PlotsOfDifferences – a web app for the quantitative comparison of unpaired data, bioRxiv, 2019-03-18

AbstractThe quantitative comparison of data acquired under different conditions is an important aspect of experimental science. The most widely used statistic for quantitative comparisons is the p-value. However, p-values suffer from several shortcomings. The most prominent shortcoming that is relevant for quantitative comparisons is that p-values fail to convey the magnitude of differences. The differences between conditions are best quantified by the determination of effect size. To democratize the calculation of effect size, we have developed a web-based tool. The tool uses bootstrapping to resample mean or median values for each of the conditions and these values are used to calculate the effect size and their compatibility interval. The web tool generates a graphical output, showing the bootstrap distribution of the difference next to the actual data for optimal interpretation. A tabular output with statistics and effect sizes is also generated and the table can be supplemented with p-values that are calculated with a randomization test. The app that we report here is dubbed PlotsOfDifferences and is available at <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpshuygens.science.uva.nlPlotsOfDifferences>httpshuygens.science.uva.nlPlotsOfDifferences<jatsext-link><jatsfig id=ufig1 position=float fig-type=figure orientation=portrait><jatsgraphic xmlnsxlink=httpwww.w3.org1999xlink xlinkhref=578575_ufig1 position=float orientation=portrait >

biorxiv scientific-communication-and-education 200-500-users 2019

An open resource of structural variation for medical and population genetics, bioRxiv, 2019-03-15

SUMMARYStructural variants (SVs) rearrange the linear and three-dimensional organization of the genome, which can have profound consequences in evolution, diversity, and disease. As national biobanks, human disease association studies, and clinical genetic testing are increasingly reliant on whole-genome sequencing, population references for small variants (i.e., SNVs &amp; indels) in protein-coding genes, such as the Genome Aggregation Database (gnomAD), have become integral for the evaluation and interpretation of genomic variation. However, no comparable large-scale reference maps for SVs exist to date. Here, we constructed a reference atlas of SVs from deep whole-genome sequencing (WGS) of 14,891 individuals across diverse global populations (54% non-European) as a component of gnomAD. We discovered a rich landscape of 498,257 unique SVs, including 5,729 multi-breakpoint complex SVs across 13 mutational subclasses, and examples of localized chromosome shattering, like chromothripsis, in the general population. The mutation rates and densities of SVs were non-uniform across chromosomes and SV classes. We discovered strong correlations between constraint against predicted loss-of-function (pLoF) SNVs and rare SVs that both disrupt and duplicate protein-coding genes, suggesting that existing per-gene metrics of pLoF SNV constraint do not simply reflect haploinsufficiency, but appear to capture a gene’s general sensitivity to dosage alterations. The average genome in gnomAD-SV harbored 8,202 SVs, and approximately eight genes altered by rare SVs. When incorporating these data with pLoF SNVs, we estimate that SVs comprise at least 25% of all rare pLoF events per genome. We observed large (≥1Mb), rare SVs in 3.1% of genomes (∼132 individuals), and a clinically reportable pathogenic incidental finding from SVs in 0.24% of genomes (∼1417 individuals). We also estimated the prevalence of previously reported pathogenic recurrent CNVs associated with genomic disorders, which highlighted differences in frequencies across populations and confirmed that WGS-based analyses can readily recapitulate these clinically important variants. In total, gnomAD-SV includes at least one CNV covering 57% of the genome, while the remaining 43% is significantly enriched for CNVs found in tumors and individuals with developmental disorders. However, current sample sizes remain markedly underpowered to establish estimates of SV constraint on the level of individual genes or noncoding loci. The gnomAD-SV resources have been integrated into the gnomAD browser (<jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpsgnomad.broadinstitute.org>httpsgnomad.broadinstitute.org<jatsext-link>), where users can freely explore this dataset without restrictions on reuse, which will have broad utility in population genetics, disease association, and diagnostic screening.

biorxiv genomics 200-500-users 2019

The “sewing machine” for minimally invasive neural recording, bioRxiv, 2019-03-15

AbstractWe present a system for scalable and customizable recording and stimulation of neural activity. In large animals and humans, the current benchmark for high spatial and temporal resolution neural interfaces are fixed arrays of wire or silicon electrodes inserted into the parenchyma of the brain. However, probes that are large and stiff enough to penetrate the brain have been shown to cause acute and chronic damage and inflammation, which limits their longevity, stability, and yield. One approach to this problem is to separate the requirements of the insertion device, which should to be as stiff as possible, with the implanted device, which should be as small and flexible as possible. Here, we demonstrate the feasibility and scalability of this approach with a system incorporating fine and flexible thin-film polymer probes, a fine and stiff insertion needle, and a robotic insertion machine. Together the system permits rapid and precise implantation of probes, each individually targeted to avoid observable vasculature and to attain diverse anatomical targets. As an initial demonstration of this system, we implanted arrays of electrodes in rat somatosensory cortex, recorded extracellular action potentials from them, and obtained histological images of the tissue response. This approach points the way toward a new generation of scaleable, stable, and safe neural interfaces, both for the basic scientific study of brain function and for clinical applications.

biorxiv neuroscience 200-500-users 2019

 

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