Transcription of Practical Guide to Interpreting RNA-seq Data
{{id}} {{{paragraph}}}
Practical Guide to Interpreting RNA-seq DataSkyler Kuhn1,2 Mayank Tandon1,21. CCR Collaborative Bioinformatics Resource (CCBR), Center for Cancer Research, NCI2. Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer ResearchOverviewI. Experimental DesignHypothesis-drivenOverview of Best PracticeII. Quality-controlPre- and post- alignment QC metricsInterpretationIII. PipelineFastQ Files -> Counts matrixReproducibility 1IV. Downstream AnalysisPrincipal Components Analysis (PCA)Differential ExpressionPathway AnalysisV. Advanced VisualizationsGroup comparisonsAlternative Splicing EventsPathway Diagrams Design: Overview Hypothesis-drivenAddresses a well thought-out quantifiable questionConsiderations: Library Construction: mRNA versus total RNAS ingle-end versus Paired-end SequencingSequencing Depth: quantifying gene-level or transcript-level expressionNumber of Replicates: statistical-power and abilit
Practical Guide to Interpreting RNA-seq Data Skyler Kuhn1,2 Mayank Tandon1,2 1. CCR Collaborative Bioinformatics Resource (CCBR), Center for Cancer Research, NCI 2. Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research
Domain:
Source:
Link to this page:
Please notify us if you found a problem with this document:
{{id}} {{{paragraph}}}