PublisherDOIYearVolumeIssuePageTitleAuthor(s)Link
Genomics & Informatics10.5808/gi.2017.15.1.11201715111A ChIP-Seq Data Analysis Pipeline Based on Bioconductor PackagesSeung-Jin Park, Jong-Hwan Kim, Byung-Ha Yoon, Seon-Young Kimhttps://synapse.koreamed.org/pdf/10.5808/GI.2017.15.1.11, https://synapse.koreamed.org/DOIx.php?id=10.5808/GI.2017.15.1.11, https://synapse.koreamed.org/DOIx.php?id=10.5808/GI.2017.15.1.11
Methods in Molecular Biology10.1007/978-1-4939-7380-4_172017195-226Analysis of ChIP-seq Data in R/BioconductorInes de Santiago, Thomas Carrollhttp://link.springer.com/content/pdf/10.1007/978-1-4939-7380-4_17
Nucleic Acids Research10.1093/nar/gkv11912015445e45-e45csaw: a Bioconductor package for differential binding analysis of ChIP-seq data using sliding windowsAaron T.L. Lun, Gordon K. Smythhttp://academic.oup.com/nar/article-pdf/44/5/e45/33377168/gkv1191.pdf, http://academic.oup.com/nar/article-pdf/44/5/e45/33377168/gkv1191.pdf
Bioinformatics and Biology Insights10.4137/bbi.s3088420159BBI.S30884A Computational Pipeline for Cross-Species Analysis of RNA-seq Data Using R and BioconductorPeter R. LoVerso, Feng Cuihttp://journals.sagepub.com/doi/pdf/10.4137/BBI.S30884, http://journals.sagepub.com/doi/full-xml/10.4137/BBI.S30884, http://journals.sagepub.com/doi/pdf/10.4137/BBI.S30884
F1000Research10.12688/f1000research.7016.1201541080From reads to regions: a Bioconductor workflow to detect differential binding in ChIP-seq dataAaron T. L. Lun, Gordon K. Smythhttps://f1000research.com/articles/4-1080/v1/xml, https://f1000research.com/articles/4-1080/v1/pdf, https://f1000research.com/articles/4-1080/v1/iparadigms
F1000Research10.12688/f1000research.7016.2201641080From reads to regions: a Bioconductor workflow to detect differential binding in ChIP-seq dataAaron T. L. Lun, Gordon K. Smythhttps://f1000research.com/articles/4-1080/v2/xml, https://f1000research.com/articles/4-1080/v2/pdf, https://f1000research.com/articles/4-1080/v2/iparadigms
BMC Bioinformatics10.1186/1471-2105-11-2372010111ChIPpeakAnno: a Bioconductor package to annotate ChIP-seq and ChIP-chip dataLihua J Zhu, Claude Gazin, Nathan D Lawson, Hervé Pagès, Simon M Lin, David S Lapointe, Michael R Greenhttp://link.springer.com/content/pdf/10.1186/1471-2105-11-237.pdf, http://link.springer.com/article/10.1186/1471-2105-11-237/fulltext.html, http://link.springer.com/content/pdf/10.1186/1471-2105-11-237.pdf
Genes & Genomics10.1007/s13258-014-0260-32014373305-311An automated analysis pipeline for a large set of ChIP-seq data: AutoChIPTaemook Kim, Wooseok Lee, Kyudong Han, Keunsoo Kanghttp://link.springer.com/content/pdf/10.1007/s13258-014-0260-3.pdf, http://link.springer.com/article/10.1007/s13258-014-0260-3/fulltext.html, http://link.springer.com/content/pdf/10.1007/s13258-014-0260-3
Computational Epigenetics and Diseases10.1016/b978-0-12-814513-5.00005-2201967-77Data Analysis of ChIP-Seq ExperimentsQi Zhanghttps://api.elsevier.com/content/article/PII:B9780128145135000052?httpAccept=text/xml, https://api.elsevier.com/content/article/PII:B9780128145135000052?httpAccept=text/plain
F1000Research10.12688/f1000research.8964.1201651309RiboProfiling: a Bioconductor package for standard Ribo-seq pipeline processingAlexandra Popa, Kevin Lebrigand, Agnes Paquet, Nicolas Nottet, Karine Robbe-Sermesant, Rainer Waldmann, Pascal Barbryhttps://f1000research.com/articles/5-1309/v1/xml, https://f1000research.com/articles/5-1309/v1/pdf, https://f1000research.com/articles/5-1309/v1/iparadigms