articles.bib

@article{berger2008variation,
  title={{Variation in homeodomain DNA binding revealed by high-resolution analysis of sequence preferences}},
  author={Berger, Michael F and Badis, Gwenael and Gehrke, Andrew R and Talukder, Shaheynoor and Philippakis, Anthony A and Pena-Castillo, Lourdes and Alleyne, Trevis M and Mnaimneh, Sanie and Botvinnik, Olga B and Chan, Esther T and others},
  journal={Cell},
  volume={133},
  number={7},
  pages={1266--1276},
  year={2008},
  publisher={Elsevier}
}

@article{wood2012microscale,
  title={{MicroSCALE screening reveals genetic modifiers of therapeutic response in melanoma}},
  author={Wood, Kris C and Konieczkowski, David J and Johannessen, Cory M and Boehm, Jesse S and Tamayo, Pablo and Botvinnik, Olga B and Mesirov, Jill P and Hahn, William C and Root, David E and Garraway, Levi A and others},
  journal={Science Signaling},
  volume={5},
  number={224},
  pages={rs4},
  year={2012},
  publisher={NIH Public Access}
}

@article{galili2012prediction,
  title={Prediction of response to therapy with ezatiostat in lower risk myelodysplastic syndrome},
  author={Galili, Naomi and Tamayo, Pablo and Botvinnik, Olga B and Mesirov, Jill P and Brooks, Margarita R and Brown, Gail and Raza, Azra},
  journal={Journal of Hematology \& Oncology},
  volume={5},
  number={1},
  pages={1},
  year={2012},
  publisher={BioMed Central}
}

@article{galili2011gene,
  title={{Gene Expression Studies May Identify Lower Risk Myelodysplastic Syndrome Patients Likely to Respond to Therapy with Ezatiostat Hydrochloride (TLK199)}},
  author={Galili, Naomi and Tamayo, Pablo and Botvinnik, Olga B and Mesirov, Jill P and Zikria, Jennifer and Brown, Gail and Raza, Azra},
  journal={Blood},
  volume={118},
  number={21},
  pages={2779--2779},
  year={2011},
  publisher={American Society of Hematology}
}

@article{kim2016characterizing,
  title={Characterizing genomic alterations in cancer by complementary functional associations},
  author={Kim*, Jong Wook and Botvinnik*, Olga B and Abudayyeh, Omar and Birger, Chet and Rosenbluh, Joseph and Shrestha, Yashaswi and Abazeed, Mohamed E and Hammerman, Peter S and DiCara, Daniel and Konieczkowski, David J and others},
  journal={Nature Biotechnology},
  year={2016},
  publisher={Nature Publishing Group},
  note={* These authors contributed equally to this work}
}

@article{song2017,
  title={{Single-Cell Alternative Splicing Analysis with Expedition Reveals Splicing Dynamics during Neuron Differentiation}},
  author={Song*, Yan and Botvinnik*, Olga B and Lovci, Michael T and Kakaradov, Boyko and Liu, Patrick and Xu, Jia L and Yeo, Gene},
  journal={Molecular Cell},
  year={2017},
  publisher={Nature Publishing Group},
  note={* These authors contributed equally to this work}
}

@article{Goncearenco:2012eha,
author = {Goncearenco, A and Grynberg, P and Botvinnik, Olga B and Macintyre, Geoff and Abeel, Thomas},
title = {{Highlights from the Eighth International Society for Computational Biology (ISCB) Student Council Symposium 2012}},
journal = {BMC Bioinformatics},
year = {2012},
doi = {10.1186/1471-2105-13-S18-A1},
read = {Yes},
rating = {0},
date-added = {2016-12-26T22:41:19GMT},
date-modified = {2016-12-26T22:45:51GMT},
abstract = {... BMC Bioinformatics201213(Suppl 18):A1. DOI: 10.1186 / 1471 - 2105 - 13 - S18 - A1 . {\textcopyright} Goncearenco et al; licensee BioMed Central Ltd. 2012. Published: 14 December 2012. Abstract. The report summarizes the scientific content of ...
},
url = {http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-13-S18-A1},
local-url = {file://localhost/Users/olga/Documents/Library.papers3/Articles/2012/Goncearenco/2012%20Goncearenco.pdf},
file = {{2012 Goncearenco.pdf:/Users/olga/Documents/Library.papers3/Articles/2012/Goncearenco/2012 Goncearenco.pdf:application/pdf}},
uri = {\url{papers3://publication/doi/10.1186/1471-2105-13-S18-A1}}
}


%% Created using Papers on Mon, 26 Dec 2016.
%% http://papersapp.com/papers/

@article{Nutter:2016fd,
author = {Nutter, Curtis A and Jaworski, Elizabeth A and Verma, Sunil K and Deshmukh, Vaibhav and Wang, Qiongling and Botvinnik, Olga B and Lozano, Mario J and Abass, Ismail J and Ijaz, Talha and Brasier, Allan R and Garg, Nisha J and Wehrens, Xander H T and Yeo, Gene W and Kuyumcu-Martinez, Muge N},
title = {{Dysregulation of RBFOX2 Is an Early Event in Cardiac Pathogenesis of Diabetes}},
journal = {Cell Reports},
year = {2016},
volume = {15},
number = {10},
pages = {2200--2213},
doi = {10.1016/j.celrep.2016.05.002},
language = {English},
rating = {0},
date-added = {2016-12-26T22:41:36GMT},
date-modified = {2016-12-26T22:43:33GMT},
url = {http://linkinghub.elsevier.com/retrieve/pii/S2211124716305551},
local-url = {file://localhost/Users/olga/Documents/Library.papers3/Articles/2016/Nutter/Cell%20Reports%202016%20Nutter.pdf},
file = {{Cell Reports 2016 Nutter.pdf:/Users/olga/Documents/Library.papers3/Articles/2016/Nutter/Cell Reports 2016 Nutter.pdf:application/pdf;Cell Reports 2016 Nutter.pdf:/Users/olga/Documents/Library.papers3/Articles/2016/Nutter/Cell Reports 2016 Nutter.pdf:application/pdf}},
uri = {\url{papers3://publication/doi/10.1016/j.celrep.2016.05.002}}
}


@ARTICLE{Klopfenstein2018-jb,
  title    = "{GOATOOLS}: {A Python library for Gene Ontology analyses}",
  author   = "Klopfenstein, D V and Zhang, Liangsheng and Pedersen, Brent S and
              Ram{\'\i}rez, Fidel and Warwick Vesztrocy, Alex and Naldi,
              Aur{\'e}lien and Mungall, Christopher J and Yunes, Jeffrey M and
              Botvinnik, Olga B and Weigel, Mark and Dampier, Will and Dessimoz,
              Christophe and Flick, Patrick and Tang, Haibao",
  abstract = "The biological interpretation of gene lists with interesting
              shared properties, such as up- or down-regulation in a particular
              experiment, is typically accomplished using gene ontology
              enrichment analysis tools. Given a list of genes, a gene ontology
              (GO) enrichment analysis may return hundreds of statistically
              significant GO results in a ``flat'' list, which can be
              challenging to summarize. It can also be difficult to keep pace
              with rapidly expanding biological knowledge, which often results
              in daily changes to any of the over 47,000 gene ontologies that
              describe biological knowledge. GOATOOLS, a Python-based library,
              makes it more efficient to stay current with the latest
              ontologies and annotations, perform gene ontology enrichment
              analyses to determine over- and under-represented terms, and
              organize results for greater clarity and easier interpretation
              using a novel GOATOOLS GO grouping method. We performed
              functional analyses on both stochastic simulation data and real
              data from a published RNA-seq study to compare the enrichment
              results from GOATOOLS to two other popular tools: DAVID and
              GOstats. GOATOOLS is freely available through GitHub:
              https://github.com/tanghaibao/goatools .",
  journal  = "Sci. Rep.",
  volume   =  8,
  number   =  1,
  pages    = "10872",
  month    =  jul,
  year     =  2018,
  language = "en"
}



@article{TabulaMuris:2018gj,
author = {{Tabula Muris Consortium}},
title = {{Single-cell transcriptomics of 20 mouse organs creates a Tabula Muris}},
journal = {Nature},
year = {2018},
pages = {1--25},
month = oct,
URL = {https://www.nature.com/articles/s41586-018-0590-4},
eprint = {https://www.biorxiv.org/content/early/2017/12/20/237446.full.pdf}
}

@ARTICLE{Harris2020-oe,
  title     = "cerebra: A tool for fast and accurate summarizing of variant
               calling format ({VCF}) files",
  author    = "Harris, Lincoln and Vanheusden, Rohan and Botvinnik, Olga B and
               Darmanis, Spyros",
  journal   = "J. Open Source Softw.",
  publisher = "The Open Journal",
  volume    =  5,
  number    =  54,
  pages     = "2432",
  month     =  oct,
  year      =  2020,
  copyright = "http://creativecommons.org/licenses/by/4.0/"
}


@ARTICLE{Shah2020-qy,
  title    = "Clinical features, diagnostics, and outcomes of patients
              presenting with acute respiratory illness: A retrospective cohort
              study of patients with and without {COVID-19}",
  author   = "Shah, Sachin J and Barish, Peter N and Prasad, Priya A and
              Kistler, Amy and Neff, Norma and Kamm, Jack and Li, Lucy M and
              Chiu, Charles Y and Babik, Jennifer M and Fang, Margaret C and
              Abe-Jones, Yumiko and Alipanah, Narges and Alvarez, Francisco N
              and Botvinnik, Olga B and Castaneda, Gloria and {CZB
              CLIAhub Consortium} and Dadasovich, Rand M and Davis, Jennifer
              and Deng, Xianding and DeRisi, Joseph L and Detweiler, Angela M
              and Federman, Scot and Haliburton, John and Hao, Samantha and
              Kerkhoff, Andrew D and Kumar, G Renuka and Malcolm, Katherine B
              and Mann, Sabrina A and Martinez, Sandra and Mary, Rupa K and
              Mick, Eran and Mwakibete, Lusajo and Najafi, Nader and Peluso,
              Michael J and Phelps, Maira and Pisco, Angela Oliveira and
              Ratnasiri, Kalani and Rubio, Luis A and Sellas, Anna and
              Sherwood, Kyla D and Sheu, Jonathan and Spottiswoode, Natasha and
              Tan, Michelle and Yu, Guixia and Kangelaris, Kirsten Neudoerffer
              and Langelier, Charles",
  abstract = "BACKGROUND: Most data on the clinical presentation, diagnostics,
              and outcomes of patients with COVID-19 have been presented as
              case series without comparison to patients with other acute
              respiratory illnesses. METHODS: We examined emergency department
              patients between February 3 and March 31, 2020 with an acute
              respiratory illness who were tested for SARS-CoV-2. We determined
              COVID-19 status by PCR and metagenomic next generation sequencing
              (mNGS). We compared clinical presentation, diagnostics,
              treatment, and outcomes. FINDINGS: Among 316 patients, 33 tested
              positive for SARS-CoV-2; 31 without COVID-19 tested positive for
              another respiratory virus. Among patients with additional viral
              testing (27/33), no SARS-CoV-2 co-infections were identified.
              Compared to those who tested negative, patients with COVID-19
              reported longer symptoms duration (median 7d vs. 3d, p < 0.001).
              Patients with COVID-19 were more often hospitalized (79\% vs.
              56\%, p = 0.014). When hospitalized, patients with COVID-19 had
              longer hospitalizations (median 10.7d vs. 4.7d, p < 0.001) and
              more often developed ARDS (23\% vs. 3\%, p < 0.001). Most
              comorbidities, medications, symptoms, vital signs, laboratories,
              treatments, and outcomes did not differ by COVID-19 status.
              INTERPRETATION: While we found differences in clinical features
              of COVID-19 compared to other acute respiratory illnesses, there
              was significant overlap in presentation and comorbidities.
              Patients with COVID-19 were more likely to be admitted to the
              hospital, have longer hospitalizations and develop ARDS, and were
              unlikely to have co-existent viral infections. FUNDING: National
              Center for Advancing Translational Sciences, National Heart Lung
              Blood Institute, National Institute of Allergy and Infectious
              Diseases, Chan Zuckerberg Biohub, Chan Zuckerberg Initiative.",
  journal  = "EClinicalMedicine",
  volume   =  27,
  pages    = "100518",
  month    =  oct,
  year     =  2020,
  language = "en"
}



@ARTICLE{Tabula_Sapiens_Consortium2022-iy,
  title    = "{The Tabula Sapiens: A} multiple-organ, single-cell transcriptomic
              atlas of humans",
  author   = "{Tabula Sapiens Consortium}",
  abstract = "Molecular characterization of cell types using single-cell
              transcriptome sequencing is revolutionizing cell biology and
              enabling new insights into the physiology of human organs. We
              created a human reference atlas comprising nearly 500,000 cells
              from 24 different tissues and organs, many from the same donor.
              This atlas enabled molecular characterization of more than 400
              cell types, their distribution across tissues, and
              tissue-specific variation in gene expression. Using multiple
              tissues from a single donor enabled identification of the clonal
              distribution of T cells between tissues, identification of the
              tissue-specific mutation rate in B cells, and analysis of the
              cell cycle state and proliferative potential of shared cell types
              across tissues. Cell type-specific RNA splicing was discovered
              and analyzed across tissues within an individual.",
  journal  = "Science",
  volume   =  376,
  number   =  6594,
  pages    = "eabl4896",
  month    =  may,
  year     =  2022,
  language = "en"
}









@article{Reiter2022-co,
  title    = "Protein k-mers enable assembly-free microbial metapangenomics",
  author   = "Reiter, Taylor E and Tessa Pierce-Ward, N and Irber, Luiz and
              Botvinnik, Olga B and Titus Brown, C",
  abstract = "An estimated 2 billion species of microbes exist on Earth with
              orders of magnitude more strains. Microbial pangenomes are
              created by aggregating all genomes of a single clade and reflect
              the metabolic diversity of groups of organisms. As de novo
              metagenome analysis techniques have matured and reference genome
              databases have expanded, metapangenome analysis has risen in
              popularity as a tool to organize the functional potential of
              organisms in relation to the environment from which those
              organisms were sampled. However, the reliance on assembly and
              binning or on reference databases often leaves substantial
              portions of metagenomes unanalyzed, thereby underestimating the
              functional potential of a community. To address this challenge,
              we present a method for metapangenomics that relies on amino acid
              k-mers (kaa-mers) and metagenome assembly graph queries. To
              enable this method, we first show that kaa-mers estimate
              pangenome characteristics and that open reading frames can be
              accurately predicted from short shotgun sequencing reads using
              the previously developed tool orpheum. These techniques enable
              pangenomics to be performed directly on short sequencing reads.
              To enable metapangenome analysis, we combine these approaches
              with compact de Bruijn assembly graph queries to directly
              generate sets of sequencing reads for a specific species from a
              metagenome. When applied to stool metagenomes from an individual
              receiving antibiotics over time, we show that these approaches
              identify strain fluctuations that coincide with antibiotic
              exposure. \#\#\# Competing Interest Statement The authors have
              declared no competing interest.",
  journal  = "bioRxiv",
  pages    = "2022.06.27.497795",
  month    =  jun,
  year     =  2022,
  language = "en"
}

% The entry below contains non-ASCII chars that could not be converted
% to a LaTeX equivalent.
@article{Ezran2021-ci,
  title     = "{Tabula Microcebus: A transcriptomic cell atlas of mouse lemur,
               an emerging primate model organism}",
  author    = "Ezran, C and Liu, S and Chang, S and Ming, J and Botvinnik, Olga B
               and {others}",
  abstract  = "Mouse lemurs are the smallest, fastest reproducing, and among
               the most abundant primates, and an emerging model organism for
               primate biology, behavior, health and …",
  journal   = "bioRxiv",
  publisher = "biorxiv.org",
  year      =  2021
}

@article{The_Tabula_Microcebus_Consortium2022-zo,
  title    = "Mouse lemur transcriptomic atlas elucidates primate genes,
              physiology, disease, and evolution",
  author   = "{The Tabula Microcebus Consortium} and Ezran, Camille and Liu,
              Shixuan and Ming, Jingsi and Guethlein, Lisbeth A and Wang,
              Michael F Z and Dehghannasiri, Roozbeh and Olivieri, Julia and
              Frank, Hannah K and Tarashansky, Alexander and Koh, Winston and
              Jing, Qiuyu and Botvinnik, Olga B and Antony, Jane and Chang,
              Stephen and Pisco, Angela Oliveira and Karkanias, Jim and Yang,
              Can and Ferrell, James E and Boyd, Scott D and Parham, Peter and
              Long, Jonathan Z and Wang, Bo and Salzman, Julia and De Vlaminck,
              Iwijn and Wu, Angela and Quake, Stephen R and Krasnow, Mark A",
  abstract = "Mouse lemurs ( Microcebus spp.) are an emerging model organism
              for primate biology, behavior, health, and conservation. Although
              little has been known about their cellular and molecular biology,
              in the accompanying paper we used large-scale single cell
              RNA-sequencing of 27 organs and tissues to identify over 750
              molecular cell types and their full transcriptomic profiles. Here
              we use this extensive transcriptomic dataset to uncover thousands
              of previously unidentified genes and hundreds of thousands of new
              splice junctions in the reference genome that globally define
              lemur gene structures and cell-type selective expression and
              splicing and to investigate gene expression evolution. We use the
              atlas to explore the biology and function of the lemur immune
              system, including the expression profiles across the organism of
              all MHC genes and chemokines in health and disease, and the
              mapping of neutrophil and macrophage development, trafficking,
              and activation, their local and global responses to infection,
              and primate-specific aspects of the program. We characterize
              other examples of primate-specific physiology and disease such as
              unique features of lemur adipocytes that may underlie their
              dramatic seasonal rhythms, and spontaneous metastatic endometrial
              cancer that models the human gynecological malignancy. We
              identify and describe the organism-wide expression profiles of
              over 400 primate genes missing in mice, some implicated in human
              disease. Thus, an organism-wide molecular cell atlas and
              molecular cell autopsies can enhance gene discovery, structure
              definition, and annotation in a new model organism, and can
              identify and elucidate primate-specific genes, physiology,
              diseases, and evolution. \#\#\# Competing Interest Statement The
              authors have declared no competing interest.",
  journal  = "bioRxiv",
  pages    = "2022.08.06.503035",
  month    =  aug,
  year     =  2022,
  language = "en"
}


@article{Botvinnik2021-hd,
  title       = "Single-cell transcriptomics for the 99.9\% of species without
                 reference genomes",
  author      = "Botvinnik, Olga B and Vemuri, Venkata Naga Pranathi
                 and Tessa Pierce, N and Logan, Phoenix Aja and Nafees, Saba
                 and Karanam, Lekha and Travaglini, Kyle Joseph and Ezran,
                 Camille Sophie and Ren, Lili and Juang, Yanyi and Wang,
                 Jianwei and Wang, Jianbin and Titus Brown, C",
  abstract    = "Single-cell RNA-seq (scRNA-seq) is a powerful tool for cell
                 type identification but is not readily applicable to organisms
                 without well-annotated reference genomes. Of the approximately
                 10 million animal species predicted to exist on Earth, >99.9\%
                 do not have any submitted genome assembly. To enable scRNA-seq
                 for the vast majority of animals on the planet, here we
                 introduce the concept of `` k -mer homology,'' combining
                 biochemical synonyms in degenerate protein alphabets with
                 uniform data subsampling via MinHash into a pipeline called
                 Kmermaid. Implementing this pipeline enables direct detection
                 of similar cell types across species from transcriptomic data
                 without the need for a reference genome. Underpinning Kmermaid
                 is the tool Orpheum, a memory-efficient method for extracting
                 high-confidence protein-coding sequences from RNA-seq data.
                 After validating Kmermaid using datasets from human and mouse
                 lung, we applied Kmermaid to the Chinese horseshoe bat (
                 Rhinolophus sinicus ), where we propagated cellular
                 compartment labels at high fidelity. Our pipeline provides a
                 high-throughput tool that enables analyses of transcriptomic
                 data across divergent species' transcriptomes in a genome- and
                 gene annotation-agnostic manner. Thus, the combination of
                 Kmermaid and Orpheum identifies cell type-specific sequences
                 that may be missing from genome annotations and empowers
                 molecular cellular phenotyping for novel model organisms and
                 species. \#\#\# Competing Interest Statement The authors have
                 declared no competing interest.",
  journal     = "bioRxiv",
  pages       = "2021.07.09.450799",
  month       =  jul,
  year        =  2021,
  language    = "en",
  original_id = "49bb2a0b-21b5-057e-a0ae-b42df83f1e23"
}


@ARTICLE{Luecken2024-mx,
  title     = "Defining and benchmarking open problems in single-cell analysis",
  author    = "Luecken, Malte D and Gigante, Scott and Burkhardt, Daniel B and
               Cannoodt, Robrecht and Strobl, Daniel C and Markov, Nikolay S and
               Zappia, Luke and Palla, Giovanni and Lewis, Wesley and Dimitrov,
               Daniel and Vinyard, Michael E and Magruder, D S and Andersson,
               Alma and Dann, Emma and Qin, Qian and Otto, Dominik J and Klein,
               Michal and Botvinnik, Olga B and Deconinck, Louise and
               Waldrant, Kai and {Open Problems Jamboree Members} and Bloom,
               Jonathan M and Pisco, Angela Oliveira and Saez-Rodriguez, Julio
               and Wulsin, Drausin and Pinello, Luca and Saeys, Yvan and Theis,
               Fabian J and Krishnaswamy, Smita",
  journal   = "Res. Sq.",
  publisher = "American Journal Experts",
  abstract  = "With the growing number of single-cell analysis tools, benchmarks
               are increasingly important to guide analysis and method
               development. However, a lack of standardisation and extensibility
               in current benchmarks limits their usability, longevity, and
               relevance to the community. We present Open Problems, a living,
               extensible, community-guided benchmarking platform including 10
               current single-cell tasks that we envision will raise standards
               for the selection, evaluation, and development of methods in
               single-cell analysis.",
  month     =  apr,
  year      =  2024,
  language  = "en"
}


@article{irber2024sourmash,
  title={sourmash v4: A multitool to quickly search, compare, and analyze genomic and metagenomic data sets},
  author={Irber, Luiz and Pierce-Ward, N Tessa and Abuelanin, Mohamed and Alexander, Harriet and Anant, Abhishek and Barve, Keya and Baumler, Colton and Botvinnik, Olga B and Brooks, Phillip and Dsouza, Daniel and others},
  journal={Journal of Open Source Software},
  volume={9},
  number={98},
  pages={6830},
  year={2024}
}