GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Eran Eden,Roy Navon,Roy Navon,Israel Steinfeld,Israel Steinfeld,Doron Lipson,Zohar Yakhini,Zohar Yakhini +7 more
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TLDR
GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets, and its unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation.Abstract:
Since the inception of the GO annotation project, a variety of tools have been developed that support exploring and searching the GO database In particular, a variety of tools that perform GO enrichment analysis are currently available Most of these tools require as input a target set of genes and a background set and seek enrichment in the target set compared to the background set A few tools also exist that support analyzing ranked lists The latter typically rely on simulations or on union-bound correction for assigning statistical significance to the results GOrilla is a web-based application that identifies enriched GO terms in ranked lists of genes, without requiring the user to provide explicit target and background sets This is particularly useful in many typical cases where genomic data may be naturally represented as a ranked list of genes (eg by level of expression or of differential expression) GOrilla employs a flexible threshold statistical approach to discover GO terms that are significantly enriched at the top of a ranked gene list Building on a complete theoretical characterization of the underlying distribution, called mHG, GOrilla computes an exact p-value for the observed enrichment, taking threshold multiple testing into account without the need for simulations This enables rigorous statistical analysis of thousand of genes and thousands of GO terms in order of seconds The output of the enrichment analysis is visualized as a hierarchical structure, providing a clear view of the relations between enriched GO terms GOrilla is an efficient GO analysis tool with unique features that make a useful addition to the existing repertoire of GO enrichment tools GOrilla's unique features and advantages over other threshold free enrichment tools include rigorous statistics, fast running time and an effective graphical representation GOrilla is publicly available at: http://cbl-gorillacstechnionacilread more
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Exposure to the gut microbiota drives distinct methylome and transcriptome changes in intestinal epithelial cells during postnatal development
Wei-Hung Pan,Felix Sommer,Felix Sommer,Maren Falk-Paulsen,Thomas Ulas,Philipp Best,Antonella Fazio,Priyadarshini Kachroo,Anne Luzius,Marlene Jentzsch,Ateequr Rehman,Fabian Müller,Thomas Lengauer,Thomas Lengauer,Joern Walter,Sven Künzel,John F. Baines,John F. Baines,Stefan Schreiber,Andre Franke,Joachim L. Schultze,Joachim L. Schultze,Fredrik Bäckhed,Fredrik Bäckhed,Philip Rosenstiel +24 more
TL;DR: This study represents the first genome-wide analysis of microbiota-mediated effects on maturation of DNA methylation signatures and the transcriptional program of IECs after birth and indicates that the gut microbiota dynamically modulates large portions of the epithelial transcriptome during postnatal development, but targets only a subset of microbially responsive genes through theirDNA methylation status.
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Structural, geometric and genetic factors predict interregional brain connectivity patterns probed by electrocorticography.
Richard F. Betzel,John D. Medaglia,Ari E. Kahn,Jonathan Soffer,Daniel R. Schonhaut,Danielle S. Bassett +5 more
TL;DR: The basic organization of ECoG networks is characterized, including frequency-specific architecture, segregated modules and the dependence of connection weights on interregional Euclidean distance, and linear models are used to explain variabilities in the connection strengths between pairs of brain regions.
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Mouse-Human Experimental Epigenetic Analysis Unmasks Dietary Targets and Genetic Liability for Diabetic Phenotypes
Michael L. Multhaup,Marcus M. Seldin,Andrew E. Jaffe,Xia Lei,Henriette Kirchner,Prosenjit Mondal,Yuan-Yuan Li,Varenka Rodriguez,Alexander W. Drong,Mehboob A. Hussain,Cecilia M. Lindgren,Mark I. McCarthy,Mark I. McCarthy,Mark I. McCarthy,Erik Näslund,Juleen R. Zierath,G. William Wong,Andrew P. Feinberg +17 more
TL;DR: Functional analysis of genes associated with differentially DNA-methylated genomic regions revealed four genes with roles in insulin resistance, demonstrating the potential general utility of this approach for complementing conventional human genetic studies by integrating cross-species epigenomics and clinical genetic risk.
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Merging transcriptomics and metabolomics - advances in breast cancer profiling
Eldrid Borgan,Beathe Sitter,Ole Christian Lingjærde,Hilde Johnsen,Steinar Lundgren,Tone Frost Bathen,Therese Sørlie,Therese Sørlie,Anne Lise Børresen-Dale,Anne Lise Børresen-Dale,Ingrid S. Gribbestad +10 more
TL;DR: Combining transcriptional and metabolic data from the same breast carcinoma sample is feasible and may contribute to a more refined subclassification of breast cancers as well as reveal relations between metabolic and transcriptional levels.
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De Novo Mutation in Genes Regulating Neural Stem Cell Fate in Human Congenital Hydrocephalus
Charuta G. Furey,Jungmin Choi,Sheng Chih Jin,Xue Zeng,Andrew T. Timberlake,Carol Nelson-Williams,M. Shahid Mansuri,Qiongshi Lu,Daniel Duran,Shreyas Panchagnula,August A Allocco,Jason K. Karimy,Arjun Khanna,Jonathan Gaillard,Tyrone DeSpenza,Prince Antwi,Erin Loring,William E. Butler,Edward R. Smith,Benjamin C. Warf,Jennifer Strahle,David D. Limbrick,Phillip B. Storm,Phillip B. Storm,Gregory G. Heuer,Gregory G. Heuer,Eric M. Jackson,Bermans J. Iskandar,James M. Johnston,Irina Tikhonova,Christopher Castaldi,Francesc López-Giráldez,Robert D. Bjornson,James R. Knight,Kaya Bilguvar,Shrikant M. Mane,Seth L. Alper,Shozeb Haider,Bulent Guclu,Yasar Bayri,Yener Sahin,Michael L.J. Apuzzo,Charles C. Duncan,Michael L. DiLuna,Murat Gunel,Richard P. Lifton,Richard P. Lifton,Kristopher T. Kahle +47 more
TL;DR: Exome sequencing of 125 CH trios and 52 additional probands identified three genes with significant burden of rare damaging de novo or transmitted mutations and four genes required for neural tube development and regulate ventricular zone neural stem cell fate, implicate impaired neurogenesis in the pathogenesis of a subset of CH patients.
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