myunpubs.bib

@unpublished{globin-reduction,
  abstract = {Primate blood contains high concentrations of globin messenger RNA. Globin reduction is a standard technique used to improve the expression results obtained by DNA microarrays on RNA from blood samples. However, with whole transcriptome RNA-sequencing (RNA-seq) quickly replacing microarrays for many applications, the impact of globin reduction for RNA-seq has not been previously studied. Moreover, no off-the-shelf kits are available for globin reduction in nonhuman primates. Here we report a protocol for RNA-seq in primate blood samples that uses complimentary oligonucleotides to block reverse transcription of the alpha and beta globin genes. In test samples from cynomolgus monkeys (Macaca fascicularis), this globin blocking protocol approximately doubles the yield of informative (non-globin) reads by greatly reducing the fraction of globin reads, while also improving the consistency in sequencing depth between samples. The increased yield enables detection of about 2000 more genes, significantly increases the correlation in measured gene expression levels between samples, and increases the sensitivity of differential gene expression tests. These results show that globin blocking significantly improves the cost-effectiveness of mRNA sequencing in primate blood samples by doubling the yield of useful reads, allowing detection of more genes, and improving the precision of gene expression measurements. Based on these results, a globin reducing or blocking protocol is recommended for all RNA-seq studies of primate blood samples.},
  address = {{La Jolla, CA}},
  author = {Thompson, Ryan C. and Gelbart, Terri and Head, Steven R and Ordoukhanian, Phillip and Mullen, Courtney and Han, Dongmei and Berman, Dora M and Bartholomew, Amelia and Kenyon, Norma S and Salomon, Daniel R},
  keywords = {\#nosource},
  note = {Institution: The Scripps Research Institute},
  title = {Optimizing Yield of Deep {{RNA}} Sequencing for Gene Expression Profiling of Peripheral Blood Samples from Cynomolgus Monkeys ({{Macaca}} Fascicularis). ({{In}} Preparation)},
  year = {2019}
}

@article{Scott2016,
  author = {Scott, Erick R and Larman, H Benjamin and Torkamani, Ali and Schork, Nicholas J and Wineinger, Nathan and Nanis, Max and Thompson, Ryan C. and Beheshti Zavareh, Reza B. and Lairson, Luke L and Schultz, Peter G and Su, Andrew I.},
  doi = {10/ggcxmn},
  file = {/Users/ryan/Zotero/storage/STZYTJ26/Scott et al_2016_RASLseqTools.pdf},
  journal = {bioRxiv},
  title = {{{RASLseqTools}}: Open-Source Methods for Designing and Analyzing {{RNA}}-Mediated Oligonucleotide {{Annealing}}, {{Selection}}, and, {{Ligation}} Sequencing ({{RASL}}-Seq) Experiments},
  year = {2016}
}

@misc{Thompson2008,
  author = {Thompson, Ryan C.},
  copyright = {Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC-BY-NC-SA)},
  file = {/Users/ryan/Zotero/storage/SFULV6YT/Thompson_2008_The Sources and Limits of Geometric Rigor from Euclid Through Descartes.pdf},
  month = may,
  note = {Institution: University of Virginia},
  title = {The {{Sources}} and {{Limits}} of {{Geometric Rigor}} from {{Euclid Through Descartes}}},
  url = {http://darwinawardwinner.github.io/resume/examples/UVa/math-history-paper.pdf},
  year = {2008}
}

@misc{Thompson2009,
  abstract = {Here we present Contig Farmer, a tool for improving the length and depth of coverage of contigs gener- ated from a database of short sequence reads. Contig Farmer works without assembling the entire database and has only modest hardware requirements. The underlying methodology of Contig Farmer is iterative growth of seed contigs using repeated search and assembly. The utility of Contig Farmer is demonstrated on the sequences in TOBFAC, the database of tobacco transcription factors. Contig Farmer successfully grew the TOBFAC contigs, both in length and in depth of coverage, to yield a larger, higher-quality set of contigs.},
  author = {Thompson, Ryan C. and Rushton, Paul J. and Laudeman, Tom W. and Timko, Michael P.},
  copyright = {Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC-BY-NC-SA)},
  file = {/Users/ryan/Zotero/storage/W289P5S8/Thompson et al_2009_Contig Farmer.pdf},
  month = jun,
  note = {Institution: University of Virginia},
  title = {Contig {{Farmer}} : {{A}} Tool for Extracting Maximal-Length Contiguous Sequences from a Database of Short Sequence Reads ({{Undergraduate Thesis}})},
  url = {http://darwinawardwinner.github.io/resume/examples/UVa/contigfarmer.pdf},
  year = {2009}
}

@phdthesis{Thompson2019,
  abstract = {Transplant rejection mediated by adaptive immune response is the major challenge to long-term graft survival. Rejection is treated with immune suppressive drugs, but early diagnosis is essential for effective treatment. Memory lymphocytes are known to resist immune suppression, but the precise regulatory mechanisms underlying immune memory are still poorly understood. High-throughput genomic assays such as microarrays, RNA-seq, and ChIP-seq are heavily used in the study of immunology and transplant rejection. Here we present 3 analyses of such assays in this context. First, we re-analyze a large data set consisting of H3K4me2, H3K4me3, and H3K27me3 ChIP-seq data and RNA-seq data in na{\"i}ve and memory CD4+ T-cells using modern bioinformatics methods designed to address deficiencies in the data and extend the analysis in several new directions. All 3 histone marks are found to occur in broad regions and are enriched near promoters, but the radius of promoter enrichment is found to be larger for H3K27me3. We observe that both gene expression and promoter histone methylation in na{\"i}ve and memory cells converges on a common signature 14 days after activation, consistent with differentiation of na{\"i}ve cells into memory cells. The location of histone modifications within the promoter is also found to be important, with asymmetric associations with gene expression for peaks located the same distance up- or downstream of the TSS. Second, we demonstrate the effectiveness of fRMA as a single-channel normalization for using expression arrays to diagnose transplant rejection in a clinical diagnostic setting, and we develop a custom fRMA normalization for a previously unsupported array platform. For methylation arrays, we adapt methods designed for RNA-seq to improve the sensitivity of differential methylation analysis by modeling the heteroskedasticity inherent in the data. Finally, we present and validate a novel method for RNA-seq of cynomolgus monkey blood samples using complementary oligonucleotides to prevent wasteful over-sequencing of globin genes. These results all demonstrate the usefulness of a toolbox full of flexible and modular analysis methods in analyzing complex high-throughput assays in contexts ranging from basic science to translational medicine.},
  author = {Thompson, Ryan C.},
  file = {/Users/ryan/Zotero/storage/384V48WH/Thompson_2019_Bioinformatic analysis of complex , high-throughput genomic and epigenomic data.pdf},
  school = {The Scripps Research Institute},
  title = {Bioinformatic Analysis of Complex , High-Throughput Genomic and Epigenomic Data in the Context of {{CD4}}+ {{T}}-Cell Differentiation and Diagnosis and Treatment of Transplant Rejection},
  year = {2019}
}

@unpublished{Thompson2019a,
  address = {{La Jolla, CA}},
  author = {Thompson, Ryan C. and Lamere, Sarah A. and Salomon, Daniel R.},
  keywords = {\#nosource},
  note = {Institution: The Scripps Research Institute},
  title = {Reproducible Genome-Wide Epigenetic Analysis of {{H3K4}} and {{H3K27}} Methylation in Na{\"i}ve and Memory {{CD4}}+ {{T}}-Cell Activation. ({{In}} Preparation)},
  year = {2019}
}