* Ross-Innes C. S., R. Stark, A. E. Teschendorff, K. A. Holmes, H. R. Ali, M. J. Dunning, G. D. Brown, O. Gojis, I. O. Ellis, A. R. Green, S. Ali, S. Chin, C. Palmieri, C. Caldas, and J. S. Carroll. 2012. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481: 389-393. doi:[10.1038/nature10730](https://dx.doi.org/10.1038/nature10730)
16.**MultiQc**:
* Ewels P., Magnusson M., Lundin S. and Käller M. 2016. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32(19): 3047–3048. doi:[10.1093/bioinformatics/btw354](https://dx.doi.org/10.1093/bioinformatics/btw354)
* Ewels P., Magnusson M., Lundin S. and Käller M. 2016. MultiQC: Summarize analysis results for multiple tools and samples in a single report. Bioinformatics 32(19): 3047–3048. doi:[10.1093/bioinformatics/btw354](https://dx.doi.org/10.1093/bioinformatics/btw354)
17.**BICF ChIP-seq Analysis Workflow**:
* Spencer D. Barnes, Holly Ruess, Beibei Chen, & Venkat S. Malladi. (2019). BICF ChIP-seq Analysis Workflow (publish_1.0.5). Zenodo. doi:[10.5281/zenodo.2648844](https://doi.org/10.5281/zenodo.2648844)
Marcel, M. 2011. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal 17(1):10-12. DOI: http://dx.doi.org/10.14806/ej.17.1.200
bwa/intel/0.7.12:
Li H., and R. Durbin. 2009. Fast and accurate short read alignment with Burrows-Wheeler Transform. Bioinformatics 25: 1754-60.
samtools/1.6:
Li H., B. Handsaker, A. Wysoker, T. Fennell, J. Ruan, N. Homer, G. Marth, G. Abecasis, R. Durbin, and 1000 Genome Project Data Processing Subgroup. 2009. The Sequence alignment/map (SAM) format and SAMtools. Bioinformatics 25: 2078-9.
sambamba/0.6.6:
Tarasov, A., A. J. Vilella, E. Cuppen, I. J. Nijman, and P. Prins. 2015 Sambamba: fast processing of NGS alignment formats. Bioinformatics 31(12): 2032-2034. doi:10.1093/bioinformatics/btv098.
bedtools/2.26.0:
Quinlan, A. R., and I. M. Hall. 2010. BEDTools: a flexible suite of utilities for comparing genomic feautures. Bioinformatics 26(6): 841-842. doi:10.1093/bioinformatics/btq033
deeptools/2.5.0.1:
Ramírez, F., D. P. Ryan, B. Grüning, V. Bhardwaj, F. Kilpert, A. S. Richter, S. Heyne, F. Dündar, and T. Manke. 2016. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Research 44: W160-165. doi: 10.1093/nar/gkw257.
phantompeakqualtools/1.2:
Landt S. G., G. K. Marinov, A. Kundaje, et al. 2012. ChIP-seq guidelines and practices of the ENCODE and modENCODE consortia. Genome Res 9: 1813-31. doi: 10.1101/gr.136184.111.
Kharchenko P. K., M. Y. Tolstorukov, and P. J. Park. 2008. Design and analysis of ChIP-seq experiments for DNA-binding proteins. Nat Biotechnol 26(12): 1351-1359.
macs/2.1.0-20151222:
Zhang Y., T. Liu, C. A. Meyer, J. Eeckhoute, D. S. Johnson, B. E. Bernstein, C. Nusbaum, R. M. Myers, M. Brown, W. Li, and X. S. Liu. 2008. Model-based Analysis of ChIP-Seq (MACS). Genome Biol 9: R137.
UCSC_userApps/v317
Kent W. J., A. S. Zweig, G. Barber, A. S. Hinrichs, and D. Karolchik. BigWig and BigBed: enabling browsing of large distributed data sets. Bioinformatics 26(17): 2204-2207.
R/3.3.2-gccmkl:
R Core Team 2014. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/.
meme/4.11.1-gcc-openmpi:
Bailey T. L., M. Bodén, F. A. Buske, M. Frith, C. E. Grant, L. Clementi, J. Ren, W. W. Li, and W. S. Noble. 2009. MEME SUITE: tools for motif discovery and searching. Nucleic Acids Research 37: W202-W208.
Machanick P., and T. L. Bailey. 2011. MEME-ChIP: motif analysis of large DNA datasets. Bioinformatics 27(12): 1696-1697.
R ChIPseeker:
Yu G., L. Wang, and Q. He. 2015. ChIPseeker: an R/Bioconductor package for ChIP peak annotation, comparison and visualization. Bioinformatics 31(14): 2382-2383. doi: 10.1093/bioinformatics/btv145.
R DiffBind:
Stark R., and G. Brown. 2011. DiffBind: differential binding analysis of ChIP-Seq peak data. http://bioconductor.org/packages/release/bioc/vignettes/DiffBind/inst/doc/DiffBind.pdf.
Ross-Innes C. S., R. Stark, A. E. Teschendorff, K. A. Holmes, H. R. Ali, M. J. Dunning, G. D. Brown, O. Gojis, I. O. Ellis, A. R. Green, S. Ali, S. Chin, C. Palmieri, C. Caldas, and J. S. Carroll. 2012. Differential oestrogen receptor binding is associated with clinical outcome in breast cancer. Nature 481: 389-393. http://www.nature.com/nature/journal/v481/n7381/full/nature10730.html.
