2020
SCELLECTOR: ranking amplification bias in single cells using shallow sequencing
Sarangi V, Jourdon A, Bae T, Panda A, Vaccarino F, Abyzov A. SCELLECTOR: ranking amplification bias in single cells using shallow sequencing. BMC Bioinformatics 2020, 21: 521. PMID: 33183232, PMCID: PMC7663899, DOI: 10.1186/s12859-020-03858-y.Peer-Reviewed Original ResearchConceptsMultiple displacement amplificationShallow sequencingSingle-cell platformsSingle-cell sequencingCoverage sequencing dataSingle cellsHuman neuronal cellsMosaic mutationsAmount of DNAAmplification qualityCell sequencingCoverage sequencingHigh-coverage dataSequencing dataHaplotype informationPhi29 polymeraseDNA damageIndividual cellsNeuronal cellsSequencingAmplification biasAllelic imbalancePresence of sitesMutationsFragment length
2015
Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors
Mitra A, Mukherjee U, Harding T, Jang J, Stessman H, Li Y, Abyzov A, Jen J, Kumar S, Rajkumar V, Van Ness B. Single-cell analysis of targeted transcriptome predicts drug sensitivity of single cells within human myeloma tumors. Leukemia 2015, 30: 1094-1102. PMID: 26710886, DOI: 10.1038/leu.2015.361.Peer-Reviewed Original ResearchConceptsSingle cellsIndividual cellsSignificant genetic diversitySingle-cell analysisGene expression profile signaturesSingle-cell levelGenetic diversityTranscriptome analysisDrug responseCellular responsesDrug sensitivityBulk populationInhibitor sensitivitySubclonal architectureProfiling studiesPCR analysisPrediction programsCell linesMyeloma cell linesTumor progressionCellsIntratumor heterogeneityProfile signaturesProteasome inhibitor sensitivitySubclonal level