A comparative analysis of algorithms for somatic SNV detection in cancer

Motivation: With the advent of relatively affordable high-throughput technologies, DNA sequencing of cancers is now common practice in cancer research projects and will be increasingly used in clinical practice to inform diagnosis and treatment. Somatic (cancer-only) single nucleotide variants (SNVs) are the simplest class of mutation, yet their identification in DNA sequencing data is confounded by germline polymorphisms, tumour heterogeneity and sequencing and analysis errors. Four recently published algorithms for the detection of somatic SNV sites in matched cancer–normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer–normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterized and compared to investigate the strengths and weaknesses of each SNV calling algorithm. Results: Comparing the candidate SNV sets returned by VarScan, SomaticSniper, JointSNVMix2 and Strelka revealed substantial differences with respect to the number and character of sites returned; the somatic probability scores assigned to the same sites; their susceptibility to various sources of noise; and their sensitivities to low-allelic-fraction candidates.Nicola D. Roberts, R. Daniel Kortschak, Wendy T. Parker, Andreas W. Schreiber, Susan Branford, Hamish S. Scott, Garique Glonek and David L. Adelso

Reanalysis of travelling speed and the risk of crash involvement in Adelaide South Australia

Modified logistic regression modelling was used to reanalyse free travelling speed case control data in an urban 60 km/h speed limit environment. An exponentiated second order polynomial function was used to model the relative risk of being involved in a casualty crash based on free travelling speed. The relative risk was found to approximately double for each 5 km/h increase in free travelling speed. This curve and the original data were then used to estimate the effects of various hypothetical speed reduction scenarios. Illegal speeding was found to be a major factor in casualty crashes and it was found that even very small reductions in the speeds of vehicles in general could be expected to result in a major reduction in the frequency of casualty crashes in an urban area.C.N. Kloeden, A.J. McLean and G. Glone