Gene Expression Analysis c Flashcards

What are FPKM and TPM both?measures of relative abundance of a transcript in pool of transcriptsWhat can be done with FPKM and TPM to make them appropriate for between sample normalisation?making further assumptions allows us to develop suitable methodsWhy is total read count not an accurate normalisation factor?highly and differentially expressed genes can distort gene abundance measuresWhat do we need to find for between sample normalisation?want to find control set of transcripts that are not DE and use these to estimate size factors that enable meaningful comparisons between samples; typically can use housekeeping genesWhat methods exist for between sample normalisation and what is the key assumption for them?Trimmer Mean of M values (TMM) and median of ratios; assume most genes are not DEDescribe TMMuses trimmed weighted means, excludes gene with large log-fold ratios between samples and those with extreme abundance values before calculating weighted mean of log-fold changesWhat package uses TMM?edgeRDescribe median of ratiosuses median of ratios of observed counts; for each gene, calculate mean of expression across all samples and treat this as pseudo-reference, then calculate ratio of observed genes counts to pseudo-references, and take median value as size factor for each sampleWhat package uses median of ratios?DESeq2What does sensitivity analysis involve?vary some assumptions/parameters and see if we still get the same answerAs well as normalisation, what else might be required for RNA-seq?may need to correct for batch effectsWhat are batch effects?confounding factors that cause unwanted variation in gene abundances between samples, due to technical factors that differ across batchesWhat are batches?samples that are processed in parallelGive examples of causes of batch effectsdifferences in reagents, equipment, or date of library preparation for sequencingGive examples of tools that can be used for batch correctionCOMBAT and SVAseqWhat is necessary for batch correction programs?need suitable experimental design so technical and experimental factors are not confoundedHow does COMBAT work?uses PCA to try and correct, but does assume most of the variation is caused by noise, and not biologically relevantHow can we plot data to view differential expression?heat map of DE gene counts with dendrograms, and volcano plots showing log-fold change in expressionWhat does a smaller p-value mean?lower likelihood of the change occurring by chanceWhat is required for identification of differentially expressed genes?replicates, where at least 3 biological replicates are recommendedWhat is the issue with DE identification requiring biological replicates?RNA-seq experiments often have few replicates so specialised statistical methods are requiredWhat do the specialised statistical methods for DE analysis do?many individual statistical hypothesis tests are performed for all the genes so p-values need to be corrected for multiple testingWhat do the specialised statistical methods for DE analysis require?normalised data, as they perform an integrated normalisation step; want to use raw/estimated read countsHow are DE genes often selected?by setting thresholds for significance (p-value) and log-fold changeWhat might we do with the results from DE analysis?validate the genes experimentally with targeted methods, functional analysis, downstream statistical analyses, experimental designAs well as quantifying gene expression, what does RNA-seq allow us to identify?changes in isoform expression due to alternative splicing, and gene fusion eventsWhat is RNA mis-splicing associated with?many diseases, such as mutations in the lamina gene causing several types of mis-splicing associated with specific diseasesWhat might mutations affect when disrupting alternative splicing?RNA cis-regulatory elements, spliceosomal components, or trans-acting regulatory factorsWhat leads to fused transcripts?chromosomal rearrangementsWhere are gene fusions commonly reported?many types of cancer, and may be used for diagnosis and prognosis

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