Thesis/code-refs.bib

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@misc{gh-cd4-csaw,
	Abstract = {epic is a software package for finding medium to diffusely enriched domains in chip-seq data. It is a fast, parallel and memory-efficient implementation of the incredibly popular SICER algorithm. By running epic on a set of data ("ChIP") files and control ("Input") files, epic is able to quickly differentially enriched regions.

epic is an improvement over the original SICER by being faster, more memory efficient, multicore, and significantly much easier to install and use.},
	Author = {Ryan C. Thompson},
	Date-Added = {2019-08-01 02:15:39 -0700},
	Date-Modified = {2019-08-01 02:15:39 -0700},
	Howpublished = {\url{https://github.com/DarwinAwardWinner/CD4-csaw}},
	Keywords = {chipseq, rnaseq},
	Month = {nov},
	Publisher = {GitHub, Inc.},
	Title = {Reproducible reanalysis of a combined ChIP-Seq \& RNA-Seq data set},
	Year = {2018},
	Bdsk-Url-1 = {https://doi.org/10.5281/zenodo.806811}}

@manual{greylistchip,
	Author = {Gord Brown},
	Date-Added = {2019-08-01 02:00:09 -0700},
	Date-Modified = {2019-08-01 02:03:29 -0700},
	Edition = {R package version 1.16.0.},
	Organization = {Bioconductor},
	Title = {GreyListChIP: Grey Lists -- Mask Artefact Regions Based on ChIP Inputs},
	Year = {2019}}

@misc{gh-epic,
	Abstract = {epic is a software package for finding medium to diffusely enriched domains in chip-seq data. It is a fast, parallel and memory-efficient implementation of the incredibly popular SICER algorithm. By running epic on a set of data ("ChIP") files and control ("Input") files, epic is able to quickly differentially enriched regions.

epic is an improvement over the original SICER by being faster, more memory efficient, multicore, and significantly much easier to install and use.},
	Author = {Endre Bakken Stovner},
	Date-Added = {2019-08-01 01:47:19 -0700},
	Date-Modified = {2019-08-01 01:47:19 -0700},
	Howpublished = {\url{https://github.com/biocore-ntnu/epic}},
	Keywords = {chipseq},
	Month = {nov},
	Publisher = {GitHub, Inc.},
	Title = {epic: diffuse domain ChIP-Seq caller based on SICER},
	Year = {2018},
	Bdsk-Url-1 = {https://doi.org/10.5281/zenodo.806811}}

@misc{gh-hg38-ref,
	Abstract = {epic is a software package for finding medium to diffusely enriched domains in chip-seq data. It is a fast, parallel and memory-efficient implementation of the incredibly popular SICER algorithm. By running epic on a set of data ("ChIP") files and control ("Input") files, epic is able to quickly differentially enriched regions.

epic is an improvement over the original SICER by being faster, more memory efficient, multicore, and significantly much easier to install and use.},
	Author = {Ryan C. Thompson},
	Date-Added = {2019-08-01 01:44:09 -0700},
	Date-Modified = {2019-08-01 02:17:22 -0700},
	Howpublished = {\url{https://github.com/DarwinAwardWinner/hg38-ref}},
	Month = {dec},
	Publisher = {GitHub, Inc.},
	Title = {Workflow to download/generate various mapping indices for the human hg38 genome},
	Year = {2016},
	Bdsk-Url-1 = {https://doi.org/10.5281/zenodo.806811}}