% Refs to be added

@article{Alasoo2018,
abstract = {Regulatory variants are often context specific, modulating gene expression in a subset of possible cellular states. Although these genetic effects can play important roles in disease, the molecular mechanisms underlying context specificity are poorly understood. Here, we identified shared quantitative trait loci (QTLs) for chromatin accessibility and gene expression in human macrophages exposed to IFN$\gamma$, Salmonella and IFN$\gamma$ plus Salmonella. We observed that {\~{}}60{\%} of stimulus-specific expression QTLs with a detectable effect on chromatin altered the chromatin accessibility in naive cells, thus suggesting that they perturb enhancer priming. Such variants probably influence binding of cell-type-specific transcription factors, such as PU.1, which can then indirectly alter the binding of stimulus-specific transcription factors, such as NF-$\kappa$B or STAT2. Thus, although chromatin accessibility assays are powerful for fine-mapping causal regulatory variants, detecting their downstream effects on gene expression will be challenging, requiring profiling of large numbers of stimulated cellular states and time points.},
author = {Alasoo, Kaur and Rodrigues, Julia and Mukhopadhyay, Subhankar and Knights, Andrew J. and Mann, Alice L. and Kundu, Kousik and Hale, Christine and Dougan, Gordon and Gaffney, Daniel J.},
doi = {10.1038/s41588-018-0046-7},
file = {:Users/fede/Library/Containers/com.apple.Preview/Data/Downloads/s41588-018-0046-7.pdf:pdf},
issn = {15461718},
journal = {Nature Genetics},
mendeley-groups = {ideal{\_}manuscript,GeneTonic{\_}manuscript},
number = {3},
pages = {424--431},
publisher = {Springer US},
title = {{Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response}},
url = {http://dx.doi.org/10.1038/s41588-018-0046-7},
volume = {50},
year = {2018}
}

@article{Love2014,
abstract = {In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html webcite.},
author = {Love, Michael I and Huber, Wolfgang and Anders, Simon},
doi = {10.1186/s13059-014-0550-8},
file = {:Users/fede/Library/Application Support/Mendeley Desktop/Downloaded/Love, Huber, Anders - 2014 - Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.pdf:pdf},
isbn = {1465-6906},
issn = {1474-760X},
journal = {Genome Biology},
keywords = {Algorithms,Computational Biology,Computational Biology: methods,Genetic,High-Throughput Nucleotide Sequencing,Models,RNA,RNA: analysis,Sequence Analysis,Software},
mendeley-groups = {PhDthesis,pcaExplorer{\_}manuscript,ideal{\_}manuscript,VFapplication,VF,iSEE,GeneTonic{\_}manuscript},
month = {dec},
number = {12},
pages = {550},
pmid = {25516281},
title = {{Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2}},
url = {http://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8},
volume = {15},
year = {2014}
}

@article{Love2016,
  title = {RNA-Seq workflow: gene-level exploratory analysis and differential expression},
  volume = {4},
  ISSN = {2046-1402},
  url = {http://dx.doi.org/10.12688/f1000research.7035.2},
  DOI = {10.12688/f1000research.7035.2},
  journal = {F1000Research},
  publisher = {F1000 Research Ltd},
  author = {Love,  Michael I. and Anders,  Simon and Kim,  Vladislav and Huber,  Wolfgang},
  year = {2016},
  month = nov,
  pages = {1070}
}

@article{Law2018,
  title = {RNA-seq analysis is easy as 1-2-3 with limma,  Glimma and edgeR},
  volume = {5},
  ISSN = {2046-1402},
  url = {http://dx.doi.org/10.12688/f1000research.9005.3},
  DOI = {10.12688/f1000research.9005.3},
  journal = {F1000Research},
  publisher = {F1000 Research Ltd},
  author = {Law,  Charity W. and Alhamdoosh,  Monther and Su,  Shian and Dong,  Xueyi and Tian,  Luyi and Smyth,  Gordon K. and Ritchie,  Matthew E.},
  year = {2018},
  month = dec,
  pages = {1408}
}

@article{Ludt2022,
  title = {Interactive and Reproducible Workflows for Exploring and Modeling RNA‐seq Data with pcaExplorer,  Ideal,  and GeneTonic},
  volume = {2},
  ISSN = {2691-1299},
  url = {http://dx.doi.org/10.1002/cpz1.411},
  DOI = {10.1002/cpz1.411},
  number = {4},
  journal = {Current Protocols},
  publisher = {Wiley},
  author = {Ludt,  Annekathrin and Ustjanzew,  Arsenij and Binder,  Harald and Strauch,  Konstantin and Marini,  Federico},
  year = {2022},
  month = apr
}

@article{Kang2017,
  title = {Multiplexed droplet single-cell RNA-sequencing using natural genetic variation},
  volume = {36},
  ISSN = {1546-1696},
  url = {http://dx.doi.org/10.1038/nbt.4042},
  DOI = {10.1038/nbt.4042},
  number = {1},
  journal = {Nature Biotechnology},
  publisher = {Springer Science and Business Media LLC},
  author = {Kang,  Hyun Min and Subramaniam,  Meena and Targ,  Sasha and Nguyen,  Michelle and Maliskova,  Lenka and McCarthy,  Elizabeth and Wan,  Eunice and Wong,  Simon and Byrnes,  Lauren and Lanata,  Cristina M and Gate,  Rachel E and Mostafavi,  Sara and Marson,  Alexander and Zaitlen,  Noah and Criswell,  Lindsey A and Ye,  Chun Jimmie},
  year = {2017},
  month = dec,
  pages = {89–94}
}
