Biology subjects

Daniel Lawson

Publications and source records attributed to Daniel Lawson.

3 recordsLinked to original sources

bioRxiv2016

A tutorial on how (not) to over-interpret STRUCTURE/ADMIXTURE bar plots

Genetic clustering algorithms, implemented in popular programs such as STRUCTURE and ADMIXTURE, have been used extensively in the characterisation of individuals and populations based on genetic data. A successful example is the reconstruction of the genetic history of African Americans who are a product of recent admixture between highly differentiated populations. Histories can also be reconstructed using the same procedure for groups which do not have admixture in their recent history, where recent genetic drift is strong or that deviate in other ways from the underlying inference model. Unfortunately, such histories can be misleading. We have implemented an approach (badMIXTURE, available at github.com/danjlawson/badMIXTURE) to assess the goodness of fit of the model using the ancestry \"palettes\" estimated by CHROMOPAINTER and apply it to both simulated data and real case studies. Combining these complementary analyses with additional methods that are designed to test specific hypotheses allows a richer and more robust analysis of recent demographic history based on genetic data.

Genetics↗

bioRxiv2016

RADpainter and fineRADstructure: population inference from RADseq data

Powerful approaches to inferring recent or current population structure based on nearest neighbour haplotype coancestry have so far been inaccessible to users without high quality genome-wide haplotype data. With a boom in non-model organism genomics, there is a pressing need to bring these methods to communities without access to such data. Here we present RADpainter, a new program designed to infer the coancestry matrix from restriction-site-associated DNA sequencing (RADseq) data. We combine this program together with a previously published MCMC clustering algorithm into fineRADstructure - a complete, easy to use, and fast population inference package for RADseq data (https://github.com/millanek/fineRADstructure). Finally, with two example datasets, we illustrate its use, benefits, and robustness to missing RAD alleles in double digest RAD sequencing.

Evolutionary Biology↗

bioRxiv2014

RNA-Rocket: An RNA-Seq Analysis Resource for Infectious Disease Research

MotivationRNA-Seq is a method for profiling transcription using high-throughput sequencing and is an important component of many research projects that wish to study transcript isoforms, condition specific expression, and transcriptional structure. The methods, tools, and technologies employed to perform RNA-Seq analysis continue to change, creating a bioinformatics challenge for researchers who wish to exploit these data. Resources that bring together genomic data, analysis tools, educational material, and computational infrastructure can minimize the overhead required of life science researchers.\n\nResultsRNA-Rocket is a free service that provides access to RNA-Seq and ChIP-Seq analysis tools for studying infectious diseases. The site makes available thousands of pre-indexed genomes, their annotations, and the ability to stream results to the bioinformatics resources VectorBase, EuPathDB, and PATRIC. The site also provides a combination of experimental data and metadata, examples of pre-computed analysis, step-by-step guides, and a user interface designed to enable both novice and experienced users of RNA-Seq data.\n\nAvailability: RNA-Rocket can be found at rnaseq.pathogenportal.org Source code for this project can be found at github.com/cidvbi/PathogenPortal

Bioinformatics↗