2025
Guidelines to Analyze ChIP-Seq Data: Journey Through QC and Analysis Considerations
De Kumar B, Krishnan J. Guidelines to Analyze ChIP-Seq Data: Journey Through QC and Analysis Considerations. Methods In Molecular Biology 2025, 2889: 193-206. PMID: 39745614, DOI: 10.1007/978-1-0716-4322-8_14.Peer-Reviewed Original ResearchConceptsChIP-seqChIP-seq analysisQC metricsProperties of transcription factorsNext-generation sequencing approachChIP-seq experimentsStudy DNA-protein interactionsGene regulatory propertiesDNA-protein interactionsENCODE consortiumChromatin stateSequencing approachTranscription factorsChromatinGenesNext-generationImmunoprecipitationSequence
2016
TCR Sequencing Can Identify and Track Glioma-Infiltrating T Cells after DC Vaccination
Hsu M, Sedighim S, Wang T, Antonios J, Everson R, Tucker A, Du L, Emerson R, Yusko E, Sanders C, Robins H, Yong W, Davidson T, Li G, Liau L, Prins R. TCR Sequencing Can Identify and Track Glioma-Infiltrating T Cells after DC Vaccination. Cancer Immunology Research 2016, 4: 412-418. PMID: 26968205, PMCID: PMC4873445, DOI: 10.1158/2326-6066.cir-15-0240.Peer-Reviewed Original ResearchConceptsTumor-infiltrating lymphocytesT cell receptorT-cell receptor sequencingImmune responseOverall survivalPeripheral bloodIncreased time to progressionTumour-infiltrating lymphocytes contentAssessment of tumor-infiltrating lymphocytesPredictors of immune responseAntigen-specific immune responsesTime to progressionDendritic cell immunotherapyDC vaccinesCell immunotherapyImmunotherapeutic strategiesSurvival outcomesStatistically significant correlationT cellsClinical outcomesAdjunctive treatmentBrain tumorsImmunotherapyNext-generation sequencing approachTumor
2012
Next-generation sequencing of FFPE solid tumor specimens for clinical use.
Yelensky R, Wang K, Dogan S, Borsu L, Frampton G, Lipson D, Stephens P, Bastian B, Klimstra D, Ladanyi M, Cronin M, Hedvat C, Berger M. Next-generation sequencing of FFPE solid tumor specimens for clinical use. Journal Of Clinical Oncology 2012, 30: 10524-10524. DOI: 10.1200/jco.2012.30.15_suppl.10524.Peer-Reviewed Original ResearchNext-generation sequencingCopy changesNext-generation sequencing approachGenomic alterationsLoss-of-function variantsMutant allele frequencyIndividual base pairsConcordant callsFFPE specimensSequence dataGene characterizationLibrary constructionCancer genesBase pairsSolid tumor specimensAllele frequenciesSomatic alterationsDetect mutationsPotential clinical roleInfluence treatment decisionsFusion geneExonMutationsAverage coverageHybridization capture
2011
Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling
Gu H, Smith ZD, Bock C, Boyle P, Gnirke A, Meissner A. Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nature Protocols 2011, 6: 468-481. PMID: 21412275, DOI: 10.1038/nprot.2010.190.Peer-Reviewed Original ResearchConceptsSingle-nucleotide resolutionGenome-scale DNA methylation profilingCpG-rich DNA fragmentsGenome-wide mappingGenome-wide scaleStandard molecular biology laboratoryMajority of promotersRelevant genomic regionsIllumina Genome AnalyzerNext-generation sequencing approachDNA methylation profilingDNA methylation measurementsRestriction enzyme MspIReduced representationMolecular biology laboratoryGenomic regionsRRBS librariesGenome AnalyzerSequencing librariesMethylation profilingSequencing approachEnzyme MspIAmount of sequencingLow input requirementsGenomic DNA
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