ChIP-chip versus ChIP-seq: Lessons for experimental design and data analysis, BMC Genomics, vol.57, issue.1, p.134, 2011. ,
DOI : 10.1093/bioinformatics/btp472
FindPeaks 3.1: a tool for identifying areas of enrichment from massively parallel short-read sequencing technology, Bioinformatics, vol.24, issue.15, pp.1729-1730, 2008. ,
DOI : 10.1093/bioinformatics/btn305
Genome-Wide Mapping of in Vivo Protein-DNA Interactions, Science, vol.316, issue.5830, pp.1497-1502, 2007. ,
DOI : 10.1126/science.1141319
Using CisGenome to Analyze ChIP-chip and ChIP-seq Data, Curr Protoc Bioinformatics, vol.15, 2011. ,
DOI : 10.1002/0471250953.bi0213s33
PeakSeq enables systematic scoring of ChIP-seq experiments relative to controls, Nature Biotechnology, vol.6, issue.1, pp.66-75, 2009. ,
DOI : 10.1038/nbt.1518
Activity of fulvestrant in HER2-overexpressing advanced breast cancer, Annals of Oncology, vol.21, issue.6, pp.1246-1253, 2010. ,
DOI : 10.1093/annonc/mdp447
Model-based Analysis of ChIP-Seq (MACS), Genome Biology, vol.9, issue.9, p.137, 2008. ,
DOI : 10.1186/gb-2008-9-9-r137
A fully Bayesian hidden Ising model for ChIP-seq data analysis, Biostatistics, vol.13, issue.1, pp.113-128, 2012. ,
DOI : 10.1093/biostatistics/kxr029
HPeak: an HMM-based algorithm for defining read-enriched regions in ChIP-Seq data, BMC Bioinformatics, vol.11, issue.1, p.369, 2010. ,
DOI : 10.1186/1471-2105-11-369
BayesPeak: Bayesian analysis of ChIP-seq data, BMC Bioinformatics, vol.10, issue.1, p.299, 2009. ,
DOI : 10.1186/1471-2105-10-299
PICS: Probabilistic Inference for ChIP-seq, Biometrics, vol.9, issue.1, pp.151-163, 2011. ,
DOI : 10.1111/j.1541-0420.2010.01441.x
PeakRanger: A cloud-enabled peak caller for ChIP-seq data, BMC Bioinformatics, vol.12, issue.1, p.139, 2011. ,
DOI : 10.1126/science.1196914
Shape-based peak identification for ChIP-Seq, BMC Bioinformatics, vol.12, issue.1, p.15, 2011. ,
DOI : 10.1186/1471-2105-12-15
The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding, BMC Bioinformatics, vol.13, issue.1, p.176, 2012. ,
DOI : 10.1101/gr.849004
Model-based deconvolution of genome-wide DNA binding, Bioinformatics, vol.24, issue.3, pp.396-403, 2008. ,
DOI : 10.1093/bioinformatics/btm592
POLYPHEMUS: R package for comparative analysis of RNA polymerase II ChIP-seq profiles by non-linear normalization, Nucleic Acids Research, vol.40, issue.4, p.30, 2012. ,
DOI : 10.1093/nar/gkr1205
A manually curated ChIP-seq benchmark demonstrates room for improvement in current peak-finder programs, Nucleic Acids Research, vol.39, issue.4, p.25, 2011. ,
DOI : 10.1093/nar/gkq1187
Mapping and analysis of chromatin state dynamics in nine human cell types, Nature, vol.125, issue.7345, pp.43-49, 2011. ,
DOI : 10.1038/nature09906
Methylation specifies distinct estrogen-induced binding site repertoires of CBP to chromatin, Genes & Development, vol.25, issue.11, pp.1132-1146, 2011. ,
DOI : 10.1101/gad.619211
Measuring reproducibility of highthroughput experiments. The annals of applied statistics, p.1752, 2011. ,
ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia, Genome Research, vol.22, issue.9, pp.1813-1831, 2012. ,
DOI : 10.1101/gr.136184.111
Design and analysis of ChIP-seq experiments for DNA-binding proteins, Nature Biotechnology, vol.26, issue.12, pp.1351-1359, 2008. ,
DOI : 10.1016/S0167-9473(99)00100-0
ChIP???seq: advantages and challenges of a maturing technology, Nature Reviews Genetics, vol.453, issue.10, pp.669-680, 2009. ,
DOI : 10.1038/nrg2641
Dissecting the retinoid-induced differentiation of F9 embryonal stem cells by integrative genomics, Molecular Systems Biology, vol.34, issue.1, p.538, 2011. ,
DOI : 10.1186/gb-2008-9-9-r137
A clustering approach for identification of enriched domains from histone modification ChIP-Seq data, Bioinformatics, vol.25, issue.15, pp.1952-1958, 2009. ,
DOI : 10.1093/bioinformatics/btp340
Identifying dispersed epigenomic domains from ChIP-Seq data, Bioinformatics, vol.27, issue.6, pp.870-871, 2011. ,
DOI : 10.1093/bioinformatics/btr030
BroadPeak: a novel algorithm for identifying broad peaks in diffuse ChIP-seq datasets, Bioinformatics, vol.29, issue.4, pp.492-493, 2013. ,
DOI : 10.1093/bioinformatics/bts722
Characterising ChIP-seq binding patterns by model-based peak shape deconvolution, BMC Genomics, vol.14, issue.1, p.834, 2013. ,
DOI : 10.1093/bioinformatics/bts722
URL : https://hal.archives-ouvertes.fr/inserm-00913448