SNP Detection

RNA editing is a co-transcriptional modification that increases the molecular diversity, alters secondary structure and protein coding sequences by changing the sequence of transcripts. The most common RNA editing modification is the single base substitution (A→I) that is catalyzed by ...

Single-cell sequencing is useful for illustrating the cellular heterogeneities inherent in many intricate biological systems, particularly in human cancer. However, owing to the difficulties in acquiring, amplifying and analyzing single-cell genetic material, obstacles remain for single-cell diversity assessments such as ...

SNPs (Single Nucleotide Polymorphisms) are genetic markers whose precise identification is a prerequisite for association studies. Methods to identify them are currently well developed for model species, but rely on the availability of a (good) reference genome, and therefore cannot ...

A team led by researchers at the University of Washington has developed a new statistical method-MutRSeq-for detecting differentially expressed single nucleotide variants (SNVs) based on RNA-seq data. Specifically, we focus on nonsynonymous mutations and employ a hierarchical likelihood approach to jointly ...

Accurate identification of genetic variants such as single nucleotide polymorphisms (SNPs) or RNA editing sites from RNA-Seq reads is important, yet challenging, because it necessitates a very low false positive rate in read mapping. Although many read aligners are available, ...

Ongoing advances in high-throughput technologies have facilitated accurate proteomic measurements and provide a wealth of information on genomic and transcript level. In proteogenomics, this multi-omics data is combined to analyze unannotated organisms and to allow more accurate sample-specific predictions. Existing ...

SNiPlay is a web-based tool for detection, management and analysis of genetic variants including both single nucleotide polymorphisms (SNPs) and InDels. Version 3 now extends functionalities in order to easily manage and exploit SNPs derived from next generation sequencing technologies, ...

The growing recognition of the importance of splicing in eukaryotes, together with rapidly accumulating RNA-sequencing data, demand robust high-throughput approaches, which efficiently analyze experimentally derived whole-transcriptome splice profiles. Researchers from The George Washington University have developed a computational approach, called ...

Rapid development of next generation sequencing technology has enabled the identification of genomic alterations from short sequencing reads. There are a number of software pipelines available for calling single nucleotide variants from genomic DNA but, no comprehensive pipelines to identify, ...

RNA-Seq has become the method of choice to quantify genes and exons, discover novel transcripts, and detect fusion genes. However, reliable variant identification from RNA-Seq data remains challenging due to the complexities of the transcriptome, the challenges of accurately mapping ...