单细胞转录组数据分析从原始数据到细胞类型注释
——从原始数据到细胞类型注释 单细胞转录组数据分析
natureConstructionofahumancelllandscapeatsingle-cell人类细胞图谱levelAdult adiposeAdultthyroidglandAdult adrenal glandAdulttracheaAdult arteryeAdulttransversecoloneAdultascendingcolonAdultureterAdultbladderAdult uterus1822AdultbonemarrowChorionicvillusFetalstromalcellAdult cerebellumCordbloodAdultcervixCordbloodCD34P11AdultduodenumFetal adrenal glandAdult epityphlonFetal brainAdultoesophagusepithelialcellFetal calvariaAdultfallopian tube7FFetal eyesAdult gall bladderENFetal femalegonad46AdultheartFetal heartAdult ileumAdOEndotheliailFetal intestineAdult jejunumFetalkidneyAdult kidney89%oFetal liver8Adult liver10057Fetal lung18Adult lungFetal malegonad14Adultmuscle2FetalmuscleAdultomentumFetalpancreasAdultpancreas50Fetal ribAdultperipheralblood32Fetal skinAdultpleuraFetal spinal cordAdultprostate97FetalstomachAdultrectumAdultsigmoidcolonFetal thymusMacrophageAdultspleenHumanEScells91AdultstomachNeonataladrenalglandAdulttemporal lobePlacentat-SNE1c>简介》实例分析原始数据处理表达矩阵处理和可视化细胞类型注释
人类细胞图谱 简介 原始数据处理 表达矩阵处理和可视化 细胞类型注释 实例分析
为什么要进行单细胞研究？·没有完全相同的两片树叶无法区分以下情况Western BlotPCRbulkRNAseqsingle-cell RNAseqorgan/tissueSteinheueretal.,bioRxiv,2021https://mp.weixin.qq.com/s/5laEGHM2iWSLRuOiaBbr7Q>简介原始数据处理表达矩阵处理和可视化细胞类型注释实例分析
为什么要进行单细胞研究？ • 没有完全相同的两片树叶 Steinheuer et al., bioRxiv, 2021 https://mp.weixin.qq.com/s/5laEGHM2iWSLRu0iaBbr7Q • 无法区分以下情况 简介 原始数据处理 表达矩阵处理和可视化 细胞类型注释 实例分析
C单细胞转录组测序技术比较High scoreLowscoreo·综合比较结果score100rkingUMIStrandMethodsTranscriptReferences2specificcoveragepossibility.NoTang methodNearlyNoTang et al., 2009Be-Methodfull-lengthNoNoFull-lengthQuartz-SeqSasagawa:et-al., 2013Quartz-seq2NoNoSUPeR-seqFull-lengthFan X. et al., 2015ChromiumNoNoSmart-seqFull-lengthRamskold et al., 2012NoNoSmart-seq2Full-lengthPicell et al., 2013Smart-seq2YesFull-lengthYesMATQ-seqSheng et al., 2017CEL-seq2YesYesSTRT-seq5'-onlyIslam et al., 2011, 2012andSTRT/C1C1HT-mediumYesYesCEL-Seq3'-onlyHashimshory et al., 2012C1HT-small3'-onlyYesYesCEL-seq2Hashimshony et al., 2016福YesYes:MARS-Seq3'-onlyJaitin et al., 2014ddSEQ83'-onlyYesYesCytoSeqFan.H.C:et al., 2015Chromium (sn)?YesDrop-seq3'-onlyYesMacosko et al., 2015Drop-seqoYesYesOInDrop3'-onlyKlein et al., 2015?YesYesChromium3'-onlyZheng et al., 2017inDrop??YesSPLIT-seq3'-onlyYesRosenberg et al., 2018ICELL8.福3'-onlyYesYes?sci-RNA-seqCao et al., 20173'-onlyYesYesSeq-WellGierahn et al., 2017MARS-seqo..YesYes:DroNC-seq3'-onlyHabib et al., 2017gmcSCRB-seqC..3'-onlyYesYesQuartz-Seq2Sasagawa et al., 2018Mereuetal.,NatureBiotechnology2020Chen et al.,Frontiers in Genetics.2019>简介原始数据处理表达矩阵处理和可视化细胞类型注释实例分析
• 综合比较结果 Mereu et al., Nature Biotechnology , 2020 Chen et al., Frontiers in Genetics. 2019 简介 原始数据处理 表达矩阵处理和可视化 细胞类型注释 实例分析 单细胞转录组测序技术比较
单细胞转录组测序微流控TheChromiumSingleCellGeneExpressionSolutionPooRTCollectRemoveOilt.0.-Oil10xBarcodedGel BeadsCellsEnzymeGelBeadTruSeq Read 1PolyidTWNSingle Cell10xBarcoded10xBarcodedMCDNAGEMSCDNANextera Read.1(Read 1N)CaptureSenSingle Cell3'10xUMIv3.1Gel BeaddedatPrimersNexfera Read T(Read 1N)uneseg:TOUMIhttps://www.10xgenomics.com>简介原始数据处理表达矩阵处理和可视化细胞类型注释实例分析
7 单细胞转录组测序 • 微流控 The Chromium Single Cell Gene Expression Solution https://www.10xgenomics.com 简介 原始数据处理 表达矩阵处理和可视化 细胞类型注释 实例分析