Idan Gabdank
Stanford University
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Featured researches published by Idan Gabdank.
Nucleic Acids Research | 2016
Cricket A. Sloan; Esther T. Chan; Jean M. Davidson; Venkat S. Malladi; J. Seth Strattan; Benjamin C. Hitz; Idan Gabdank; Aditi K. Narayanan; Marcus Ho; Brian T. Lee; Laurence D. Rowe; Timothy R. Dreszer; Greg Roe; Nikhil R. Podduturi; Forrest Tanaka; Eurie L. Hong; J. Michael Cherry
The Encyclopedia of DNA Elements (ENCODE) Project is in its third phase of creating a comprehensive catalog of functional elements in the human genome. This phase of the project includes an expansion of assays that measure diverse RNA populations, identify proteins that interact with RNA and DNA, probe regions of DNA hypersensitivity, and measure levels of DNA methylation in a wide range of cell and tissue types to identify putative regulatory elements. To date, results for almost 5000 experiments have been released for use by the scientific community. These data are available for searching, visualization and download at the new ENCODE Portal (www.encodeproject.org). The revamped ENCODE Portal provides new ways to browse and search the ENCODE data based on the metadata that describe the assays as well as summaries of the assays that focus on data provenance. In addition, it is a flexible platform that allows integration of genomic data from multiple projects. The portal experience was designed to improve access to ENCODE data by relying on metadata that allow reusability and reproducibility of the experiments.
Database | 2016
Eurie L. Hong; Cricket A. Sloan; Esther T. Chan; Jean M. Davidson; Venkat S. Malladi; J. Seth Strattan; Benjamin C. Hitz; Idan Gabdank; Aditi K. Narayanan; Marcus Ho; Brian T. Lee; Laurence D. Rowe; Timothy R. Dreszer; Greg Roe; Nikhil R. Podduturi; Forrest Tanaka; Jason A Hilton; J. Michael Cherry
The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center (DCC) is responsible for organizing, describing and providing access to the diverse data generated by the ENCODE project. The description of these data, known as metadata, includes the biological sample used as input, the protocols and assays performed on these samples, the data files generated from the results and the computational methods used to analyze the data. Here, we outline the principles and philosophy used to define the ENCODE metadata in order to create a metadata standard that can be applied to diverse assays and multiple genomic projects. In addition, we present how the data are validated and used by the ENCODE DCC in creating the ENCODE Portal (https://www.encodeproject.org/). Database URL: www.encodeproject.org
Nucleic Acids Research | 2018
Carrie A Davis; Benjamin C. Hitz; Cricket A. Sloan; Esther T. Chan; Jean M. Davidson; Idan Gabdank; Jason A Hilton; Kriti Jain; Ulugbek K Baymuradov; Aditi K. Narayanan; Kathrina C. Onate; Keenan Graham; Stuart R. Miyasato; Timothy R. Dreszer; J. Seth Strattan; Otto Jolanki; Forrest Tanaka; J. Michael Cherry
Abstract The Encyclopedia of DNA Elements (ENCODE) Data Coordinating Center has developed the ENCODE Portal database and website as the source for the data and metadata generated by the ENCODE Consortium. Two principles have motivated the design. First, experimental protocols, analytical procedures and the data themselves should be made publicly accessible through a coherent, web-based search and download interface. Second, the same interface should serve carefully curated metadata that record the provenance of the data and justify its interpretation in biological terms. Since its initial release in 2013 and in response to recommendations from consortium members and the wider community of scientists who use the Portal to access ENCODE data, the Portal has been regularly updated to better reflect these design principles. Here we report on these updates, including results from new experiments, uniformly-processed data from other projects, new visualization tools and more comprehensive metadata to describe experiments and analyses. Additionally, the Portal is now home to meta(data) from related projects including Genomics of Gene Regulation, Roadmap Epigenome Project, Model organism ENCODE (modENCODE) and modERN. The Portal now makes available over 13000 datasets and their accompanying metadata and can be accessed at: https://www.encodeproject.org/.
BMC Genomics | 2016
Idan Gabdank; Sreejith Ramakrishnan; Anne M. Villeneuve; Andrew Fire
BackgroundIdentification of locus-locus contacts at the chromatin level provides a valuable foundation for understanding of nuclear architecture and function and a valuable tool for inferring long-range linkage relationships. As one approach to this, chromatin conformation capture-based techniques allow creation of genome spatial organization maps. While such approaches have been available for some time, methodological advances will be of considerable use in minimizing both time and input material required for successful application.ResultsHere we report a modified tethered conformation capture protocol that utilizes a series of rapid and efficient molecular manipulations. We applied the method to Caenorhabditis elegans, obtaining chromatin interaction maps that provide a sequence-anchored delineation of salient aspects of Caenorhabditis elegans chromosome structure, demonstrating a high level of consistency in overall chromosome organization between biological samples collected under different conditions. In addition to the application of the method to defining nuclear architecture, we found the resulting chromatin interaction maps to be of sufficient resolution and sensitivity to enable detection of large-scale structural variants such as inversions or translocations.ConclusionOur streamlined protocol provides an accelerated, robust, and broadly applicable means of generating chromatin spatial organization maps and detecting genome rearrangements without a need for cellular or chromatin fractionation.
G3: Genes, Genomes, Genetics | 2017
Massa J. Shoura; Idan Gabdank; Loren Hansen; Jason D. Merker; Jason Gotlib; Stephen D. Levene; Andrew Fire
Investigations aimed at defining the 3D configuration of eukaryotic chromosomes have consistently encountered an endogenous population of chromosome-derived circular genomic DNA, referred to as extrachromosomal circular DNA (eccDNA). While the production, distribution, and activities of eccDNAs remain understudied, eccDNA formation from specific regions of the linear genome has profound consequences on the regulatory and coding capabilities for these regions. Here, we define eccDNA distributions in Caenorhabditis elegans and in three human cell types, utilizing a set of DNA topology-dependent approaches for enrichment and characterization. The use of parallel biophysical, enzymatic, and informatic approaches provides a comprehensive profiling of eccDNA robust to isolation and analysis methodology. Results in human and nematode systems provide quantitative analysis of the eccDNA loci at both unique and repetitive regions. Our studies converge on and support a consistent picture, in which endogenous genomic DNA circles are present in normal physiological states, and in which the circles come from both coding and noncoding genomic regions. Prominent among the coding regions generating DNA circles are several genes known to produce a diversity of protein isoforms, with mucin proteins and titin as specific examples.
bioRxiv | 2017
Massa J. Shoura; Idan Gabdank; Loren Hansen; Jason D. Merker; Jason Gotlib; Stephen D. Levene; Andrew Fire
Investigations aimed at defining the 3-D configuration of eukaryotic chromosomes have consistently encountered an endogenous population of chromosome-derived circular genomic DNA, referred to as extrachromosomal circular DNA (eccDNA). While the production, distribution, and activities of eccDNAs remain understudied, eccDNA formation from specific regions of the linear genome has profound consequences on the regulatory and coding capabilities for these regions. High-throughput sequencing has only recently made extensive genomic mapping of eccDNA sequences possible and had yet to be applied using a rigorous approach that distinguishes ascertainment bias from true enrichment. Here, we define eccDNA distribution, utilizing a set of unbiased topology-dependent approaches for enrichment and characterization. We use parallel biophysical, enzymatic, and informatic approaches to obtain a comprehensive profiling of eccDNA in C. elegans and in three human cell types, where eccDNAs were previously uncharacterized. We also provide quantitative analysis of the eccDNA loci at both unique and repetitive regions. Our studies converge on and support a consistent picture in which endogenous genomic DNA circles are present in normal physiological DNA metabolism, and in which the circles come from both coding and noncoding genomic regions. Prominent among the coding regions generating DNA circles are several genes known to produce a diversity of protein isoforms, with mucin proteins and titin as specific examples.
G3: Genes, Genomes, Genetics | 2014
Idan Gabdank; Andrew Fire
In certain organisms, numbers of crossover events for any single chromosome are limited (“crossover interference”) so that double crossover events are obtained at much lower frequencies than would be expected from the simple product of independent single-crossover events. We present a number of observations during which we examined interference over a large region of Caenorhabditis elegans chromosome V. Examining this region for multiple crossover events in heteroallelic configurations with limited dimorphism, we observed high levels of crossover interference in oocytes with only partial interference in spermatocytes.
Computational Biology and Chemistry | 2012
Alexander Churkin; Idan Gabdank; Danny Barash
The secondary structure of RNAs can be represented by graphs at various resolutions. While it was shown that RNA secondary structures can be represented by coarse grain tree-graphs and meaningful topological indices can be used to distinguish between various structures, small RNAs are needed to be represented by full graphs. No meaningful topological index has yet been suggested for the analysis of such type of RNA graphs. Recalling that the second eigenvalue of the Laplacian matrix can be used to track topological changes in the case of coarse grain tree-graphs, it is plausible to assume that a topological index such as the Wiener index that represents all Laplacian eigenvalues may provide a similar guide for full graphs. However, by its original definition, the Wiener index was defined for acyclic graphs. Nevertheless, similarly to cyclic chemical graphs, small RNA graphs can be analyzed using elementary cuts, which enables the calculation of topological indices for small RNAs in an intuitive way. We show how to calculate a structural descriptor that is suitable for cyclic graphs, the Szeged index, for small RNA graphs by elementary cuts. We discuss potential uses of such a procedure that considers all eigenvalues of the associated Laplacian matrices to quantify the topology of small RNA graphs.
PLOS ONE | 2017
Benjamin C. Hitz; Laurence D. Rowe; Nikhil R. Podduturi; David I. Glick; Ulugbek K Baymuradov; Venkat S. Malladi; Esther T. Chan; Jean M. Davidson; Idan Gabdank; Aditi K. Narayana; Kathrina C. Onate; Jason A Hilton; Marcus Ho; Brian T. Lee; Stuart R. Miyasato; Timothy R. Dreszer; Cricket A. Sloan; J. Seth Strattan; Forrest Tanaka; Eurie L. Hong; J. Michael Cherry
The Encyclopedia of DNA elements (ENCODE) project is an ongoing collaborative effort to create a comprehensive catalog of functional elements initiated shortly after the completion of the Human Genome Project. The current database exceeds 6500 experiments across more than 450 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the H. sapiens and M. musculus genomes. All ENCODE experimental data, metadata, and associated computational analyses are submitted to the ENCODE Data Coordination Center (DCC) for validation, tracking, storage, unified processing, and distribution to community resources and the scientific community. As the volume of data increases, the identification and organization of experimental details becomes increasingly intricate and demands careful curation. The ENCODE DCC has created a general purpose software system, known as SnoVault, that supports metadata and file submission, a database used for metadata storage, web pages for displaying the metadata and a robust API for querying the metadata. The software is fully open-source, code and installation instructions can be found at: http://github.com/ENCODE-DCC/snovault/ (for the generic database) and http://github.com/ENCODE-DCC/encoded/ to store genomic data in the manner of ENCODE. The core database engine, SnoVault (which is completely independent of ENCODE, genomic data, or bioinformatic data) has been released as a separate Python package.
Database | 2018
Idan Gabdank; Esther T. Chan; Jean M. Davidson; Jason A Hilton; Carrie A Davis; Ulugbek K Baymuradov; Aditi K. Narayanan; Kathrina C. Onate; Keenan Graham; Stuart R. Miyasato; Timothy R. Dreszer; J. Seth Strattan; Otto Jolanki; Forrest Tanaka; Benjamin C. Hitz; Cricket A. Sloan; J. Michael Cherry
Abstract Prevention of unintended duplication is one of the ongoing challenges many databases have to address. Working with high-throughput sequencing data, the complexity of that challenge increases with the complexity of the definition of a duplicate. In a computational data model, a data object represents a real entity like a reagent or a biosample. This representation is similar to how a card represents a book in a paper library catalog. Duplicated data objects not only waste storage, they can mislead users into assuming the model represents more than the single entity. Even if it is clear that two objects represent a single entity, data duplication opens the door to potential inconsistencies between the objects since the content of the duplicated objects can be updated independently, allowing divergence of the metadata associated with the objects. Analogously to a situation in which a catalog in a paper library would contain by mistake two cards for a single copy of a book. If these cards are listing simultaneously two different individuals as current book borrowers, it would be difficult to determine which borrower (out of the two listed) actually has the book. Unfortunately, in a large database with multiple submitters, unintended duplication is to be expected. In this article, we present three principal guidelines the Encyclopedia of DNA Elements (ENCODE) Portal follows in order to prevent unintended duplication of both actual files and data objects: definition of identifiable data objects (I), object uniqueness validation (II) and de-duplication mechanism (III). In addition to explaining our modus operandi, we elaborate on the methods used for identification of sequencing data files. Comparison of the approach taken by the ENCODE Portal vs other widely used biological data repositories is provided. Database URL: https://www.encodeproject.org/