SAMBAM format v1.5 extensions for de novo assemblies, bioRxiv, 2015-05-30
Summary The plain text Sequence AlignmentMap (SAM) file format and its companion binary form (BAM) are a generic alignment format for storing read alignments against reference sequences (and unmapped reads) together with structured meta-data (Li et al., 2009). Driven by the needs of the 1000 Genomes Project which sequenced many individual human genomes, early SAMBAM usage focused on pairwise alignments of reads to a reference. However, through the CIGAR P operator multiple sequence alignments can also be preserved. Herein we describe clarifications and additions in version 1.5 of the specification to facilitate storing de novo sequence alignments Padded reference sequences (with gap characters), annotation of reads or regions of the reference, and the option of embedding the reference sequence within the file. Availability The latest public release of the specification is at httpsamtools.sourceforge.netSAM1.pdf, with in development drafts at httpsgithub.comsamtoolshts-specs under version control.
biorxiv bioinformatics 0-100-users 2015Detection and interpretation of shared genetic influences on 40 human traits, bioRxiv, 2015-05-28
We performed a genome-wide scan for genetic variants that influence multiple human phenotypes by comparing large genome-wide association studies (GWAS) of 40 traits or diseases, including anthropometric traits (e.g. nose size and male pattern baldness), immune traits (e.g. susceptibility to childhood ear infections and Crohn's disease), metabolic phenotypes (e.g. type 2 diabetes and lipid levels), and psychiatric diseases (e.g. schizophrenia and Parkinson's disease). First, we identified 307 loci (at a false discovery rate of 10%) that influence multiple traits (excluding “trivial” phenotype pairs like type 2 diabetes and fasting glucose). Several loci influence a large number of phenotypes; for example, variants near the blood group gene ABO influence eleven of these traits, including risk of childhood ear infections (rs635634 log-odds ratio = 0.06, P = 1.4 × 10−8) and allergies (log-odds ratio = 0.05, P = 2.5 × 10−8), among others. Similarly, a nonsynonymous variant in the zinc transporter SLC39A8 influences seven of these traits, including risk of schizophrenia (rs13107325 log-odds ratio = 0.15, P = 2 × 10−12) and Parkinson’s disease (log-odds ratio = -0.15, P = 1.6 × 10−7), among others. Second, we used these loci to identify traits that share multiple genetic causes in common. For example, genetic variants that delay age of menarche in women also, on average, delay age of voice drop in men, decrease body mass index (BMI), increase adult height, and decrease risk of male pattern baldness. Finally, we identified four pairs of traits that show evidence of a causal relationship. For example, we show evidence that increased BMI causally increases triglyceride levels, and that increased liability to hypothyroidism causally decreases adult height.
biorxiv genomics 0-100-users 2015Streaming algorithms for identification of pathogens and antibiotic resistance potential from real-time MinIONTM sequencing, bioRxiv, 2015-05-16
AbstractThe recently introduced Oxford Nanopore MinION platform generates DNA sequence data in real-time. This opens immense potential to shorten the sample-to-results time and is likely to lead to enormous benefits in rapid diagnosis of bacterial infection and identification of drug resistance. However, there are very few tools available for streaming analysis of real-time sequencing data. Here, we present a framework for streaming analysis of MinION real-time sequence data, together with probabilistic streaming algorithms for species typing, multi-locus strain typing, gene presence strain-typing and antibiotic resistance profile identification. Using three culture isolate samples as well as a mixed-species sample, we demonstrate that bacterial species and strain information can be obtained within 30 minutes of sequencing and using about 500 reads, initial drug-resistance profiles within two hours, and complete resistance profiles within 10 hours. Multi-locus strain typing required more than 15x coverage to generate confident assignments, whereas gene-presence typing could detect the presence of a known strain with 0.5x coverage. We also show that our pipeline can process over 100 times more data than the current throughput of the MinION on a desktop computer.
biorxiv bioinformatics 100-200-users 2015Sequencing ultra-long DNA molecules with the Oxford Nanopore MinION, bioRxiv, 2015-05-14
Oxford Nanopore Technologies' nanopore sequencing device, the MinION, holds the promise of sequencing ultra-long DNA fragments >100kb. An obstacle to realizing this promise is delivering ultra-long DNA molecules to the nanopores. We present our progress in developing cost-effective ways to overcome this obstacle and our resulting MinION data, including multiple reads >100kb.
biorxiv genomics 0-100-users 2015A Chronological Atlas of Natural Selection in the Human Genome during the Past Half-million Years, bioRxiv, 2015-05-06
The spatiotemporal distribution of recent human adaptation is a long standing question. We developed a new coalescent-based method that collectively assigned human genome regions to modes of neutrality or to positive, negative, or balancing selection. Most importantly, the selection times were estimated for all positive selection signals, which ranged over the last half million years, penetrating the emergence of anatomically modern human (AMH). These selection time estimates were further supported by analyses of the genome sequences from three ancient AMHs and the Neanderthals. A series of brain function-related genes were found to carry signals of ancient selective sweeps, which may have defined the evolution of cognitive abilities either before Neanderthal divergence or during the emergence of AMH. Particularly, signals of brain evolution in AMH are strongly related to Alzheimer's disease pathways. In conclusion, this study reports a chronological atlas of natural selection in Human.
biorxiv evolutionary-biology 100-200-users 2015