases across 11 cohorts, using eight exome capture kits. We demonstrated that the proposed pipeline leads to a considerable decrease in the batch effect signal, potentially increasing the likelihood of finding true biological signals.<\/jats:p>","DOI":"10.3390\/mps9050125","type":"journal-article","created":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T10:04:55Z","timestamp":1787652295000},"page":"125","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Practical Workflow for Correcting Kit-Specific Effects in Whole-Exome Sequencing Data"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-5297-2407","authenticated-orcid":false,"given":"Laura","family":"Jarosz","sequence":"first","affiliation":[{"name":"Department of Data Science and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marcel","family":"Ochocki","sequence":"additional","affiliation":[{"name":"Department of Data Science and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-8999-5036","authenticated-orcid":false,"given":"Julia","family":"Merta","sequence":"additional","affiliation":[{"name":"Department of Data Science and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9632-6686","authenticated-orcid":false,"given":"Lajos","family":"Pusztai","sequence":"additional","affiliation":[{"name":"Yale Cancer Center, New Haven, CT 06511, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2508-5736","authenticated-orcid":false,"given":"Michal","family":"Marczyk","sequence":"additional","affiliation":[{"name":"Department of Data Science and Engineering, Silesian University of Technology, 44-100 Gliwice, Poland"},{"name":"Yale Cancer Center, New Haven, CT 06511, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"213","DOI":"10.1038\/nprot.2016.182","article-title":"DNA Sequencing Technologies: 2006\u20132016","volume":"12","author":"Mardis","year":"2017","journal-title":"Nat. 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PLoS Med., 12.","DOI":"10.1371\/journal.pmed.1001779"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Buckley, A.R., Standish, K.A., Bhutani, K., Ideker, T., Lasken, R.S., Carter, H., Harismendy, O., and Schork, N.J. (2017). Pan-Cancer Analysis Reveals Technical Artifacts in TCGA Germline Variant Calls. BMC Genom., 18.","DOI":"10.1186\/s12864-017-3770-y"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"750","DOI":"10.1038\/s41576-024-00738-6","article-title":"Next-Generation Data Filtering in the Genomics Era","volume":"25","author":"Hemstrom","year":"2024","journal-title":"Nat. Rev. Genet."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1136\/jmedgenet-2011-100223","article-title":"What Can Exome Sequencing Do for You?","volume":"48","author":"Majewski","year":"2011","journal-title":"J. Med. Genet."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"4487","DOI":"10.1038\/s41467-022-32041-5","article-title":"The Mutational Signatures of Formalin Fixation on the Human Genome","volume":"13","author":"Guo","year":"2022","journal-title":"Nat. Commun."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"17668","DOI":"10.1038\/s41598-017-17333-x","article-title":"Estimating and Mitigating Amplification Bias in Qualitative and Quantitative Arthropod Metabarcoding","volume":"7","author":"Krehenwinkel","year":"2017","journal-title":"Sci. Rep."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"2","DOI":"10.1186\/s13059-021-02569-8","article-title":"Assessing Reproducibility of Inherited Variants Detected with Short-Read Whole Genome Sequencing","volume":"23","author":"Pan","year":"2022","journal-title":"Genome Biol."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Wickland, D.P., Ren, Y., Sinnwell, J.P., Reddy, J.S., Pottier, C., Sarangi, V., Carrasquillo, M.M., Ross, O.A., Younkin, S.G., and Ertekin-Taner, N. (2021). Impact of Variant-Level Batch Effects on Identification of Genetic Risk Factors in Large Sequencing Studies. PLoS ONE, 16.","DOI":"10.1371\/journal.pone.0249305"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Jarosz, L., Dai, J., Ochocki, M., Merta, J., Pusztai, L., and Marczyk, M. (2026, January 2\u20134). Kit-Specific and Other Non-Biological-Based Biases in Germline Whole-Exome Analysis at the Gene Level. Proceedings of the 17th International Conference on Bioinformatics Models, Methods and Algorithms, Marbella, Spain.","DOI":"10.5220\/0014309600004070"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1093\/biostatistics\/kxj037","article-title":"Adjusting Batch Effects in Microarray Expression Data Using Empirical Bayes Methods","volume":"8","author":"Johnson","year":"2007","journal-title":"Biostatistics"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"Limma Powers Differential Expression Analyses for RNA-Sequencing and Microarray Studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1289","DOI":"10.1038\/s41592-019-0619-0","article-title":"Fast, Sensitive and Accurate Integration of Single-Cell Data with Harmony","volume":"16","author":"Korsunsky","year":"2019","journal-title":"Nat. Methods"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"e72","DOI":"10.1093\/nar\/gks001","article-title":"Summarizing and Correcting the GC Content Bias in High-Throughput Sequencing","volume":"40","author":"Benjamini","year":"2012","journal-title":"Nucleic Acids Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"bbab186","DOI":"10.1093\/bib\/bbab186","article-title":"Strand Orientation Bias Detector to Determine the Probability of FFPE Sequencing Artifacts","volume":"22","author":"Diossy","year":"2021","journal-title":"Brief. Bioinform."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2559","DOI":"10.1038\/s41598-024-53167-0","article-title":"DEEPOMICS FFPE, a Deep Neural Network Model, Identifies DNA Sequencing Artifacts from Formalin Fixed Paraffin Embedded Tissue with High Accuracy","volume":"14","author":"Heo","year":"2024","journal-title":"Sci. Rep."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"lqab092","DOI":"10.1093\/nargab\/lqab092","article-title":"Ideafix: A Decision Tree-Based Method for the Refinement of Variants in FFPE DNA Sequencing Data","volume":"3","author":"Calvo","year":"2021","journal-title":"NAR Genom. Bioinform."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1396","DOI":"10.1038\/s42003-021-02930-4","article-title":"MicroSEC Filters Sequence Errors for Formalin-Fixed and Paraffin-Embedded Samples","volume":"4","author":"Ikegami","year":"2021","journal-title":"Commun. Biol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1038\/nbt.4235","article-title":"A Universal SNP and Small-Indel Variant Caller Using Deep Neural Networks","volume":"36","author":"Poplin","year":"2018","journal-title":"Nat. Biotechnol."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Lin, M.F., Rodeh, O., Penn, J., Bai, X., Reid, J.G., Krasheninina, O., and Salerno, W.J. (2018). GLnexus: Joint Variant Calling for Large Cohort Sequencing. BioRxiv.","DOI":"10.1101\/343970"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"D733","DOI":"10.1093\/nar\/gkv1189","article-title":"Reference Sequence (RefSeq) Database at NCBI: Current Status, Taxonomic Expansion, and Functional Annotation","volume":"44","author":"Wright","year":"2016","journal-title":"Nucleic Acids Res."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1016\/j.ajhg.2018.07.015","article-title":"A One-Penny Imputed Genome from Next-Generation Reference Panels","volume":"103","author":"Browning","year":"2018","journal-title":"Am. J. Hum. Genet."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1880","DOI":"10.1016\/j.ajhg.2021.08.005","article-title":"Fast Two-Stage Phasing of Large-Scale Sequence Data","volume":"108","author":"Browning","year":"2021","journal-title":"Am. J. Hum. Genet."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"D886","DOI":"10.1093\/nar\/gky1016","article-title":"CADD: Predicting the Deleteriousness of Variants throughout the Human Genome","volume":"47","author":"Rentzsch","year":"2019","journal-title":"Nucleic Acids Res."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3047","DOI":"10.1093\/bioinformatics\/btw354","article-title":"MultiQC: Summarize Analysis Results for Multiple Tools and Samples in a Single Report","volume":"32","author":"Ewels","year":"2016","journal-title":"Bioinformatics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2114","DOI":"10.1093\/bioinformatics\/btu170","article-title":"Trimmomatic: A Flexible Trimmer for Illumina Sequence Data","volume":"30","author":"Bolger","year":"2014","journal-title":"Bioinformatics"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"D988","DOI":"10.1093\/nar\/gkab1049","article-title":"Ensembl 2022","volume":"50","author":"Cunningham","year":"2022","journal-title":"Nucleic Acids Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"2078","DOI":"10.1093\/bioinformatics\/btp352","article-title":"1000 Genome Project Data Processing Subgroup The Sequence Alignment\/Map Format and SAMtools","volume":"25","author":"Li","year":"2009","journal-title":"Bioinformatics"},{"key":"ref_31","unstructured":"GATK Team (2026, March 13). MarkDuplicates (Picard). Available online: https:\/\/gatk.broadinstitute.org\/hc\/en-us\/articles\/360037052812-MarkDuplicates-Picard."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1093\/bioinformatics\/btt730","article-title":"CrossMap: A Versatile Tool for Coordinate Conversion between Genome Assemblies","volume":"30","author":"Zhao","year":"2014","journal-title":"Bioinformatics"},{"key":"ref_33","first-page":"3426","article-title":"High Coverage Whole Genome Sequencing of the Expanded 1000 Genomes Project Cohort Including 602 Trios","volume":"185","author":"Evani","year":"2021","journal-title":"Cell"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.tree.2019.10.012","article-title":"Using Haplotype Information for Conservation Genomics","volume":"35","author":"Leitwein","year":"2020","journal-title":"Trends Ecol. Evol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"e164","DOI":"10.1093\/nar\/gkq603","article-title":"ANNOVAR: Functional Annotation of Genetic Variants from High-Throughput Sequencing Data","volume":"38","author":"Wang","year":"2010","journal-title":"Nucleic Acids Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"D1143","DOI":"10.1093\/nar\/gkad989","article-title":"CADD v1.7: Using Protein Language Models, Regulatory CNNs and Other Nucleotide-Level Scores to Improve Genome-Wide Variant Predictions","volume":"52","author":"Schubach","year":"2024","journal-title":"Nucleic Acids Res."},{"key":"ref_37","first-page":"2825","article-title":"Scikit-Learn: Machine Learning in Python","volume":"12","author":"Pedregosa","year":"2011","journal-title":"J. Mach. Learn. Res."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2778","DOI":"10.1093\/bioinformatics\/btaa042","article-title":"PARC: Ultrafast and Accurate Clustering of Phenotypic Data of Millions of Single Cells","volume":"36","author":"Stassen","year":"2020","journal-title":"Bioinformatics"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"102811","DOI":"10.1016\/j.jocs.2026.102811","article-title":"dpGMM: A New R Package for Efficient and Robust Gaussian Mixture Modeling of 1D and 2D Data","volume":"95","author":"Zyla","year":"2026","journal-title":"J. Comput. Sci."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"273","DOI":"10.32614\/RJ-2021-048","article-title":"A Unifying Framework for Parallel and Distributed Processing in R Using Futures","volume":"13","author":"Bengtsson","year":"2021","journal-title":"R J."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1038\/s41592-018-0254-1","article-title":"A Test Metric for Assessing Single-Cell RNA-Seq Batch Correction","volume":"16","author":"Miao","year":"2019","journal-title":"Nat. Methods"},{"key":"ref_42","unstructured":"Jefferis, G., Kemp, S.E., Arya, S., and Mount, D. (2026, March 10). RANN: Fast Nearest Neighbour Search (Wraps ANN Library) Using L2 Metric. R Package Version 2.6.3. Available online: https:\/\/github.com\/jefferislab\/RANN."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"R94","DOI":"10.1186\/gb-2011-12-9-r94","article-title":"Comparison of Solution-Based Exome Capture Methods for next Generation Sequencing","volume":"12","author":"Sulonen","year":"2011","journal-title":"Genome Biol."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"12742","DOI":"10.1038\/srep12742","article-title":"Performance Comparison of Four Commercial Human Whole-Exome Capture Platforms","volume":"5","author":"Shigemizu","year":"2015","journal-title":"Sci. Rep."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"lqaf115","DOI":"10.1093\/nargab\/lqaf115","article-title":"A Systematic Analysis of Contemporary Whole Exome Sequencing Capture Kits to Optimise High-Coverage Capture of CCDS Regions","volume":"7","author":"Ashton","year":"2025","journal-title":"NAR Genom. Bioinf."},{"key":"ref_46","unstructured":"(2026, March 10). Agilent Technologies|Agilent. Available online: https:\/\/www.agilent.com\/en\/."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"5582","DOI":"10.1093\/bioinformatics\/btaa1081","article-title":"Accurate, Scalable Cohort Variant Calls Using DeepVariant and GLnexus","volume":"36","author":"Yun","year":"2021","journal-title":"Bioinformatics"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Barbitoff, Y.A., Abasov, R., Tvorogova, V.E., Glotov, A.S., and Predeus, A.V. (2022). Systematic Benchmark of State-of-the-Art Variant Calling Pipelines Identifies Major Factors Affecting Accuracy of Coding Sequence Variant Discovery. BMC Genom., 23.","DOI":"10.1186\/s12864-022-08365-3"},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Pinto, V., Sousa, L., and Silva, C. (2026). Variant Calling in Genomics: A Comparative Performance Analysis and Decision Guide. PLoS ONE, 21.","DOI":"10.1371\/journal.pone.0339891"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1186\/s13059-024-03401-9","article-title":"Assessing and Mitigating Batch Effects in Large-Scale Omics Studies","volume":"25","author":"Yu","year":"2024","journal-title":"Genome Biol."},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Garrison, E., Kronenberg, Z.N., Dawson, E.T., Pedersen, B.S., and Prins, P. (2022). A Spectrum of Free Software Tools for Processing the VCF Variant Call Format: Vcflib, Bio-Vcf, Cyvcf2, Hts-Nim and Slivar. PLoS Comput. Biol., 18.","DOI":"10.1371\/journal.pcbi.1009123"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"2202","DOI":"10.1093\/bioinformatics\/btv112","article-title":"Unified Representation of Genetic Variants","volume":"31","author":"Tan","year":"2015","journal-title":"Bioinformatics"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1038\/s41586-021-03205-y","article-title":"Sequencing of 53,831 Diverse Genomes from the NHLBI TOPMed Program","volume":"590","author":"Taliun","year":"2021","journal-title":"Nature"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1186\/s13073-019-0682-2","article-title":"Low Coverage Whole Genome Sequencing Enables Accurate Assessment of Common Variants and Calculation of Genome-Wide Polygenic Scores","volume":"11","author":"Homburger","year":"2019","journal-title":"Genome Med."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"351","DOI":"10.1534\/genetics.166.1.351","article-title":"The Allele Frequency Spectrum in Genome-Wide Human Variation Data Reveals Signals of Differential Demographic History in Three Large World Populations","volume":"166","author":"Marth","year":"2004","journal-title":"Genetics"},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Savas, P., Teo, Z.L., Lefevre, C., Flensburg, C., Caramia, F., Alsop, K., Mansour, M., Francis, P.A., Thorne, H.A., and Silva, M.J. (2016). The Subclonal Architecture of Metastatic Breast Cancer: Results from a Prospective Community-Based Rapid Autopsy Program \u201cCASCADE.\u201d. PLoS Med., 13.","DOI":"10.1371\/journal.pmed.1002204"}],"container-title":["Methods and Protocols"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2409-9279\/9\/5\/125\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T10:15:38Z","timestamp":1787652938000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2409-9279\/9\/5\/125"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,25]]},"references-count":56,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2026,10]]}},"alternative-id":["mps9050125"],"URL":"https:\/\/doi.org\/10.3390\/mps9050125","relation":{},"ISSN":["2409-9279"],"issn-type":[{"value":"2409-9279","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,25]]}}}