What exactly is ‘N’ in cell culture and animal experiments?, bioRxiv, 2017-09-03

AbstractBiologists establish the existence of experimental effects by applying treatments or interventions to biological entities or units, such as people, animals, slice preparations, or cells. When done appropriately, independent replication of the entity-intervention pair contributes to the sample size (N) and forms the basis of statistical inference. However, sometimes the appropriate entity-intervention pair may not be obvious, and the wrong choice can make an experiment worthless. We surveyed a random sample of published animal experiments from 2011 to 2016 where interventions were applied to parents but effects examined in the offspring, as regulatory authorities have provided clear guidelines on replication with such designs. We found that only 22% of studies (95% CI = 17% to 29%) replicated the correct entity-intervention pair and thus made valid statistical inferences. Approximately half of the studies (46%, 95% CI = 38% to 53%) had pseudoreplication while 32% (95% CI = 26% to 39%) provided insufficient information to make a judgement. Pseudoreplication artificially inflates the sample size, leading to more false positive results and inflating the apparent evidence supporting a scientific claim. It is hard for science to advance when so many experiments are poorly designed and analysed. We argue that distinguishing between biological units, experimental units, and observational units clarifies where replication should occur, describe the criteria for genuine replication, and provide guidelines for designing and analysing in vitro, ex vivo, and in vivo experiments.

biorxiv neuroscience 100-200-users 2017

Inter-homologue repair in fertilized human eggs?, bioRxiv, 2017-08-29

Many human diseases have an underlying genetic component. The development and application of methods to prevent the inheritance of damaging mutations through the human germline could have significant health benefits, and currently include preimplantation genetic diagnosis and carrier screening. Ma et al. take this a step further by attempting to remove a disease mutation from the human germline through gene editing1. They assert the following advances (i) the correction of a pathogenic gene mutation responsible for hypertrophic cardiomyopathy in human embryos using CRISPR-Cas9 and (ii) the avoidance of mosaicism in edited embryos. In the case of correction, the authors conclude that repair using the homologous chromosome was as or more frequent than mutagenic nonhomologous end-joining (NHEJ). Their conclusion is significant, if validated, because such a “self-repair” mechanism would allow gene correction without the introduction of a repair template. While the authors’ analyses relied on the failure to detect mutant alleles, here we suggest approaches to provide direct evidence for inter-homologue recombination and discuss other events consistent with the data. We also review the biological constraints on inter-homologue recombination in the early embryo.

biorxiv cell-biology 100-200-users 2017

An improved ATAC-seq protocol reduces background and enables interrogation of frozen tissues, bioRxiv, 2017-08-27

ABSTRACTWe present Omni-ATAC, an improved ATAC-seq protocol for chromatin accessibility profiling that works across multiple applications with substantial improvement of signal-to-background ratio and information content. The Omni-ATAC protocol enables chromatin accessibility profiling from archival frozen tissue samples and 50 μm sections, revealing the activities of disease-associated DNA elements in distinct human brain structures. The Omni-ATAC protocol enables the interrogation of personal regulomes in tissue context and translational studies.

biorxiv genomics 100-200-users 2017

Rapid profiling of the preterm infant gut microbiota using nanopore sequencing aids pathogen diagnostics, bioRxiv, 2017-08-25

ABSTRACTThe Oxford Nanopore MinION sequencing platform offers near real time analysis of DNA reads as they are generated, which makes the device attractive for in-field or clinical deployment, e.g. rapid diagnostics. We used the MinION platform for shotgun metagenomic sequencing and analysis of gut-associated microbial communities; firstly, we used a 20-species human microbiota mock community to demonstrate how Nanopore metagenomic sequence data can be reliably and rapidly classified. Secondly, we profiled faecal microbiomes from preterm infants at increased risk of necrotising enterocolitis and sepsis. In single patient time course, we captured the diversity of the immature gut microbiota and observed how its complexity changes over time in response to interventions, i.e. probiotic, antibiotics and episodes of suspected sepsis. Finally, we performed ‘real-time’ runs from sample to analysis using faecal samples of critically ill infants and of healthy infants receiving probiotic supplementation. Real-time analysis was facilitated by our new NanoOK RT software package which analysed sequences as they were generated. We reliably identified potentially pathogenic taxa (i.e. Klebsiella pneumoniae and Enterobacter cloacae) and their corresponding antimicrobial resistance (AMR) gene profiles within as little as one hour of sequencing. Antibiotic treatment decisions may be rapidly modified in response to these AMR profiles, which we validated using pathogen isolation, whole genome sequencing and antibiotic susceptibility testing. Our results demonstrate that our pipeline can process clinical samples to a rich dataset able to inform tailored patient antimicrobial treatment in less than 5 hours.

biorxiv genomics 100-200-users 2017

Chiron Translating nanopore raw signal directly into nucleotide sequence using deep learning, bioRxiv, 2017-08-24

ABSTRACTSequencing by translocating DNA fragments through an array of nanopores is a rapidly maturing technology which offers faster and cheaper sequencing than other approaches. However, accurately deciphering the DNA sequence from the noisy and complex electrical signal is challenging. Here, we report Chiron, the first deep learning model to achieve end-to-end basecalling directly translating the raw signal to DNA sequence without the error-prone segmentation step. Trained with only a small set of 4000 reads, we show that our model provides state-of-the-art basecalling accuracy even on previously unseen species. Chiron achieves basecalling speeds of over 2000 bases per second using desktop computer graphics processing units.

biorxiv bioinformatics 100-200-users 2017

An atlas of genetic associations in UK Biobank, bioRxiv, 2017-08-17

ABSTRACTGenome-wide association studies have revealed many loci contributing to the variation of complex traits, yet the majority of loci that contribute to the heritability of complex traits remain elusive. Large study populations with sufficient statistical power are required to detect the small effect sizes of the yet unidentified genetic variants. However, the analysis of huge cohorts, like UK Biobank, is complicated by incidental structure present when collecting such large cohorts. For instance, UK Biobank comprises 107,162 third degree or closer related participants. Traditionally, GWAS have removed related individuals because they comprised an insignificant proportion of the overall sample size, however, removing related individuals in UK Biobank would entail a substantial loss of power. Furthermore, modelling such structure using linear mixed models is computationally expensive, which requires a computational infrastructure that may not be accessible to all researchers. Here we present an atlas of genetic associations for 118 non-binary and 599 binary traits of 408,455 related and unrelated UK Biobank participants of White-British descent. Results are compiled in a publicly accessible database that allows querying genome-wide association summary results for 623,944 genotyped and HapMap2 imputed SNPs, as well downloading whole GWAS summary statistics for over 30 million imputed SNPs from the Haplotype Reference Consortium panel. Our atlas of associations (GeneATLAS, <jatsext-link xmlnsxlink=httpwww.w3.org1999xlink ext-link-type=uri xlinkhref=httpgeneatlas.roslin.ed.ac.uk>httpgeneatlas.roslin.ed.ac.uk<jatsext-link>) will help researchers to query UK Biobank results in an easy way without the need to incur in high computational costs.

biorxiv genomics 100-200-users 2017