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Analyses biostatistiques de données RNA-seq NathalieVialaneix(MIAT,INRA) encollaborationavecIgnacioGonzàlesetAnnickMoisan [email protected] http://www.nathalievialaneix.eu Toulouse,11/12février2019 NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 1/63 Outline 1 Exploratoryanalysis Introduction Experimentaldesign Dataexplorationandqualityassessment 2 Normalization Rawdatafiltering Interpretingreadcounts 3 DifferentialExpressionanalysis Hypothesistestingandcorrectionformultipletests DifferentialexpressionanalysisforRNAseqdata Interpretingandimprovingtheanalysis NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 2/63 A typical transcriptomic experiment NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 3/63 A typical transcriptomic experiment NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 3/63 Outline 1 Exploratoryanalysis Introduction Experimentaldesign Dataexplorationandqualityassessment 2 Normalization Rawdatafiltering Interpretingreadcounts 3 DifferentialExpressionanalysis Hypothesistestingandcorrectionformultipletests DifferentialexpressionanalysisforRNAseqdata Interpretingandimprovingtheanalysis NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 4/63 A typical RNA-seq experiment 1 collectsamples 2 generatelibrariesofcDNA fragments 3 affectmaterialtoonelanein oneflowcell NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 5/63 Steps in RNAseq data analysis NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 6/63 Part I: Experimental design NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 7/63 In summary, what is a good experimental design? Experimentaldesignareusuallynotassimpleasthisexample: theycan includemultipleexperimentalfactors(dayofexperiment,flowcell,...) and multiplecovariates(sex,parents,...). ⇒Theexperimentaldesignmustbecarefullythoughtbeforestartingthe experimentandconfoundedeffectsmustbesearchedforinasystematic manner. Confounded effects: a simple example Basicexperiment: finddifferencesbetweencontrol/treatedplants controlgroupplant treatedgroupplant NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 8/63 In summary, what is a good experimental design? Experimentaldesignareusuallynotassimpleasthisexample: theycan includemultipleexperimentalfactors(dayofexperiment,flowcell,...) and multiplecovariates(sex,parents,...). ⇒Theexperimentaldesignmustbecarefullythoughtbeforestartingthe experimentandconfoundedeffectsmustbesearchedforinasystematic manner. Confounded effects: a simple example Basicexperiment: finddifferencesbetweencontrol/treatedplants controlgroupplant treatedgroupplant Abadexperimentaldesign: growallcontrolgroupplantsinonefieldand growalltreatedgroupplantsinanotherfield Field 1 Field 2 becauseyoucannotdifferentiatebetweendifferencesduetothefieldand differencesduetothetreatment⇒confoundedeffects NV2 (INRA) BiostatistiqueRNA-seq Toulouse,11/12février2019 8/63

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first gene: different median levels between the two groups but large variance: differences may be non significant second gene: different median levels

Analyses biostatistiques de données RNA-seq PDF

124 Pages·2017·6.96 MB·French

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first gene: different median levels between the two groups but large variance: differences may be non significant second gene: different median levels

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Publication Year:	2017
Pages:	124
Language:	French
File Size:	6.96
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