http://www.nature.com/ncomms/2015/150121/ncomms7033/full/ncomms7033.html
Julie Brind’Amour,
Sheng Liu,
Matthew Hudson,
Carol Chen,
Mohammad M. Karimi
& Matthew C. Lorincz
Nature Communications 6, Article number: 6033 doi:10.1038/ncomms7033
http://www.nature.com/ncomms/2015/150121/ncomms7033/full/ncomms7033.html
Julie Brind’Amour,
Sheng Liu,
Matthew Hudson,
Carol Chen,
Mohammad M. Karimi
& Matthew C. Lorincz
Nature Communications 6, Article number: 6033 doi:10.1038/ncomms7033
http://www.nature.com/neuro/journal/v19/n1/abs/nn.4181.html
Andrew E Jaffe,
Yuan Gao,
Amy Deep-Soboslay,
Ran Tao,
Thomas M Hyde,
Daniel R Weinberger
& Joel E Kleinman
Nature Neuroscience 19, 40–47 (2016) doi:10.1038/nn.4181
Spatial genomic heterogeneity w/in…prostate #cancer
http://www.nature.com/ng/journal/v47/n7/full/ng.3315.html WGS analysis of many sites suggests divergent tumor evolution
Boutros…, van der Kwast, Bristow (2015) “Spatial genomic
heterogeneity within localized, multi-focal prostate cancer” Nature Genetics 47(7):736-745 (PMID: 26005866)
This work represents the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcomes at the level of whole-genome sequencing (WGS). Five patients, with index tumors of Gleason score 7, were subjected to a WGS protocol with spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity. In their analysis, Boutros et al, discovered recurrent amplification of MYCL, which is associated with TP53 loss. This finding is one of the first clear functional distinctions between MYC family members in prostate cancer and suggests that MYCL amplification may be preferentially localized in the index lesion. Overall, the authors believe their results are useful in the development of prognostic biomarkers that are necessary to achieve personalized prostate cancer medicine. It is important to note that such diagnostic biopsy protocols can miss regions of more aggressive cancers resulting in the patient being under-staged.
http://www.cell.com/cell/pdf/S0092-8674(15)01504-4.pdf
Dynamics of genomic clones in breast #cancer PDX at #singlecell resolution http://www.nature.com/nature/journal/v518/n7539/full/nature13952.html Extensive trees of samples & some WGS
Peter Eirew,
Adi Steif,
Jaswinder Khattra,
Gavin Ha,
…
Jazmine Brimhall,
Arusha Oloumi,
Tomo Osako
et al.
Nature 518, 422–426 (19 February 2015) doi:10.1038/nature13952
#SingleCell #RNASeq Reveals Dynamic, Random Monoallelic Gene Expression, occurring in ~20% of genes in mice cells
http://science.sciencemag.org/content/343/6167/193.abstract
Health ROI as a measure of misalignment of…needs & resources by @arzhetsky http://www.nature.com/nbt/journal/v33/n8/full/nbt.3276.html See funding decisions like stock trades
QT:{{"In a recently published letter to Nature Biotechnology, Lixia Yao,
IGSB core faculty Andrey Rzhetsky and colleagues dissect the decisions
made in funding choices. His team compares these choices by funding
agencies to trades in a financial market. In this communication, they
expand on the idea that there exists an imbalance between health needs
and biomedical research investment.
In order to fairly examine the relationship between biomedical need
and biomedical research, they validated a new, insurance based measure
of health burden that enables automatic evaluation of burden and
research investment for many more diseases than have been previously
assessed. "
"}}
Tumor genome simulation w/ #crowdsourcing to benchmark…SNV detection http://www.nature.com/nmeth/journal/v12/n7/full/nmeth.3407.html Addresses lack of gold standards & privacy
Ewing, Houlahan…..Stuart, Boutros (2015) “Combining accurate
tumour genome simulation with crowd-sourcing to benchmark somatic
single nucleotide variant detection” Nature Methods 12(7):623-630
(PMID: 25984700)
A crowdsourced benchmark of somatic mutation detection algorithms was
introduced for the ICGC-TCGA DREAM challenge. This has the advantage
of dealing with the lack of gold standard data and the issue of
sharing private genomic data. All groups worked on three different
simulated tumor-normal pairs generated with BAMSurgeon, by directly
adding synthetic mutations to existing reads. An ensemble of
pipelines outperforms the best individual pipeline in all cases,
assessed on the basis of recall, precision and F-score.
Parameterization and genomic localization both have an effect on
pipeline performance, while characteristics of prediction errors
differed for most pipelines.
Bias from removing read duplication [eg from PCR amplification] in ultra-deep #sequencing
http://bioinformatics.oxfordjournals.org/content/early/2014/01/02/bioinformatics.btt771 pot. overcorrection issues
Zhou et al.
Bias from removing read duplication in ultra-deep sequencing experiments
Estimating variant allele frequency and copy number variations can be approached by counting reads. In practice, read counting is
complicated by bias from PCR amplification and from sampling coincidence. This paper assessed the overcorrection introduced while removing read duplicates. The overcorrection is a particular concern when the sequencing is ultra-deep and the insert size is short and non-variant.
Folding by Chaperones Accelerates Evolutionary Dynamics
http://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1003269 Multiscale models link NT mutations, PPIs & cell populations