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Exercise

Calculate QC metrics

To remove problematic cells and genes, we want to calculate quality control metrics using the calculateQCMetrics() function from the package scater, which is a useful package for quality control and analysis of single-cell data. These metrics will help us filter out low quality genes and cells.

Remember that to identify problematic cells, experimentalists sometimes use synthetic spike-in RNAs as positive controls. The spike-in RNA names start with "ERCC", and are already stored as isSpike(sce, "ERCC").

Instructions
100 XP

  • Load the library scater.

  • Use the calculateQCMetrics() function to calculate quality control (QC) metrics and assign it back to sce. A list of the QC metrics calculated by this function is available in the documentation of the function (type ?calculateQCMetrics in the console to access the help).

  • After calculateQCMetrics() has been applied to sce, columns are added to colData(sce). Explore colData(sce).

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