2022
All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons
Sarangi V, Jang Y, Suvakov M, Bae T, Fasching L, Sekar S, Tomasini L, Mariani J, Vaccarino FM, Abyzov A. All2: A tool for selecting mosaic mutations from comprehensive multi-cell comparisons. PLOS Computational Biology 2022, 18: e1009487. PMID: 35442945, PMCID: PMC9060341, DOI: 10.1371/journal.pcbi.1009487.Peer-Reviewed Original Research
2021
Comprehensive identification of somatic nucleotide variants in human brain tissue
Wang Y, Bae T, Thorpe J, Sherman MA, Jones AG, Cho S, Daily K, Dou Y, Ganz J, Galor A, Lobon I, Pattni R, Rosenbluh C, Tomasi S, Tomasini L, Yang X, Zhou B, Akbarian S, Ball LL, Bizzotto S, Emery SB, Doan R, Fasching L, Jang Y, Juan D, Lizano E, Luquette LJ, Moldovan JB, Narurkar R, Oetjens MT, Rodin RE, Sekar S, Shin JH, Soriano E, Straub RE, Zhou W, Chess A, Gleeson JG, Marquès-Bonet T, Park PJ, Peters MA, Pevsner J, Walsh CA, Weinberger DR, Vaccarino F, Moran J, Urban A, Kidd J, Mills R, Abyzov A. Comprehensive identification of somatic nucleotide variants in human brain tissue. Genome Biology 2021, 22: 92. PMID: 33781308, PMCID: PMC8006362, DOI: 10.1186/s13059-021-02285-3.Peer-Reviewed Original ResearchMeSH KeywordsAllelesBrainChromosome MappingComputational BiologyGenetic Association StudiesGenetic VariationGenomicsGerm CellsHigh-Throughput Nucleotide SequencingHumansOrgan SpecificityPolymorphism, Single NucleotideConceptsSomatic SNVsSomatic single nucleotide variantsWhole-genome sequencing dataSequencing dataBulk DNA samplesCell lineage treesSomatic mosaicismSingle nucleotide variantsLineage treesSomatic nucleotide variantsCellular processesDNA replicationHuman genomeSomatic tissuesDNA repairNucleotide variantsComprehensive identificationDNA samplesMosaic variantsNon-cancerous tissuesDNASingle individualMultiple replicatesHuman brain tissueVariantsMachine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia
Zhu X, Zhou B, Pattni R, Gleason K, Tan C, Kalinowski A, Sloan S, Fiston-Lavier AS, Mariani J, Petrov D, Barres BA, Duncan L, Abyzov A, Vogel H, Moran J, Vaccarino F, Tamminga C, Levinson D, Urban A. Machine learning reveals bilateral distribution of somatic L1 insertions in human neurons and glia. Nature Neuroscience 2021, 24: 186-196. PMID: 33432196, PMCID: PMC8806165, DOI: 10.1038/s41593-020-00767-4.Peer-Reviewed Original ResearchMeSH KeywordsAdaptor Proteins, Signal TransducingAdultCation Transport ProteinsEmbryonic DevelopmentFemaleGenomeHeLa CellsHigh-Throughput Nucleotide SequencingHumansLong Interspersed Nucleotide ElementsMachine LearningMental DisordersMutagenesis, InsertionalNeurogliaNeuronsPregnancyRetroelementsSchizophreniaConceptsBrain developmentPossible pathological effectsAnatomical distributionBilateral distributionHuman neuronsNervous systemHuman nervous systemNeuropsychiatric diseasesNeuropsychiatric disordersGliaPathological effectsNeuronsSomatic L1 insertionsWhole-genome sequencingHuman brainSomatic retrotransposition
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 ResearchMeSH KeywordsCell DifferentiationDNAHigh-Throughput Nucleotide SequencingHumansInduced Pluripotent Stem CellsNeuronsNucleic Acid Amplification TechniquesPolymorphism, Single NucleotideSequence Analysis, DNASingle-Cell AnalysisConceptsMultiple 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