Biology subjects

Michael C Schatz

Publications and source records attributed to Michael C Schatz.

4 recordsLinked to original sources

bioRxiv2016

Assemblytics: a web analytics tool for the detection of assembly-based variants

SummaryAssemblytics is a web app for detecting and analyzing structural variants from a de novo genome assembly aligned to a reference genome. It incorporates a unique anchor filtering approach to increase robustness to repetitive elements, and identifies six classes of variants based on their distinct alignment signatures. Assemblytics can be applied both to comparing aberrant genomes, such as human cancers, to a reference, or to identify differences between related species. Multiple interactive visualizations enable in-depth explorations of the genomic distributions of variants.\n\nAvailability and Implementationhttp://qb.cshl.edu/assemblytics, https://github.com/marianattestad/assemblytics\n\nContact: mnattest@cshl.edu\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

Genomics↗

bioRxiv2015

Teaser: Individualized benchmarking and optimization of read mapping results for NGS data

Mapping reads to a genome remains challenging, especially for non-model organisms with poorer quality assemblies, or for organisms with higher rates of mutations. While most research has focused on speeding up the mapping process, little attention has been paid to optimize the choice of mapper and parameters for a users dataset. Here we present Teaser, which assists in these choices through rapid automated benchmarking of different mappers and parameter settings for individualized data. Within minutes, Teaser completes a quantitative evaluation of an ensemble of mapping algorithms and parameters. Using Teaser, we demonstrate how Bowtie2 can be optimized for different data.

Bioinformatics↗

bioRxiv2014

New whole genome de novo assemblies of three divergent strains of rice (O. sativa) documents novel gene space of aus and indica

The use of high throughput genome-sequencing technologies has uncovered a large extent of structural variation in eukaryotic genomes that makes important contributions to genomic diversity and phenotypic variation. Currently, when the genomes of different strains of a given organism are compared, whole genome resequencing data are aligned to an established reference sequence. However when the reference differs in significant structural ways from the individuals under study, the analysis is often incomplete or inaccurate. Here, we use rice as a model to explore the extent of structural variation among strains adapted to different ecologies and geographies, and show that this variation can be significant, often matching or exceeding the variation present in closely related human populations or other mammals. We demonstrate how improvements in sequencing and assembly technology allow rapid and inexpensive de novo assembly of next generation sequence data into high-quality assemblies that can be directly compared to provide an unbiased assessment. Using this approach, we are able to accurately assess the \"pan-genome\" of three divergent rice varieties and document several megabases of each genome absent in the other two. Many of the genome-specific loci are annotated to contain genes, reflecting the potential for new biological properties that would be missed by standard resequencing approaches. We further provide a detailed analysis of several loci associated with agriculturally important traits, illustrating the utility of our approach for biological discovery. All of the data and software are openly available to support further breeding and functional studies of rice and other species.

Genomics↗

bioRxiv2013

Accurate detection of de novo and transmitted INDELs within exome-capture data using micro-assembly

We present a new open-source algorithm, Scalpel, for sensitive and specific discovery of INDELs in exome-capture data. By combining the power of mapping and assembly, Scalpel searches the de Bruijn graph for sequence paths (contigs) that span each exon. The algorithm creates a single path for exons with no INDEL, two paths for an exon with a heterozygous mutation, and multiple paths for more exotic variations. A detailed repeat composition analysis coupled with a self-tuning k-mer strategy allows Scalpel to outperform other state-of-the-art approaches for INDEL discovery. We extensively compared Scalpel with a battery of >10000 simulated and >1000 experimentally validated INDELs between 1 and 100bp against two recent algorithms for INDEL discovery: GATK HaplotypeCaller and SOAPindel. We report anomalies for these tools in their ability to detect INDELs, especially in regions containing near-perfect repeats which contribute to high false positive rates. In contrast, Scalpel demonstrates superior specificity while maintaining high sensitivity. We also present a large-scale application of Scalpel for detecting de novo and transmitted INDELs in 593 families with autistic children from the Simons Simplex Collection. Scalpel demonstrates enhanced power to detect long ([≥]20bp) transmitted events, and strengthens previous reports of enrichment for de novo likely gene-disrupting INDEL mutations in children with autism with many new candidate genes. The source code and documentation for the algorithm is available at http://scalpel.sourceforge.net.

Bioinformatics↗