High contiguity Arabidopsis thaliana genome assembly with a single nanopore flow cell, bioRxiv, 2017-06-15

AbstractWhile many evolutionary questions can be answered by short read re-sequencing, presenceabsence polymorphisms of genes andor transposons have been largely ignored in large-scale intraspecific evolutionary studies. To enable the rigorous analysis of such variants, multiple high quality and contiguous genome assemblies are essential. Similarly, while genome assemblies based on short reads have made genomics accessible for non-reference species, these assemblies have limitations due to low contiguity. Long-read sequencers and long-read technologies have ushered in a new era of genome sequencing where the lengths of reads exceed those of most repeats. However, because these technologies are not only costly, but also time and compute intensive, it has been unclear how scalable they are. Here we demonstrate a fast and cost effective reference assembly for an Arabidopsis thaliana accession using the USB-sized Oxford Nanopore MinION sequencer and typical consumer computing hardware (4 Cores, 16Gb RAM). We assemble the accession KBS-Mac-74 into 62 contigs with an N50 length of 12.3 Mb covering 100% (119 Mb) of the non-repetitive genome. We demonstrate that the polished KBS-Mac-74 assembly is highly contiguous with BioNano optical genome maps, and of high per-base quality against a likewise polished Pacific Biosciences long-read assembly. The approach we implemented took a total of four days at a cost of less than 1,000 USD for sequencing consumables including instrument depreciation.

biorxiv genomics 200-500-users 2017

Beyond Consensus Embracing Heterogeneity in Curated Neuroimaging Meta-Analysis, bioRxiv, 2017-06-14

Coordinate-based meta-analysis can provide important insights into mind-brain relationships. A popular approach for curated small-scale meta-analysis is activation likelihood estimation (ALE), which identifies brain regions consistently activated across a selected set of experiments, such as within a functional domain or mental disorder. ALE can also be utilized in meta-analytic co-activation modeling (MACM) to identify brain regions consistently co-activated with a seed region. Therefore, ALE aims to find consensus across experiments, treating heterogeneity across experiments as noise. However, heterogeneity within an ALE analysis of a functional domain might indicate the presence of functional sub-domains. Similarly, heterogeneity within a MACM analysis might indicate the involvement of a seed region in multiple co-activation patterns that are dependent on task contexts. Here, we demonstrate the use of the author-topic model to automatically determine if heterogeneities within ALE-type meta-analyses can be robustly explained by a small number of latent patterns. In the first application, the author-topic modeling of experiments involving self-generated thought (N = 179) revealed cognitive components fractionating the default network. In the second application, the author-topic model revealed that the left inferior frontal junction (IFJ) participated in multiple task-dependent co-activation patterns (N = 323). Furthermore, the author-topic model estimates compared favorably with spatial independent component analysis in both simulation and real data. Overall, the results suggest that the author-topic model is a flexible tool for exploring heterogeneity in ALE-type meta-analyses that might arise from functional sub-domains, mental disorder subtypes or task-dependent co-activation patterns. Code for this study is publicly available (httpsgithub.comThomasYeoLabCBIGtreemasterstable_projectsmeta-analysisNgo2019_AuthorTopic).

biorxiv neuroscience 0-100-users 2017

 

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