Scalable detection of technically challenging variants through modified next-generation sequencing.

Background: Some clinically important genetic variants are not easily evaluated with next-generation sequencing (NGS) methods due to technical challenges arising from high- similarity copies (e.g., PMS2, SMN1/SMN2, GBA1, HBA1/HBA2, CYP21A2), repetitive short sequences (e.

Thermostable group II intron reverse transcriptase fusion proteins and their use in cDNA synthesis and next-generation RNA sequencing.

Mobile group II introns encode reverse transcriptases (RTs) that function in intron mobility ("retrohoming") by a process that requires reverse transcription of a highly structured, 2-2.5-kb intron RNA with high processivity and fidelity. Although the latter properties are potentially useful for applications in cDNA synthesis and next-generation RNA sequencing (RNA-seq), group II intron RTs have been difficult to purify free of the intron RNA, and their utility as research tools has not been investigated systematically.

Whole-genome haplotyping by dilution, amplification, and sequencing.

Standard whole-genome genotyping technologies are unable to determine haplotypes. Here we describe a method for rapid and cost-effective long-range haplotyping. Genomic DNA is diluted and distributed into multiple aliquots such that each aliquot receives a fraction of a haploid copy.

Strelka: accurate somatic small-variant calling from sequenced tumor-normal sample pairs.

Motivation: Whole genome and exome sequencing of matched tumor-normal sample pairs is becoming routine in cancer research. The consequent increased demand for somatic variant analysis of paired samples requires methods specialized to model this problem so as to sensitively call variants at any practical level of tumor impurity.

Results: We describe Strelka, a method for somatic SNV and small indel detection from sequencing data of matched tumor-normal samples.

Signatures of mutation and selection in the cancer genome.

The cancer genome is moulded by the dual processes of somatic mutation and selection. Homozygous deletions in cancer genomes occur over recessive cancer genes, where they can confer selective growth advantage, and over fragile sites, where they are thought to reflect an increased local rate of DNA breakage. However, most homozygous deletions in cancer genomes are unexplained.

PICNIC: an algorithm to predict absolute allelic copy number variation with microarray cancer data.

High-throughput oligonucleotide microarrays are commonly employed to investigate genetic disease, including cancer. The algorithms employed to extract genotypes and copy number variation function optimally for diploid genomes usually associated with inherited disease. However, cancer genomes are aneuploid in nature leading to systematic errors when using these techniques.

Neurotransmitters drive combinatorial multistate postsynaptic density networks.

The mammalian postsynaptic density (PSD) comprises a complex collection of approximately 1100 proteins. Despite extensive knowledge of individual proteins, the overall organization of the PSD is poorly understood. Here, we define maps of molecular circuitry within the PSD based on phosphorylation of postsynaptic proteins.

Comparison of Mascot and X!Tandem performance for low and high accuracy mass spectrometry and the development of an adjusted Mascot threshold.

It is a major challenge to develop effective sequence database search algorithms to translate molecular weight and fragment mass information obtained from tandem mass spectrometry into high quality peptide and protein assignments. We investigated the peptide identification performance of Mascot and X!Tandem for mass tolerance settings common for low and high accuracy mass spectrometry. We demonstrated that sensitivity and specificity of peptide identification can vary substantially for different mass tolerance settings, but this effect was more significant for Mascot.