ScholarGate
Asistente

Comparar métodos

Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.

Llamada de picos de ChIP-seq bayesiano×Llamada de variantes×
CampoBioinformáticaBioinformática
FamiliaProcess / pipelineProcess / pipeline
Año de origen2008–20092009–2010 (modern high-throughput era)
Autor originalSpyrou et al. (BayesPeak, 2009); broader Bayesian ChIP-seq framework developed across multiple groups ~2008–2012Li et al. (SAMtools/bcftools, 2009); McKenna et al. (GATK, 2010)
TipoProbabilistic signal detection pipelineComputational genomics pipeline
Fuente seminalZhang, Y., Liu, T., Meyer, C. A., Eeckhoute, J., Johnson, D. S., Bernstein, B. E., Nusbaum, C., Myers, R. M., Brown, M., Li, W., & Liu, X. S. (2008). Model-based analysis of ChIP-Seq (MACS). Genome Biology, 9(9), R137. DOI ↗McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., ... & DePristo, M. A. (2010). The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), 1297–1303. DOI ↗
AliasBayesian ChIP-seq analysis, probabilistic peak detection, Bayesian peak caller, ChIP-seq Bayesian enrichment callingSNP calling, genotyping from sequencing, mutation detection, variant detection
Relacionados66
ResumenBayesian ChIP-seq peak calling applies probabilistic models — typically Poisson, negative binomial, or hidden Markov models with Bayesian inference — to detect genomic regions enriched for a protein of interest in chromatin immunoprecipitation followed by sequencing experiments. By explicitly modelling read-count noise and incorporating prior distributions, Bayesian callers yield posterior probabilities of enrichment rather than simple p-values, providing a principled framework for uncertainty quantification across the genome.Variant calling is the computational process of identifying positions in a sequenced genome that differ from a reference sequence — including single nucleotide polymorphisms (SNPs), small insertions and deletions (indels), and structural variants. It transforms aligned sequencing reads into an interpretable catalogue of genetic differences, forming the foundation for population genetics, disease-gene discovery, and clinical genomics applications.
ScholarGateConjunto de datos
  1. v1
  2. 2 Fuentes
  3. PUBLISHED
  1. v1
  2. 2 Fuentes
  3. PUBLISHED

Ir a la búsqueda Descargar diapositivas

ScholarGateComparar métodos: Bayesian ChIP-seq peak calling · Variant Calling. Recuperado el 2026-06-15 de https://scholargate.app/es/compare