@article {501, title = {STRetch: detecting and discovering pathogenic short tandem repeat expansions.}, journal = {Genome Biol}, volume = {19}, year = {2018}, month = {2018 08 21}, pages = {121}, abstract = {

Short tandem repeat (STR) expansions have been identified as the causal DNA mutation in dozens of Mendelian diseases. Most existing tools for detecting STR variation with short reads do so within the read length and so are unable to detect the majority of pathogenic expansions. Here we present STRetch, a new genome-wide method to scan for STR expansions at all loci across the human genome. We demonstrate the use of STRetch for detecting STR expansions using short-read whole-genome sequencing data at known pathogenic loci as well as novel STR loci. STRetch is open source software, available from github.com/Oshlack/STRetch .

}, keywords = {Alleles, Chromosomes, Human, DNA Repeat Expansion, Genetic Loci, Genome, Human, Humans, Microsatellite Repeats, Polymerase Chain Reaction, Software}, issn = {1474-760X}, doi = {10.1186/s13059-018-1505-2}, author = {Dashnow, Harriet and Lek, Monkol and Phipson, Belinda and Halman, Andreas and Sadedin, Simon and Lonsdale, Andrew and Davis, Mark and Lamont, Phillipa and Clayton, Joshua S and Laing, Nigel G and MacArthur, Daniel G and Oshlack, Alicia} } @article {551, title = {Ximmer: a system for improving accuracy and consistency of CNV calling from exome data.}, journal = {Gigascience}, volume = {7}, year = {2018}, month = {2018 10 01}, abstract = {

Background: While exome and targeted next-generation DNA sequencing are primarily used for detecting single nucleotide changes and small indels, detection of copy number variants (CNVs) can provide highly valuable additional information from the data. Although there are dozens of exome CNV detection methods available, these are often difficult to use, and accuracy varies unpredictably between and within datasets.

Findings: We present Ximmer, a tool that supports an end-to-end process for evaluating, tuning, and running analysis methods for detection of CNVs in germline samples. Ximmer includes a simulation framework, implementations of several commonly used CNV detection methods, and a visualization and curation tool that together enable interactive exploration and quality control of CNV results. Using Ximmer, we comprehensively evaluate CNV detection on four datasets using five different detection methods. We show that application of Ximmer can improve accuracy and aid in quality control of CNV detection results. In addition, Ximmer can be used to run analyses and explore CNV results in exome data.

Conclusions: Ximmer offers a comprehensive tool and method for applying and improving accuracy of CNV detection methods for exome data.

}, keywords = {Algorithms, Computational Biology, Computer Simulation, DNA Copy Number Variations, Exome, High-Throughput Nucleotide Sequencing, Humans, Reproducibility of Results, ROC Curve, Sensitivity and Specificity, Software}, issn = {2047-217X}, doi = {10.1093/gigascience/giy112}, author = {Sadedin, Simon P and Ellis, Justine A and Masters, Seth L and Oshlack, Alicia} }