SeqMonk: Using visualisation to identify errors and biases in genome scale sequencing data

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The increasing scale and complexity of genome scale studies has led to more widespread use of unsupervised analysis pipelines and reduced inspection and sanity checking of the underlying data.  Here we will illustrate how the use of interactive visualisation tools along with an explorative approach to analysis can identify problems which would otherwise go undetected by standard pipelines.