Month: June 2017

MutSigNC

[PMID:28658208] [Nature]

Recurrent and functional regulatory mutations in breast cancer

“deep sequencing in 360 primary breast cancers and develop computational methods to identify significantly mutated promoters.” “promoter regions harbour recurrent mutations in cancer with functional consequences and that the mutations occur at similar frequencies as in coding regions.” Work from Gad Getz.

[PMID:28658210] [Nature]

Cancer genomics: Less is more in the hunt for driver mutations

“The authors’ power analysis (statistical calculations estimating the sample numbers needed to detect an effect of a given size) indicated that more than 90% of drivers could be reliably identified if they occurred in at least 10% of the 360 samples studied, but only 70% of drivers present in 5%of patients would be identified”

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DNA Methylation Markers

[PMID:28652331] [Proceedings of the National Academy of Sciences]

DNA methylation markers for diagnosis and prognosis of common cancers

“We identified cancer markers in a training cohort of 1,619 tumor samples and 173 matched adjacent normal tissue samples. We replicated our findings in a separate TCGA cohort of 791 tumor samples and 93 matched adjacent normal tissue samples, as well as an independent Chinese cohort of 394 tumor samples and 324 matched adjacent normal tissue samples. The DNA methylation analysis could predict cancer versus normal tissue with more than 95% accuracy in these three cohorts, demonstrating accuracy comparable to typical diagnostic methods. This analysis also correctly identified 29 of 30 colorectal cancer metastases to the liver and 32 of 34 colorectal cancer metastases to the lung. We also found that methylation patterns can predict prognosis and survival.”

15-20X Coverage for Singletons

[PMID:28640830] [PLoS Genetics]

Optimal sequencing strategies for identifying disease-associated singletons

“We show that the power to detect singletons increases with coverage, typically plateauing for coverage > ~25x. Next, we show that, when total sequencing capacity is fixed, the power of association studies focused on singletons is typically maximized for coverage of 15-20x, independent of relative risk, disease prevalence, singleton burden, and case-control ratio. Our results suggest sequencing depth of 15-20x as an appropriate compromise of singleton detection power and sample size for studies of rare variants in complex disease.” Work from Abecasis.

cfDNA in 10K Cases

[PMID:28617416] [Genetics in Medicine]

Genome-wide cfDNA screening: clinical laboratory experience with the first 10,000 cases

“the first description of clinical experience with genome-wide cfDNA analysis for prenatal screening, within the first year of the test’s introduction”

Comparison of Hi-C Algorithms

[PMID:28604721] [Nature Methods]

Comparison of computational methods for Hi-C data analysis

“We quantitatively compared the performance of 13 algorithms in their analyses of Hi-C data from six landmark studies and simulations. This comparison revealed differences in the performance of methods for chromatin interaction identification, but more comparable results for topologically associating domains (TAD) detection between algorithms.”