2025
Travel-associated international spread of Oropouche virus beyond the Amazon
de Melo Iani F, Pereira F, de Oliveira E, Rodrigues J, Machado M, Fonseca V, Adelino T, Guimarães N, Tomé L, Gómez M, Nardy V, Ribeiro A, Rosewell A, Ferreira Á, de Mello A, Fernandes B, de Albuquerque C, dos Santos Pereira D, Pimentel E, Lima F, Silva F, de Carvalho Pereira G, Tegally H, Almeida J, Moreno K, Vasconcelos K, Santos L, Silva L, Frutuoso L, Lamounier L, Costa M, de Oliveira M, dos Anjos M, Ciccozzi M, Lima M, Pereira M, Rocha M, da Silva P, Rabinowitz P, de Almeida P, Lessells R, Gazzinelli R, da Cunha R, Gonçalves S, dos Santos S, de Alcântara Belettini S, Pedroso S, Araújo S, da Silva S, Croda J, Maciel E, Van Voorhis W, Martin D, Holmes E, de Oliveira T, Lourenço J, Alcantara L, Giovanetti M. Travel-associated international spread of Oropouche virus beyond the Amazon. Journal Of Travel Medicine 2025, 32: taaf018. PMID: 40037296, PMCID: PMC11955161, DOI: 10.1093/jtm/taaf018.Peer-Reviewed Original ResearchOropouche virusAmazon basinWhole-genome sequencingViral adaptationLocal ecological conditionsMonophyletic groupGenome segmentsPhylogenetic analysisGenomic analysisViral movementGenomic changesPhenotypic traitsEpidemiological metadataReassortment eventsBrazilian Amazon basinPublic health laboratoriesEcological conditionsHuman population changeGenomeCentral Public Health LaboratoryReassortmentPublic health significanceHealth laboratoriesGeographic expansionSequence589. Late Onset Invasive Group B Streptococcal Disease Outbreak in a Neonatal Intensive Care Unit Identified Through Whole Genome Sequencing — Connecticut, 2020–2024
Lambert M, Jones S, Mueller K, Maloney M, Perera N, Incekara K, Petit S, Ramachandran V, Grossman M, Valderrama A, Chochua S, McGee L, Metcalf B, Schrag S, Sosa L. 589. Late Onset Invasive Group B Streptococcal Disease Outbreak in a Neonatal Intensive Care Unit Identified Through Whole Genome Sequencing — Connecticut, 2020–2024. Open Forum Infectious Diseases 2025, 12: ofae631.184. PMCID: PMC11778314, DOI: 10.1093/ofid/ofae631.184.Peer-Reviewed Original ResearchNeonatal intensive care unitGroup B streptococciGroup B Streptococcus isolatesWhole-genome sequencingIntensive care unitLate-onset diseaseOutbreak-related casesSingle nucleotide polymorphismsColonized infantsCare unitColon screeningGroup B streptococcus colonizationActive Bacterial Core surveillance programIntegration of whole genome sequencingDepartment of Public HealthAssessment of infection preventionDays of lifeIPC gapsLOD casesNeonatal sepsisB streptococciReview of dataConnecticut Department of Public HealthOutbreak-relatedIllness onsetA new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission
Sobkowiak B, Cudahy P, Chitwood M, Clark T, Colijn C, Grandjean L, Walter K, Crudu V, Cohen T. A new method for detecting mixed Mycobacterium tuberculosis infection and reconstructing constituent strains provides insights into transmission. Genome Medicine 2025, 17: 8. PMID: 39871355, PMCID: PMC11771024, DOI: 10.1186/s13073-025-01430-y.Peer-Reviewed Original ResearchConceptsShort-read WGS dataWhole-genome sequencingStrain sequencesWGS dataMultiple strainsStrain proportionsMycobacterium tuberculosis populationMixed infectionGenome sequenceBioinformatics pipelineClustering allele frequenciesDownstream analysisAllele frequenciesEvidence of mixed infectionSequenceTuberculosis populationStrainIsolatesIn vitroTransmission clustersMixed samplesAllelesInfectionMycobacterium tuberculosis infectionPathogensThe human and non-human primate developmental GTEx projects
Bell T, Blanchard T, Hernandez R, Linn R, Taylor D, VonDran M, Ahooyi T, Beitra D, Bernieh A, Delaney M, Faith M, Fattahi E, Footer D, Gilbert M, Guambaña S, Gulino S, Hanson J, Hattrell E, Heinemann C, Kreeb J, Leino D, Mcdevitt L, Palmieri A, Pfeiffer M, Pryhuber G, Rossi C, Rasool I, Roberts R, Salehi A, Savannah E, Stachowicz K, Stokes D, Suplee L, Van Hoose P, Wilkins B, Williams-Taylor S, Zhang S, Ardlie K, Getz G, Lappalainen T, Montgomery S, Aguet F, Anderson L, Bernstein B, Choudhary A, Domenech L, Gaskell E, Johnson M, Liu Q, Marderstein A, Nedzel J, Okonda J, Padhi E, Rosano M, Russell A, Walker B, Sestan N, Gerstein M, Milosavljevic A, Borsari B, Cho H, Clarke D, Deveau A, Galeev T, Gobeske K, Hameed I, Huttner A, Jensen M, Jiang Y, Li J, Liu J, Liu Y, Ma J, Mane S, Meng R, Nadkarni A, Ni P, Park S, Petrosyan V, Pochareddy S, Salamon I, Xia Y, Yates C, Zhang M, Zhao H, Conrad D, Feng G, Brady F, Boucher M, Carbone L, Castro J, del Rosario R, Held M, Hennebold J, Lacey A, Lewis A, Lima A, Mahyari E, Moore S, Okhovat M, Roberts V, de Castro S, Wessel B, Zaniewski H, Zhang Q, Arguello A, Baroch J, Dayal J, Felsenfeld A, Ilekis J, Jose S, Lockhart N, Miller D, Minear M, Parisi M, Price A, Ramos E, Zou S. The human and non-human primate developmental GTEx projects. Nature 2025, 637: 557-564. PMID: 39815096, DOI: 10.1038/s41586-024-08244-9.Peer-Reviewed Original ResearchConceptsChromatin accessibility dataFunctional genomic studiesWhole-genome sequencingEffects of genetic variationSpatial gene expression profilesNon-human primatesGenotype-Tissue ExpressionGene expression profilesGenomic studiesGene regulationGenetic dataGenetic variationGenomic researchDonor diversityCommunity engagementHuman evolutionEarly developmental defectsGene expressionCell statesDevelopmental programmeHuman diseasesExpression profilesAdult tissuesDevelopmental defectsSingle-cellPhenotypic and genotypic characterization of Mycobacterium tuberculosis pyrazinamide resistance—India, 2018–2020
Tamilzhalagan S, Justin E, Selvaraj A, Venkateswaran K, Sivakumar A, Chittibabu S, McLaughlin H, Moonan P, Smith J, Suba S, Narayanan M, Ho C, Kumar N, Tripathy S, Shanmugam S, Hall-Eidson P, Ranganathan U. Phenotypic and genotypic characterization of Mycobacterium tuberculosis pyrazinamide resistance—India, 2018–2020. Frontiers In Microbiology 2025, 15: 1515627. PMID: 39845030, PMCID: PMC11750862, DOI: 10.3389/fmicb.2024.1515627.Peer-Reviewed Original ResearchPZA resistancePyrazinamide resistanceMultidrug resistanceDuration of tuberculosis treatmentWhole-genome sequencingPrevalence of mutationsSecond-line drugsPZA-resistant isolatesResistance-conferring mutationsGenome sequenceTB burden countriesLineage 2Genotypic characterizationResistance markersNovel mutationsPhenotypic resistanceMutational diversityDiagnostic accuracyTuberculosis treatmentAntituberculosis drugsCo-resistanceBurden countriesPyrazinamideMutationsTB prevention
2024
Monitoring sewage and effluent water is an effective approach for the detection of the mobile colistin resistance genes (mcr) and associated bacterial hosts in the human population and environment in the USA
Hassan J, Osman M, Xu T, Naas T, Schiff S, Mann D, Esseili M, Deng X, Kassem I. Monitoring sewage and effluent water is an effective approach for the detection of the mobile colistin resistance genes (mcr) and associated bacterial hosts in the human population and environment in the USA. Environmental Pollution 2024, 366: 125515. PMID: 39662581, DOI: 10.1016/j.envpol.2024.125515.Peer-Reviewed Original ResearchWhole-genome sequencingMobile colistin resistance geneColistin resistance genesResistance genesMcr-9Whole-genome sequence analysisKirby-Bauer disk diffusionGram-negative bacterial isolatesBroth micro-dilution assayLast-resort antibioticsTreat recalcitrant infectionsMcr-positive isolatesAntibiotic resistance genesMicro-dilution assayGenome sequenceBacterial hostsHuman populationKirby-BauerIncHI2 plasmidsBiofilm assayBacterial isolatesDisk diffusionMcr-3Water samplesRecalcitrant infectionsRare genetic variation in fibronectin 1 (FN1) protects against APOE ɛ4 in Alzheimer’s Disease
Bhattarai P, Gunasekaran T, Uzrek B, Reyes‐Dumeyer D, Jülich D, Lee A, Yilmaz E, Tayran H, Lantigua R, Medrano M, Mejia D, Recio P, Flaherty D, Dalgard C, Nuriel T, Ertekin‐Taner N, Dickson D, Teich A, Holley S, Mayeux R, Kizil C, Vardarajan B. Rare genetic variation in fibronectin 1 (FN1) protects against APOE ɛ4 in Alzheimer’s Disease. Alzheimer's & Dementia 2024, 20: e089111. PMCID: PMC11710415, DOI: 10.1002/alz.089111.Peer-Reviewed Original ResearchWhole-genome sequencingLoss-of-functionIn vivo functional studiesFibronectin 1Genetic variationAlzheimer's diseaseFunctional studiesWhole-genome sequence analysisTarget genesRare genetic variationLoss-of-function mutationsPotential gene variantsZebrafish modelGenome sequenceProtective variantsAPOE variantsGenetic variantsECM proteinsZebrafish AD modelBioinformatics analysisAD pathologyPotential therapeutic interventional targetsPathway analysisPostmortem human brain tissueRare variantsDNAR-16. TARGETING APOBEC CYTIDINE DEAMINASES TO ENHANCE RADIOSENSITIVITY IN GLIOMA
Marin B, Gujar A, Kocakavuk E, Johnson K, Amin S, Verhaak R. DNAR-16. TARGETING APOBEC CYTIDINE DEAMINASES TO ENHANCE RADIOSENSITIVITY IN GLIOMA. Neuro-Oncology 2024, 26: viii120-viii121. PMCID: PMC11553289, DOI: 10.1093/neuonc/noae165.0467.Peer-Reviewed Original ResearchApolipoprotein B mRNA-editing enzyme catalytic polypeptide-likeRadiation therapyNon-homologous end joiningRecurrent gliomaDNA-dependent protein kinaseMutational signaturesRT-induced DNA damageMonitoring response to treatmentRadiosensitivity in vitroEnhanced radiosensitivity in vitroA3GPromote tumor evolutionResponse to treatmentAutophosphorylation of DNA-dependent protein kinaseAPOBEC mutational signaturesAdult brain tumorsPrimary adult brain tumorGlioma Longitudinal Analysis ConsortiumFamily of cytidine deaminasesRadiosensitizing gliomasAPOBEC3G (A3GNon-homologous end-joining pathwayPost-RTGlioma cell linesWhole-genome sequencingCNSC-54. CENTRAL AND BOUNDARY-DRIVEN GROWTH PATTERNS DOMINATE RESPECTIVELY IDH WILD-TYPE AND MUTANT GLIOMAS
Kyriakidou M, Urbaniak K, Mbegbu M, Rockne R, Wesseling P, Eijgelaar R, Anderson K, Verhaak R, de Witt-Hamer P, Verburg N, Branciamore S, Barthel F. CNSC-54. CENTRAL AND BOUNDARY-DRIVEN GROWTH PATTERNS DOMINATE RESPECTIVELY IDH WILD-TYPE AND MUTANT GLIOMAS. Neuro-Oncology 2024, 26: viii53-viii53. PMCID: PMC11553254, DOI: 10.1093/neuonc/noae165.0210.Peer-Reviewed Original ResearchConsistent with neutral evolutionDiffuse gliomasLocal treatmentEvolutionary processWhole-genome sequencingSpread to distant sitesIDH wild-typePrimary malignant brain tumorImage-guided samplingPhylogeographic relationshipsDN/dS ratiosMalignant brain tumorsNeutral evolutionSomatic variantsGenetic heterogeneityIDHmut tumorsTumor centerMRI abnormalitiesStochastic mutationsTumor diffusionAdult patientsPoor prognosisTumor cellsIDH mutantTumor developmentIntegrative multiomic analysis identifies distinct molecular subtypes of NAFLD in a Chinese population
Ding J, Liu H, Zhang X, Zhao N, Peng Y, Shi J, Chen J, Chi X, Li L, Zhang M, Liu W, Zhang L, Ouyang J, Yuan Q, Liao M, Tan Y, Li M, Xu Z, Tang W, Xie C, Li Y, Pan Q, Xu Y, Cai S, Byrne C, Targher G, Ouyang X, Zhang L, Jiang Z, Zheng M, Sun F, Chai J. Integrative multiomic analysis identifies distinct molecular subtypes of NAFLD in a Chinese population. Science Translational Medicine 2024, 16: eadh9940. PMID: 39504356, DOI: 10.1126/scitranslmed.adh9940.Peer-Reviewed Original ResearchConceptsNonalcoholic fatty liver diseaseWhole-genome sequencingHepatocellular carcinomaMolecular subtypesLiver cirrhosisChinese cohort of patientsInfiltration of M1Risk of liver cirrhosisSerum metabolic analysisClinical diagnosisSubtype of nonalcoholic fatty liver diseaseCohort of patientsDevelopment of liver cirrhosisHepatocellular carcinoma developmentIntegrative multiomic analysisHealth care burdenFatty liver diseaseExpression of CYP1A2Urine specimensTreatment strategiesChinese cohortImpaired outcomeM2 macrophagesIntegrative multiomicsLiver diseaseGenomic Determinants of Clinical Outcomes in Multiple Myeloma with t(11;14)(CCND1;IGH) Treated with Venetoclax
Kaddoura M, Wiedmeier-Nutor J, Gupta V, Ziccheddu B, Shivaram S, Tang H, Fonseca R, Durante M, Matulis S, Jelinek T, Landgren O, Mitsiades C, Bergsagel P, Braggio E, Boise L, Fonseca R, Kumar S, Maura F, Baughn L. Genomic Determinants of Clinical Outcomes in Multiple Myeloma with t(11;14)(CCND1;IGH) Treated with Venetoclax. Blood 2024, 144: 249. DOI: 10.1182/blood-2024-204071.Peer-Reviewed Original ResearchProgression free survivalSingle nucleotide variantsWhole-genome sequencingMultiple myelomaMM patientsFocal deletionsCopy number variantsMechanisms of resistanceTraining cohortValidation cohortChronic lymphocytic leukemia treated with venetoclaxDisease progressionMAPK pathwayMedian progression free survivalPopulation of MM patientsDeterminants of clinical outcomeAnti-CD38 agentsTreated with venetoclaxComprehensive genomic profilingMAPK pathway mutationsStructural variantsAcute myeloid leukemiaGenomic eventsLoss of NoxaNovel drug combinationsSomatic mosaicism in schizophrenia brains reveals prenatal mutational processes
Maury E, Jones A, Seplyarskiy V, Nguyen T, Rosenbluh C, Bae T, Wang Y, Abyzov A, Khoshkhoo S, Chahine Y, Zhao S, Venkatesh S, Root E, Voloudakis G, Roussos P, Network B, Park P, Akbarian S, Brennand K, Reilly S, Lee E, Sunyaev S, Walsh C, Chess A. Somatic mosaicism in schizophrenia brains reveals prenatal mutational processes. Science 2024, 386: 217-224. PMID: 39388546, PMCID: PMC11490355, DOI: 10.1126/science.adq1456.Peer-Reviewed Original ResearchConceptsTranscription factor binding sitesWhole-genome sequencingOpen chromatinMutational processesSomatic mutationsFactor binding sitesSchizophrenia casesSchizophrenia risk genesSomatic mosaicismSomatic variantsRisk genesG mutationGene expressionGermline mutationsBinding sitesGenesMutationsIncreased somatic mutationsChromatinMosaic somatic mutationsPrenatal neurogenesisContext of schizophreniaBrain neuronsSchizophrenia brainVariants80. IMPLICATION OF COMPLEX STRUCTURAL GENOME VARIATION IN THE GENETIC ARCHITECTURE OF NEUROPSYCHIATRIC DISORDERS: INSIGHTS FROM HUMAN POPULATION ANALYSIS AND FROM POSTMORTEM BRAINS OF INDIVIDUALS WITH PSYCHIATRIC DISORDERS
Zhou B, Arthur J, Guo H, Kim T, Huang Y, Pattni R, Song G, Palejev D, Dohna H, Roussos P, Kundaje A, Hallmayer J, Snyder M, Wong, Urban A. 80. IMPLICATION OF COMPLEX STRUCTURAL GENOME VARIATION IN THE GENETIC ARCHITECTURE OF NEUROPSYCHIATRIC DISORDERS: INSIGHTS FROM HUMAN POPULATION ANALYSIS AND FROM POSTMORTEM BRAINS OF INDIVIDUALS WITH PSYCHIATRIC DISORDERS. European Neuropsychopharmacology 2024, 87: 93. DOI: 10.1016/j.euroneuro.2024.08.194.Peer-Reviewed Original ResearchWhole-genome sequencingComplex structural variationsHuman genomeMarker SNPsContinental populationsRisk allelesShort-read whole-genome sequencingSingle-nuclei RNA-seqFunctional genomics dataComplex genetic architectureDNA sequence variantsComplex genetic componentPost-mortem brainsPopulation-scale studiesDifferentially expressed genesVariant typeIntegration of genotypesStructural variationsGWAS lociGenome biologyCandidate lociIndividual genomesLinkage analysisGenomic analysisGenomic dataW32. A GENOME-WIDE ASSOCIATION STUDY OF BIPOLAR DISORDER FROM INDIA
Mahadevan J, Holla B, Ganesh S, Shankarappa B, Paul P, Sud R, Jain S, Purushottam M, Viswanath B. W32. A GENOME-WIDE ASSOCIATION STUDY OF BIPOLAR DISORDER FROM INDIA. European Neuropsychopharmacology 2024, 87: 118. DOI: 10.1016/j.euroneuro.2024.08.241.Peer-Reviewed Original ResearchGenome-wide association studiesGenomic risk lociRisk lociAssociation studiesGenome-wide association study of BDGenome wide association studiesAncestry principal componentsSevere mental illnessWhole-genome sequencingTissue expression analysisBiology of BdPatients of European ancestryBipolar disorderHRC panelGenome sequenceMental illnessAncestry samplesGenomic methodsEpisodes of depressionAllele dosageGenetic studiesEuropean ancestryICD-10Outpatient clinicTrained psychiatristsA cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders
Lee A, Ayers L, Kosicki M, Chan W, Fozo L, Pratt B, Collins T, Zhao B, Rose M, Sanchis-Juan A, Fu J, Wong I, Zhao X, Tenney A, Lee C, Laricchia K, Barry B, Bradford V, Jurgens J, England E, Lek M, MacArthur D, Lee E, Talkowski M, Brand H, Pennacchio L, Engle E. A cell type-aware framework for nominating non-coding variants in Mendelian regulatory disorders. Nature Communications 2024, 15: 8268. PMID: 39333082, PMCID: PMC11436875, DOI: 10.1038/s41467-024-52463-7.Peer-Reviewed Original ResearchConceptsNon-coding variantsCranial motor neuronsMendelian disordersIn vivo transgenic assayPredictor of enhancer activityCis-regulatory elementsMulti-omic frameworkWhole-genome sequencingEnhanced activityVariant discoveryGenome sequenceChromatin accessibilityPutative enhancersHistone modificationsRegulatory elementsGene expression assaysGene predictionTransgenic assaysEpigenomic profilingMendelian casesExpression assaysMutational enhancementCongenital cranial dysinnervation disordersCell typesFunctional impactGenome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections
Li K, Chaguza C, Stamp J, Chew Y, Chen N, Ferguson D, Pandya S, Kerantzas N, Schulz W, Initiative Y, Hahn A, Ogbunugafor C, Pitzer V, Crawford L, Weinberger D, Grubaugh N. Genome-wide association study between SARS-CoV-2 single nucleotide polymorphisms and virus copies during infections. PLOS Computational Biology 2024, 20: e1012469. PMID: 39288189, PMCID: PMC11432881, DOI: 10.1371/journal.pcbi.1012469.Peer-Reviewed Original ResearchConceptsGenome-wide association studiesSingle-nucleotide polymorphismsAssociation studiesWhole-genome sequencingAmino acid changesSingle nucleotide polymorphismsPairs of substitutionsViral copiesEpistasis testsGenome sequenceGenetic variationSpike geneAcid changesViral genomeNucleotide polymorphismsSARS-CoV-2Detect interactionsHost factorsVirus copiesCopyInfection dynamicsRT-qPCRPolymorphismOmicron BASARS-CoV-2 infectionSemi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies
Shyr D, Dey R, Li X, Zhou H, Boerwinkle E, Buyske S, Daly M, Gibbs R, Hall I, Matise T, Reeves C, Stitziel N, Zody M, Neale B, Lin X. Semi-supervised machine learning method for predicting homogeneous ancestry groups to assess Hardy-Weinberg equilibrium in diverse whole-genome sequencing studies. American Journal Of Human Genetics 2024, 111: 2129-2138. PMID: 39270648, PMCID: PMC11480788, DOI: 10.1016/j.ajhg.2024.08.018.Peer-Reviewed Original ResearchHardy-Weinberg equilibriumWhole-genome sequencing studiesWhole-genome sequencingHomogeneous ancestryWGS studiesDownstream analysisAssociation analysisPresence of population structureAncestry groupsGenetic ancestry groupsPopulation structureSequencing studiesSelf-reported raceGenetic researchQuality variantsAncestrySubsets of samplesProgram centersVariantsIncreasing diversityHeterogeneous sampleAncestralAssociationGeneticsSequenceUltra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction
Li X, Liu T, Bacchiocchi A, Li M, Cheng W, Wittkop T, Mendez F, Wang Y, Tang P, Yao Q, Bosenberg M, Sznol M, Yan Q, Faham M, Weng L, Halaban R, Jin H, Hu Z. Ultra-sensitive molecular residual disease detection through whole genome sequencing with single-read error correction. EMBO Molecular Medicine 2024, 16: 2188-2209. PMID: 39164471, PMCID: PMC11393307, DOI: 10.1038/s44321-024-00115-0.Peer-Reviewed Original ResearchMolecular residual diseaseCirculating tumor DNAWhole-genome sequencingCell-free DNAGenome sequenceDetection of molecular residual diseaseCirculating tumor DNA detectionResidual disease detectionConsistent with clinical outcomesVariant allele frequencyResidual diseaseMelanoma patientsMonitoring immunotherapyTumor DNAEsophageal cancerClinical outcomesColorectal cancerWGS technologiesAllele frequenciesCancerDNAAnalytical sensitivitySequenceImmunotherapyRelapseHuman genetics and epigenetics of alcohol use disorder
Zhou H, Gelernter J. Human genetics and epigenetics of alcohol use disorder. Journal Of Clinical Investigation 2024, 134: e172885. PMID: 39145449, PMCID: PMC11324314, DOI: 10.1172/jci172885.Peer-Reviewed Original ResearchConceptsEpigenome-wide association studiesEWAS studiesPower of GWASTranscriptome-wide associationGenome-wide scanAlcohol use disorderWhole-genome sequencingDrug-gene interactionsSingle-cell sequencingAssociation studiesDownstream analysisHuman geneticsGenetic variantsEpigenetic risk factorsVariant functionEpigenetic changesSpatial transcriptomicsUse disorderEpigeneticsDisease risk predictionGenetic correlationsDiversity of populationGeneticsComplex etiologyEnvironmental factors13. AmpliconSuite: Analyzing focal amplifications in cancer genomes
Luebeck J, Huang E, Dameracharla B, Kim F, Liefeld T, Ahuja R, Prasad D, Prasad G, Kim S, Kim H, Bailey P, Verhaak R, Deshpande V, Reich M, Mischel P, Mesirov J, Bafna V. 13. AmpliconSuite: Analyzing focal amplifications in cancer genomes. Cancer Genetics 2024, 286: s5. DOI: 10.1016/j.cancergen.2024.08.015.Peer-Reviewed Original ResearchWhole-genome sequencingWhole-genome sequencing dataFocal amplificationCancer genomesStructural variationsAmplification of oncogenesExtrachromosomal DNACopy numberEcDNAGenomeOncogene amplificationAmpliconArchitectCancer progressionAmplificationAmplification typeTumor samplesBiocondaNextflowPCAWGGenePatternRobust identificationDNACCLESequenceOncogene
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