Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

ShRangeSim: Simulation of Single Nucleotide Polymorphism Clusters in Next-Generation Sequencing Data.

Journal of computational biology : a journal of computational molecular cell biology - 1 Jun 2018

Boenn Markus

Abstract excerpt

Genomic variations are in the focus of research to uncover mechanisms of host-pathogen interactions and diseases such as cancer. Nowadays, next-generation sequencing (NGS) data are analyzed through dedicated pipelines to detect them. Surrogate NGS data in conjunction with genomic variations help to evaluate pipelines and validate their outcomes, fostering selection of proper tools for a given scientific question....

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Algorithms
Share to Computational Biology
Share to Computer Simulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Drosophila melanogaster

Share to High-Throughput Nucleotide Sequencing

Share to Polymorphism, Single Nucleotide

Share to Sequence Analysis, DNA

Source

Identifiers

PMID: 29658778
DOI: 10.1089/cmb.2018.0007

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

ShRangeSim: Simulation of Single Nucleotide Polymorphism Clusters in Next-Generation Sequencing Data.PMID 29658778Read ↗

Genotype and SNP calling from next-generation sequencing data.Semantic proximity Read ↗

NGSCheckMate: software for validating sample identity in next-generation sequencing studies within and across data types.Semantic proximity Read ↗

A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data.Semantic proximity Read ↗

Statistical modeling for sensitive detection of low-frequency single nucleotide variants.Semantic proximity Read ↗

CellCoal: Coalescent Simulation of Single-Cell Sequencing Samples.Semantic proximity Read ↗

Single nucleotide polymorphism arrays: a decade of biological, computational and technological advances.Semantic proximity Read ↗

NGSTroubleFinder: A tool for detection and quantification of contamination and kinship across human NGS dataSemantic proximity Read ↗

A novel simulation tool for low-coverage whole-genome sequencing using multivariate Gaussian mixture models.Semantic proximity Read ↗

Rescuing low frequency variants within intra-host viral populations directly from Oxford Nanopore sequencing dataSemantic proximity Read ↗

MultiGeMS: detection of SNVs from multiple samples using model selection on high-throughput sequencing data.Semantic proximity Read ↗

BVSim: A benchmarking variation simulator mimicking human variation spectrum.Semantic proximity Read ↗

<i>In silico</i> analyses identifies sequence contamination thresholds for Nanopore-generated SARS-CoV2 sequencesSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.