scispace - formally typeset
Search or ask a question
Institution

Broad Institute

NonprofitCambridge, Massachusetts, United States
About: Broad Institute is a nonprofit organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 6584 authors who have published 11618 publications receiving 1522743 citations. The organization is also known as: Eli and Edythe L. Broad Institute of MIT and Harvard.


Papers
More filters
Journal ArticleDOI
TL;DR: A short overview of IGV's variant review features for both single-nucleotide variants and structural variants, with examples from both cancer and germline datasets are presented.
Abstract: Manual review of aligned reads for confirmation and interpretation of variant calls is an important step in many variant calling pipelines for next-generation sequencing (NGS) data. Visual inspection can greatly increase the confidence in calls, reduce the risk of false positives, and help characterize complex events. The Integrative Genomics Viewer (IGV) was one of the first tools to provide NGS data visualization, and it currently provides a rich set of tools for inspection, validation, and interpretation of NGS datasets, as well as other types of genomic data. Here, we present a short overview of IGV9s variant review features for both single-nucleotide variants and structural variants, with examples from both cancer and germline datasets. IGV is freely available at https://www.igv.org. Cancer Res; 77(21); e31–34. ©2017 AACR.

694 citations

Journal ArticleDOI
TL;DR: It was found that higher neoantigen load was positively associated with overall lymphocytic infiltration, tumor-infiltrating lymphocytes, memory T cells, and CRC-specific survival and positive selection of mutations in HLA genes and other components of the antigen-processing machinery in TIL-rich tumors.

693 citations

Journal ArticleDOI
02 Aug 2012-Nature
TL;DR: Together, this study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic β-catenin signalling in medullOBlastoma.
Abstract: Medulloblastomas are the most common malignant brain tumours in children. Identifying and understanding the genetic events that drive these tumours is critical for the development of more effective diagnostic, prognostic and therapeutic strategies. Recently, our group and others described distinct molecular subtypes of medulloblastoma on the basis of transcriptional and copy number profiles. Here we use whole-exome hybrid capture and deep sequencing to identify somatic mutations across the coding regions of 92 primary medulloblastoma/normal pairs. Overall, medulloblastomas have low mutation rates consistent with other paediatric tumours, with a median of 0.35 non-silent mutations per megabase. We identified twelve genes mutated at statistically significant frequencies, including previously known mutated genes in medulloblastoma such as CTNNB1, PTCH1, MLL2, SMARCA4 and TP53. Recurrent somatic mutations were newly identified in an RNA helicase gene, DDX3X, often concurrent with CTNNB1 mutations, and in the nuclear co-repressor (N-CoR) complex genes GPS2, BCOR and LDB1. We show that mutant DDX3X potentiates transactivation of a TCF promoter and enhances cell viability in combination with mutant, but not wild-type, β-catenin. Together, our study reveals the alteration of WNT, hedgehog, histone methyltransferase and now N-CoR pathways across medulloblastomas and within specific subtypes of this disease, and nominates the RNA helicase DDX3X as a component of pathogenic β-catenin signalling in medulloblastoma.

692 citations

Journal ArticleDOI
TL;DR: The strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies are reviewed.
Abstract: With the completion of the human genome sequence, attention turned to identifying and annotating its functional DNA elements. As a complement to genetic and comparative genomics approaches, the Encyclopedia of DNA Elements Project was launched to contribute maps of RNA transcripts, transcriptional regulator binding sites, and chromatin states in many cell types. The resulting genome-wide data reveal sites of biochemical activity with high positional resolution and cell type specificity that facilitate studies of gene regulation and interpretation of noncoding variants associated with human disease. However, the biochemically active regions cover a much larger fraction of the genome than do evolutionarily conserved regions, raising the question of whether nonconserved but biochemically active regions are truly functional. Here, we review the strengths and limitations of biochemical, evolutionary, and genetic approaches for defining functional DNA segments, potential sources for the observed differences in estimated genomic coverage, and the biological implications of these discrepancies. We also analyze the relationship between signal intensity, genomic coverage, and evolutionary conservation. Our results reinforce the principle that each approach provides complementary information and that we need to use combinations of all three to elucidate genome function in human biology and disease.

691 citations

Journal ArticleDOI
Keith Bradnam1, Joseph Fass1, Anton Alexandrov, Paul Baranay2, Michael Bechner, Inanc Birol, Sébastien Boisvert3, Jarrod Chapman4, Guillaume Chapuis5, Guillaume Chapuis6, Rayan Chikhi5, Rayan Chikhi6, Hamidreza Chitsaz7, Wen-Chi Chou8, Jacques Corbeil3, Cristian Del Fabbro9, T. Roderick Docking, Richard Durbin10, Dent Earl11, Scott J. Emrich12, Pavel Fedotov, Nuno A. Fonseca13, Ganeshkumar Ganapathy14, Richard A. Gibbs15, Sante Gnerre16, Elenie Godzaridis3, Steve Goldstein, Matthias Haimel13, Giles Hall16, David Haussler11, Joseph B. Hiatt17, Isaac Ho4, Jason T. Howard14, Martin Hunt10, Shaun D. Jackman, David B. Jaffe16, Erich D. Jarvis14, Huaiyang Jiang15, Sergey Kazakov, Paul J. Kersey13, Jacob O. Kitzman17, James R. Knight, Sergey Koren18, Tak-Wah Lam, Dominique Lavenier5, Dominique Lavenier6, François Laviolette3, Yingrui Li, Zhenyu Li, Binghang Liu, Yue Liu15, Ruibang Luo, Iain MacCallum16, Matthew D. MacManes19, Nicolas Maillet6, Sergey Melnikov, Bruno Vieira20, Delphine Naquin6, Zemin Ning10, Thomas D. Otto10, Benedict Paten11, Octávio S. Paulo20, Adam M. Phillippy18, Francisco Pina-Martins20, Michael Place, Dariusz Przybylski16, Xiang Qin15, Carson Qu15, Filipe J. Ribeiro16, Stephen Richards15, Daniel S. Rokhsar4, Daniel S. Rokhsar19, J. Graham Ruby21, J. Graham Ruby22, Simone Scalabrin9, Michael C. Schatz23, David C. Schwartz, Alexey Sergushichev, Ted Sharpe16, Timothy I. Shaw8, Jay Shendure17, Yujian Shi, Jared T. Simpson10, Henry Song15, Fedor Tsarev, Francesco Vezzi24, Riccardo Vicedomini9, Jun Wang, Kim C. Worley15, Shuangye Yin16, Siu-Ming Yiu, Jianying Yuan, Guojie Zhang, Hao Zhang, Shiguo Zhou, Ian F Korf1 
TL;DR: The Assemblathon 2 as mentioned in this paper presented a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and a snake) from 21 participating teams.
Abstract: Background - The process of generating raw genome sequence data continues to become cheaper, faster, and more accurate. However, assembly of such data into high-quality, finished genome sequences remains challenging. Many genome assembly tools are available, but they differ greatly in terms of their performance (speed, scalability, hardware requirements, acceptance of newer read technologies) and in their final output (composition of assembled sequence). More importantly, it remains largely unclear how to best assess the quality of assembled genome sequences. The Assemblathon competitions are intended to assess current state-of-the-art methods in genome assembly. Results - In Assemblathon 2, we provided a variety of sequence data to be assembled for three vertebrate species (a bird, a fish, and snake). This resulted in a total of 43 submitted assemblies from 21 participating teams. We evaluated these assemblies using a combination of optical map data, Fosmid sequences, and several statistical methods. From over 100 different metrics, we chose ten key measures by which to assess the overall quality of the assemblies. Conclusions - Many current genome assemblers produced useful assemblies, containing a significant representation of their genes, regulatory sequences, and overall genome structure. However, the high degree of variability between the entries suggests that there is still much room for improvement in the field of genome assembly and that approaches which work well in assembling the genome of one species may not necessarily work well for another.

690 citations


Authors

Showing all 7146 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Albert Hofman2672530321405
Frank B. Hu2501675253464
David J. Hunter2131836207050
Kari Stefansson206794174819
Mark J. Daly204763304452
Lewis C. Cantley196748169037
Matthew Meyerson194553243726
Gad Getz189520247560
Stacey Gabriel187383294284
Stuart H. Orkin186715112182
Ralph Weissleder1841160142508
Chris Sander178713233287
Michael I. Jordan1761016216204
Richard A. Young173520126642
Network Information
Related Institutions (5)
Howard Hughes Medical Institute
34.6K papers, 5.2M citations

96% related

Salk Institute for Biological Studies
13.1K papers, 1.6M citations

94% related

Fred Hutchinson Cancer Research Center
30.9K papers, 2.2M citations

93% related

Scripps Research Institute
32.8K papers, 2.9M citations

93% related

Genentech
17.1K papers, 1.4M citations

93% related

Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202337
2022628
20211,727
20201,534
20191,364
20181,107