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Genotype Fingerprints Enable Fast And Private Comparison Of Genetic Testing Results For Research And Direct-To-Consumer Applications., Max Robinson, Gustavo Glusman

Articles, Abstracts, and Reports

Genetic testing has expanded out of the research laboratory into medical practice and the direct-to-consumer market. Rapid analysis of the resulting genotype data now has a significant impact. We present a method for summarizing personal genotypes as 'genotype fingerprints' that meets these needs. Genotype fingerprints can be derived from any single nucleotide polymorphism-based assay, and remain comparable as chip designs evolve to higher marker densities. We demonstrate that these fingerprints support distinguishing types of relationships among closely related individuals and closely related individuals from individuals from the same background population, as well as high-throughput identification of identical genotypes, individuals in …

Lineage Marker Synchrony In Hematopoietic Genealogies Refutes The Pu.1/Gata1 Toggle Switch Paradigm., Michael K Strasser, Philipp S Hoppe, Dirk Loeffler, Konstantinos D Kokkaliaris, Timm Schroeder, Fabian J Theis, Carsten Marr

Articles, Abstracts, and Reports

Molecular regulation of cell fate decisions underlies health and disease. To identify molecules that are active or regulated during a decision, and not before or after, the decision time point is crucial. However, cell fate markers are usually delayed and the time of decision therefore unknown. Fortunately, dividing cells induce temporal correlations in their progeny, which allow for retrospective inference of the decision time point. We present a computational method to infer decision time points from correlated marker signals in genealogies and apply it to differentiating hematopoietic stem cells. We find that myeloid lineage decisions happen generations before lineage marker …

A Protein Standard That Emulates Homology For The Characterization Of Protein Inference Algorithms., Matthew The, Fredrik Edfors, Yasset Perez-Riverol, Samuel H Payne, Michael R Hoopmann, Magnus Palmblad, Björn Forsström, Lukas Käll

Articles, Abstracts, and Reports

A natural way to benchmark the performance of an analytical experimental setup is to use samples of known composition and see to what degree one can correctly infer the content of such a sample from the data. For shotgun proteomics, one of the inherent problems of interpreting data is that the measured analytes are peptides and not the actual proteins themselves. As some proteins share proteolytic peptides, there might be more than one possible causative set of proteins resulting in a given set of peptides and there is a need for mechanisms that infer proteins from lists of detected peptides. …

Mapping Genetic Variations To Three-Dimensional Protein Structures To Enhance Variant Interpretation: A Proposed Framework., Gustavo Glusman, Peter W Rose, Andreas Prlić, Jennifer Dougherty, José M Duarte, Andrew S Hoffman, Geoffrey J Barton, Emøke Bendixen, Timothy Bergquist, Christian Bock, Elizabeth Brunk, Marija Buljan, Stephen K Burley, Binghuang Cai, Hannah Carter, Jianjiong Gao, Adam Godzik, Michael Heuer, Michael Hicks, Thomas Hrabe, Rachel Karchin, Julia Koehler Leman, Lydie Lane, David L Masica, Sean D Mooney, John Moult, Gilbert S Omenn, Frances Pearl, Vikas Pejaver, Sheila M Reynolds, Ariel Rokem, Torsten Schwede, Sicheng Song, Hagen Tilgner, Yana Valasatava, Yang Zhang, Eric W Deutsch

Articles, Abstracts, and Reports

The translation of personal genomics to precision medicine depends on the accurate interpretation of the multitude of genetic variants observed for each individual. However, even when genetic variants are predicted to modify a protein, their functional implications may be unclear. Many diseases are caused by genetic variants affecting important protein features, such as enzyme active sites or interaction interfaces. The scientific community has catalogued millions of genetic variants in genomic databases and thousands of protein structures in the Protein Data Bank. Mapping mutations onto three-dimensional (3D) structures enables atomic-level analyses of protein positions that may be important for the stability …

Solving The Influence Maximization Problem Reveals Regulatory Organization Of The Yeast Cell Cycle., David L Gibbs, Ilya Shmulevich

Articles, Abstracts, and Reports

The Influence Maximization Problem (IMP) aims to discover the set of nodes with the greatest influence on network dynamics. The problem has previously been applied in epidemiology and social network analysis. Here, we demonstrate the application to cell cycle regulatory network analysis for Saccharomyces cerevisiae. Fundamentally, gene regulation is linked to the flow of information. Therefore, our implementation of the IMP was framed as an information theoretic problem using network diffusion. Utilizing more than 26,000 regulatory edges from YeastMine, gene expression dynamics were encoded as edge weights using time lagged transfer entropy, a method for quantifying information transfer between variables. …

The Acttion-Aps-Aapm Pain Taxonomy (Aaapt) Multidimensional Approach To Classifying Acute Pain Conditions., Michael L Kent, Patrick J Tighe, Inna Belfer, Timothy J Brennan, Stephen Bruehl, Chad M Brummett, Chester C Buckenmaier, Asokumar Buvanendran, Robert I Cohen, Paul Desjardins, David Edwards, Roger Fillingim, Jennifer Gewandter, Debra B Gordon, Robert W Hurley, Henrik Kehlet, John D Loeser, Sean Mackey, Samuel A Mclean, Rosemary Polomano, Siamak Rahman, Srinivasa Raja, Michael Rowbotham, Santhanam Suresh, Bernard Schachtel, Kristin Schreiber, Mark Schumacher, Brett Stacey, Steven P Stanos, Knox Todd, Dennis C Turk, Steven J Weisman, Christopher Wu, Daniel B Carr, Robert H Dworkin, Gregory Terman

Articles, Abstracts, and Reports

Objective: With the increasing societal awareness of the prevalence and impact of acute pain, there is a need to develop an acute pain classification system that both reflects contemporary mechanistic insights and helps guide future research and treatment. Existing classifications of acute pain conditions are limiting, with a predominant focus on the sensory experience (e.g., pain intensity) and pharmacologic consumption. Consequently, there is a need to more broadly characterize and classify the multidimensional experience of acute pain.

Setting: Consensus report following expert panel involving the Analgesic, Anesthetic, and Addiction Clinical Trial Translations, Innovations, Opportunities, and Networks (ACTTION), American Pain Society …

Multiscale Mutation Clustering Algorithm Identifies Pan-Cancer Mutational Clusters Associated With Pathway-Level Changes In Gene Expression., William Poole, Kalle Leinonen, Ilya Shmulevich, Theo A Knijnenburg, Brady Bernard

Articles, Abstracts, and Reports

Cancer researchers have long recognized that somatic mutations are not uniformly distributed within genes. However, most approaches for identifying cancer mutations focus on either the entire-gene or single amino-acid level. We have bridged these two methodologies with a multiscale mutation clustering algorithm that identifies variable length mutation clusters in cancer genes. We ran our algorithm on 539 genes using the combined mutation data in 23 cancer types from The Cancer Genome Atlas (TCGA) and identified 1295 mutation clusters. The resulting mutation clusters cover a wide range of scales and often overlap with many kinds of protein features including structured domains, …

Ultrafast Comparison Of Personal Genomes Via Precomputed Genome Fingerprints., Gustavo Glusman, Denise E Mauldin, Leroy E Hood, Max Robinson

Articles, Abstracts, and Reports

We present an ultrafast method for comparing personal genomes. We transform the standard genome representation (lists of variants relative to a reference) into "genome fingerprints" via locality sensitive hashing. The resulting genome fingerprints can be meaningfully compared even when the input data were obtained using different sequencing technologies, processed using different pipelines, represented in different data formats and relative to different reference versions. Furthermore, genome fingerprints are robust to up to 30% missing data. Because of their reduced size, computation on the genome fingerprints is fast and requires little memory. For example, we could compute all-against-all pairwise comparisons among the …

Annotation Of Alternatively Spliced Proteins And Transcripts With Protein-Folding Algorithms And Isoform-Level Functional Networks., Hongdong Li, Yang Zhang, Yuanfang Guan, Rajasree Menon, Gilbert S Omenn

Articles, Abstracts, and Reports

Tens of thousands of splice isoforms of proteins have been catalogued as predicted sequences from transcripts in humans and other species. Relatively few have been characterized biochemically or structurally. With the extensive development of protein bioinformatics, the characterization and modeling of isoform features, isoform functions, and isoform-level networks have advanced notably. Here we present applications of the I-TASSER family of algorithms for folding and functional predictions and the IsoFunc, MIsoMine, and Hisonet data resources for isoform-level analyses of network and pathway-based functional predictions and protein-protein interactions. Hopefully, predictions and insights from protein bioinformatics will stimulate many experimental validation studies.

Logic Models To Predict Continuous Outputs Based On Binary Inputs With An Application To Personalized Cancer Therapy., Theo A Knijnenburg, Gunnar W Klau, Francesco Iorio, Mathew J Garnett, Ultan Mcdermott, Ilya Shmulevich, Lodewyk F A Wessels

Articles, Abstracts, and Reports

Mining large datasets using machine learning approaches often leads to models that are hard to interpret and not amenable to the generation of hypotheses that can be experimentally tested. We present 'Logic Optimization for Binary Input to Continuous Output' (LOBICO), a computational approach that infers small and easily interpretable logic models of binary input features that explain a continuous output variable. Applying LOBICO to a large cancer cell line panel, we find that logic combinations of multiple mutations are more predictive of drug response than single gene predictors. Importantly, we show that the use of the continuous information leads to …

An Open Data Format For Visualization And Analysis Of Cross-Linked Mass Spectrometry Results., Michael R Hoopmann, Luis Mendoza, Eric W Deutsch, David Shteynberg, Robert L Moritz

Articles, Abstracts, and Reports

Protein-protein interactions are an important element in the understanding of protein function, and chemical cross-linking shotgun mass spectrometry is rapidly becoming a routine approach to identify these specific interfaces and topographical interactions. Protein cross-link data analysis is aided by dozens of algorithm choices, but hindered by a lack of a common format for representing results. Consequently, interoperability between algorithms and pipelines utilizing chemical cross-linking remains a challenge. pepXML is an open, widely-used format for representing spectral search algorithm results that has facilitated information exchange and pipeline development for typical shotgun mass spectrometry analyses. We describe an extension of this format …