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- %% This BibTeX bibliography file was created using BibDesk.
- %% http://bibdesk.sourceforge.net/
- %% Created for Ryan C. Thompson at 2019-09-12 00:38:41 -0700
- %% Saved with string encoding Unicode (UTF-8)
- @misc{gh-idr,
- Author = {Nathan Boley},
- Date-Added = {2019-09-12 00:06:36 -0700},
- Date-Modified = {2019-09-12 00:07:34 -0700},
- Howpublished = {\url{https://github.com/nboley/idr/}},
- Month = {jun},
- Title = {Irreproducible Discovery Rate (IDR)},
- Year = {2017}}
- @misc{gh-shoal,
- Abstract = {shoal is a tool which jointly quantify transcript abundances across multiple samples. Specifically, shoal learns an empirical prior on transcript-level abundances across all of the samples in an experiment, and subsequently applies a variant of the variational Bayesian expectation maximization algorithm to apply this prior adaptively across multi-mapping groups of reads.
- shoal can increase quantification accuracy, inter-sample consistency, and reduce false positives in downstream differential analysis when applied to multi-condition RNA-seq experiments. Moreover, shoal, runs downstream of Salmon and requires less than a minute per-sample to re-estimate transcript abundances while accounting for the learned empirical prior.},
- Author = {Avi Srivastava, Michael Love, Rob Patro},
- Date-Added = {2019-09-11 22:55:19 -0700},
- Date-Modified = {2019-09-11 22:58:18 -0700},
- Howpublished = {\url{https://github.com/COMBINE-lab/shoal/}},
- Keywords = {rnaseq},
- Month = {jul},
- Title = {Shoal: Improved multi-sample transcript abundance estimates using adaptive priors},
- Year = {2017}}
- @misc{gh-cd4-csaw,
- Author = {Ryan C. Thompson},
- Date-Added = {2019-08-01 02:15:39 -0700},
- Date-Modified = {2019-08-28 09:49:36 -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}}
- @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}}
- @misc{gh-hg38-ref,
- Author = {Ryan C. Thompson},
- Date-Added = {2019-08-01 01:44:09 -0700},
- Date-Modified = {2019-08-28 09:49:47 -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}}
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