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Article: hipFG: High-throughput harmonization and integration pipeline for functional genomics data.

Cifello, Jeffrey / Kuksa, Pavel P / Saravanan, Naveensri / Valladares, Otto / Leung, Yuk Yee / Wang, Li-San

bioRxiv : the preprint server for biology

2023

Abstract: Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG, an ... ...

Abstract	Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG, an automatically customized pipeline for efficient and scalable normalization of heterogenous FG data collections into standardized, indexed, rapidly searchable analysis-ready datasets while accounting for FG datatypes (e.g., chromatin interactions, genomic intervals, quantitative trait loci).
Language	English
Publishing date	2023-04-25
Publishing country	United States
Document type	Preprint
DOI	10.1101/2023.04.21.537695
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Article ; Online: hipFG: high-throughput harmonization and integration pipeline for functional genomics data.

Cifello, Jeffrey / Kuksa, Pavel P / Saravanan, Naveensri / Valladares, Otto / Wang, Li-San / Leung, Yuk Yee

Bioinformatics (Oxford, England)

2023 Volume 39, Issue 11

Abstract: Summary: Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce ... ...

Abstract	Summary: Preparing functional genomic (FG) data with diverse assay types and file formats for integration into analysis workflows that interpret genome-wide association and other studies is a significant and time-consuming challenge. Here we introduce hipFG (Harmonization and Integration Pipeline for Functional Genomics), an automatically customized pipeline for efficient and scalable normalization of heterogenous FG data collections into standardized, indexed, rapidly searchable analysis-ready datasets while accounting for FG datatypes (e.g. chromatin interactions, genomic intervals, quantitative trait loci). Availability and implementation: hipFG is freely available at https://bitbucket.org/wanglab-upenn/hipFG. A Docker container is available at https://hub.docker.com/r/wanglab/hipfg.
MeSH term(s)	Software ; Genome-Wide Association Study ; Genomics ; Chromatin ; Quantitative Trait Loci
Chemical Substances	Chromatin
Language	English
Publishing date	2023-12-06
Publishing country	England
Document type	Journal Article
ZDB-ID	1422668-6
ISSN	1367-4811 ; 1367-4803
ISSN (online)	1367-4811
ISSN	1367-4803
DOI	10.1093/bioinformatics/btad673
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Article ; Online: A comparative study of structural variant calling in WGS from Alzheimer's disease families.

Malamon, John S / Farrell, John J / Xia, Li Charlie / Dombroski, Beth A / Das, Rueben G / Way, Jessica / Kuzma, Amanda B / Valladares, Otto / Leung, Yuk Yee / Scanlon, Allison J / Lopez, Irving Antonio Barrera / Brehony, Jack / Worley, Kim C / Zhang, Nancy R / Wang, Li-San / Farrer, Lindsay A / Schellenberg, Gerard D / Lee, Wan-Ping / Vardarajan, Badri N

Life science alliance

2024 Volume 7, Issue 5

Abstract: Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in ... ...

Abstract	Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.
MeSH term(s)	Humans ; Alzheimer Disease/genetics ; Whole Genome Sequencing/methods
Language	English
Publishing date	2024-02-28
Publishing country	United States
Document type	Journal Article
ISSN	2575-1077
ISSN (online)	2575-1077
DOI	10.26508/lsa.202302181
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Article ; Online: NIAGADS Alzheimer's GenomicsDB: A resource for exploring Alzheimer's disease genetic and genomic knowledge.

Greenfest-Allen, Emily / Valladares, Otto / Kuksa, Pavel P / Gangadharan, Prabhakaran / Lee, Wan-Ping / Cifello, Jeffrey / Katanic, Zivadin / Kuzma, Amanda B / Wheeler, Nicholas / Bush, William S / Leung, Yuk Yee / Schellenberg, Gerard / Stoeckert, Christian J / Wang, Li-San

Alzheimer's & dementia : the journal of the Alzheimer's Association

2023 Volume 20, Issue 2, Page(s) 1123–1136

Abstract: Introduction: The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site Alzheimer's Genomics Database (GenomicsDB) is a public knowledge base of Alzheimer's disease (AD) genetic datasets and genomic annotations.: Methods: ... ...

Abstract	Introduction: The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site Alzheimer's Genomics Database (GenomicsDB) is a public knowledge base of Alzheimer's disease (AD) genetic datasets and genomic annotations. Methods: GenomicsDB uses a custom systems architecture to adopt and enforce rigorous standards that facilitate harmonization of AD-relevant genome-wide association study summary statistics datasets with functional annotations, including over 230 million annotated variants from the AD Sequencing Project. Results: GenomicsDB generates interactive reports compiled from the harmonized datasets and annotations. These reports contextualize AD-risk associations in a broader functional genomic setting and summarize them in the context of functionally annotated genes and variants. Discussion: Created to make AD-genetics knowledge more accessible to AD researchers, the GenomicsDB is designed to guide users unfamiliar with genetic data in not only exploring but also interpreting this ever-growing volume of data. Scalable and interoperable with other genomics resources using data technology standards, the GenomicsDB can serve as a central hub for research and data analysis on AD and related dementias. Highlights: The National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) offers to the public a unique, disease-centric collection of AD-relevant GWAS summary statistics datasets. Interpreting these data is challenging and requires significant bioinformatics expertise to standardize datasets and harmonize them with functional annotations on genome-wide scales. The NIAGADS Alzheimer's GenomicsDB helps overcome these challenges by providing a user-friendly public knowledge base for AD-relevant genetics that shares harmonized, annotated summary statistics datasets from the NIAGADS repository in an interpretable, easily searchable format.
MeSH term(s)	United States ; Humans ; Alzheimer Disease/genetics ; Genome-Wide Association Study ; National Institute on Aging (U.S.) ; Genomics ; Databases, Factual ; Genetic Predisposition to Disease/genetics
Language	English
Publishing date	2023-10-26
Publishing country	United States
Document type	Journal Article
ZDB-ID	2211627-8
ISSN	1552-5279 ; 1552-5260
ISSN (online)	1552-5279
ISSN	1552-5260
DOI	10.1002/alz.13509
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Zs.MO 540: Show issues

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Article ; Online: FILER: a framework for harmonizing and querying large-scale functional genomics knowledge.

Kuksa, Pavel P / Leung, Yuk Yee / Gangadharan, Prabhakaran / Katanic, Zivadin / Kleidermacher, Lauren / Amlie-Wolf, Alexandre / Lee, Chien-Yueh / Qu, Liming / Greenfest-Allen, Emily / Valladares, Otto / Wang, Li-San

NAR genomics and bioinformatics

2022 Volume 4, Issue 1, Page(s) lqab123

Abstract: Querying massive functional genomic and annotation data collections, linking and summarizing the query results across data sources/data types are important steps in high-throughput genomic and genetic analytical workflows. However, these steps are made ... ...

Abstract	Querying massive functional genomic and annotation data collections, linking and summarizing the query results across data sources/data types are important steps in high-throughput genomic and genetic analytical workflows. However, these steps are made difficult by the heterogeneity and breadth of data sources, experimental assays, biological conditions/tissues/cell types and file formats. FILER (FunctIonaL gEnomics Repository) is a framework for querying large-scale genomics knowledge with a large, curated integrated catalog of harmonized functional genomic and annotation data coupled with a scalable genomic search and querying interface. FILER uniquely provides: (i) streamlined access to >50 000 harmonized, annotated genomic datasets across >20 integrated data sources, >1100 tissues/cell types and >20 experimental assays; (ii) a scalable genomic querying interface; and (iii) ability to analyze and annotate user's experimental data. This rich resource spans >17 billion GRCh37/hg19 and GRCh38/hg38 genomic records. Our benchmark querying 7 × 10
Language	English
Publishing date	2022-01-14
Publishing country	England
Document type	Journal Article
ISSN	2631-9268
ISSN (online)	2631-9268
DOI	10.1093/nargab/lqab123
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Article ; Online: HIPPIE2: a method for fine-scale identification of physically interacting chromatin regions.

Kuksa, Pavel P / Amlie-Wolf, Alexandre / Hwang, Yih-Chii / Valladares, Otto / Gregory, Brian D / Wang, Li-San

NAR genomics and bioinformatics

2020 Volume 2, Issue 2, Page(s) lqaa022

Abstract: Most regulatory chromatin interactions are mediated by various transcription factors (TFs) and involve physically interacting elements such as enhancers, insulators or promoters. To map these elements and interactions at a fine scale, we developed ... ...

Abstract	Most regulatory chromatin interactions are mediated by various transcription factors (TFs) and involve physically interacting elements such as enhancers, insulators or promoters. To map these elements and interactions at a fine scale, we developed HIPPIE2 that analyzes raw reads from high-throughput chromosome conformation (Hi-C) experiments to identify precise loci of DNA physically interacting regions (PIRs). Unlike standard genome binning approaches (e.g. 10-kb to 1-Mb bins), HIPPIE2 dynamically infers the physical locations of PIRs using the distribution of restriction sites to increase analysis precision and resolution. We applied HIPPIE2 to
Language	English
Publishing date	2020-03-31
Publishing country	England
Document type	Journal Article
ISSN	2631-9268
ISSN (online)	2631-9268
DOI	10.1093/nargab/lqaa022
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Article ; Online: DASHR 2.0: integrated database of human small non-coding RNA genes and mature products

Kuksa, Pavel P. / Amlie-Wolf, Alexandre / Katanić, Živadin / Valladares, Otto / Wang, Lisan / Leung, Yuk Yee

Bioinformatics. 2019 Mar. 15, v. 35, no. 6, p. 1033-1039

2019 , Page(s) 1033–1039

Abstract: Small non-coding RNAs (sncRNAs, <100 nts) are highly abundant RNAs that regulate diverse and often tissue-specific cellular processes by associating with transcription factor complexes or binding to mRNAs. While thousands of sncRNA genes exist in the ... ...

Abstract	Small non-coding RNAs (sncRNAs, <100 nts) are highly abundant RNAs that regulate diverse and often tissue-specific cellular processes by associating with transcription factor complexes or binding to mRNAs. While thousands of sncRNA genes exist in the human genome, no single resource provides searchable, unified annotation, expression and processing information for full sncRNA transcripts and mature RNA products derived from these larger RNAs. Our goal is to establish a complete catalog of annotation, expression, processing, conservation, tissue-specificity and other biological features for all human sncRNA genes and mature products derived from all major RNA classes. DASHR (Database of small human non-coding RNAs) v2.0 database is the first that integrates human sncRNA gene and mature products profiles obtained from multiple RNA-seq protocols. Altogether, 185 tissues/cell types and sncRNA annotations and >800 curated experiments from ENCODE and GEO/SRA across multiple RNA-seq protocols for both GRCh38/hg38 and GRCh37/hg19 assemblies are integrated in DASHR. Moreover, DASHR is the first to contain both known and novel, previously un-annotated sncRNA loci identified by unsupervised segmentation (13 times more loci with 1 678 800 total). Additionally, DASHR v2.0 adds >3 200 000 annotations for non-small RNA genes and other genomic features (long-noncoding RNAs, mRNAs, promoters, repeats). Furthermore, DASHR v2.0 introduces an enhanced user interface, interactive experiment-by-locus table view, sncRNA locus sorting and filtering by biological features. All annotation and expression information directly downloadable and accessible as UCSC genome browser tracks. DASHR v2.0 is freely available at https://lisanwanglab.org/DASHRv2. Supplementary data are available at Bioinformatics online.
Keywords	bioinformatics ; databases ; genes ; genomics ; humans ; loci ; non-coding RNA ; sequence analysis ; transcription factors ; user interface
Language	English
Dates of publication	2019-0315
Size	p. 1033-1039
Publishing place	Oxford University Press
Document type	Article ; Online
Note	Use and reproduction
ZDB-ID	1468345-3
ISSN	1367-4811 ; 1460-2059
ISSN	1367-4811 ; 1460-2059
DOI	10.1093/bioinformatics/bty709
Database	NAL-Catalogue (AGRICOLA)

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Article ; Online: Genetically regulated expression in late-onset Alzheimer's disease implicates risk genes within known and novel loci.

Chen, Hung-Hsin / Petty, Lauren E / Sha, Jin / Zhao, Yi / Kuzma, Amanda / Valladares, Otto / Bush, William / Naj, Adam C / Gamazon, Eric R / Below, Jennifer E

Translational psychiatry

2021 Volume 11, Issue 1, Page(s) 618

Abstract: Late-onset Alzheimer disease (LOAD) is highly polygenic, with a heritability estimated between 40 and 80%, yet risk variants identified in genome-wide studies explain only ~8% of phenotypic variance. Due to its increased power and interpretability, ... ...

Abstract	Late-onset Alzheimer disease (LOAD) is highly polygenic, with a heritability estimated between 40 and 80%, yet risk variants identified in genome-wide studies explain only ~8% of phenotypic variance. Due to its increased power and interpretability, genetically regulated expression (GReX) analysis is an emerging approach to investigate the genetic mechanisms of complex diseases. Here, we conducted GReX analysis within and across 51 tissues on 39 LOAD GWAS data sets comprising 58,713 cases and controls from the Alzheimer's Disease Genetics Consortium (ADGC) and the International Genomics of Alzheimer's Project (IGAP). Meta-analysis across studies identified 216 unique significant genes, including 72 with no previously reported LOAD GWAS associations. Cross-brain-tissue and cross-GTEx models revealed eight additional genes significantly associated with LOAD. Conditional analysis of previously reported loci using established LOAD-risk variants identified eight genes reaching genome-wide significance independent of known signals. Moreover, the proportion of SNP-based heritability is highly enriched in genes identified by GReX analysis. In summary, GReX-based meta-analysis in LOAD identifies 216 genes (including 72 novel genes), illuminating the role of gene regulatory models in LOAD.
MeSH term(s)	Alzheimer Disease/genetics ; Genetic Predisposition to Disease ; Genome-Wide Association Study ; Humans ; Multifactorial Inheritance ; Polymorphism, Single Nucleotide
Language	English
Publishing date	2021-12-06
Publishing country	United States
Document type	Journal Article ; Meta-Analysis ; Research Support, N.I.H., Extramural
ZDB-ID	2609311-X
ISSN	2158-3188 ; 2158-3188
ISSN (online)	2158-3188
ISSN	2158-3188
DOI	10.1038/s41398-021-01677-0
Database	MEDical Literature Analysis and Retrieval System OnLINE

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Article: Copy Number Variation Identification on 3,800 Alzheimer's Disease Whole Genome Sequencing Data from the Alzheimer's Disease Sequencing Project.

Lee, Wan-Ping / Tucci, Albert A / Conery, Mitchell / Leung, Yuk Yee / Kuzma, Amanda B / Valladares, Otto / Chou, Yi-Fan / Lu, Wenbin / Wang, Li-San / Schellenberg, Gerard D / Tzeng, Jung-Ying

Frontiers in genetics

2021 Volume 12, Page(s) 752390

Abstract: Alzheimer's Disease (AD) is a progressive neurologic disease and the most common form of dementia. While the causes of AD are not completely understood, genetics plays a key role in the etiology of AD, and thus finding genetic factors holds the potential ...

Abstract	Alzheimer's Disease (AD) is a progressive neurologic disease and the most common form of dementia. While the causes of AD are not completely understood, genetics plays a key role in the etiology of AD, and thus finding genetic factors holds the potential to uncover novel AD mechanisms. For this study, we focus on copy number variation (CNV) detection and burden analysis. Leveraging whole-genome sequence (WGS) data released by Alzheimer's Disease Sequencing Project (ADSP), we developed a scalable bioinformatics pipeline to identify CNVs. This pipeline was applied to 1,737 AD cases and 2,063 cognitively normal controls. As a result, we observed 237,306 and 42,767 deletions and duplications, respectively, with an average of 2,255 deletions and 1,820 duplications per subject. The burden tests show that Non-Hispanic-White cases on average have 16 more duplications than controls do (
Language	English
Publishing date	2021-11-04
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2606823-0
ISSN	1664-8021
ISSN	1664-8021
DOI	10.3389/fgene.2021.752390
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Article ; Online: Alzheimer's Disease Variant Portal: A Catalog of Genetic Findings for Alzheimer's Disease.

Kuksa, Pavel P / Liu, Chia-Lun / Fu, Wei / Qu, Liming / Zhao, Yi / Katanic, Zivadin / Clark, Kaylyn / Kuzma, Amanda B / Ho, Pei-Chuan / Tzeng, Kai-Teh / Valladares, Otto / Chou, Shin-Yi / Naj, Adam C / Schellenberg, Gerard D / Wang, Li-San / Leung, Yuk Yee

Journal of Alzheimer's disease : JAD

2022 Volume 86, Issue 1, Page(s) 461–477

Abstract: Background: Recent Alzheimer's disease (AD) genetics findings from genome-wide association studies (GWAS) span progressively larger and more diverse populations and outcomes. Currently, there is no up-to-date resource providing harmonized and searchable ...

Abstract	Background: Recent Alzheimer's disease (AD) genetics findings from genome-wide association studies (GWAS) span progressively larger and more diverse populations and outcomes. Currently, there is no up-to-date resource providing harmonized and searchable information on all AD genetic associations found by GWAS, nor linking the reported genetic variants and genes with functional and genomic annotations. Objective: Create an integrated/harmonized, and literature-derived collection of population-specific AD genetic associations. Methods: We developed the Alzheimer's Disease Variant Portal (ADVP), an extensive collection of associations curated from >200 GWAS publications from Alzheimer's Disease Genetics Consortium and other consortia. Genetic associations were systematically extracted, harmonized, and annotated from both the genome-wide significant and suggestive loci reported in these publications. To ensure consistent representation of AD genetic findings, all the extracted genetic association information was harmonized across specifically designed publication, variant, and association categories. Results: ADVP V1.0 (February 2021) catalogs 6,990 associations related to disease-risk, expression quantitative traits, endophenotypes, or neuropathology. This extensive harmonization effort led to a catalog containing >900 loci, >1,800 variants, >80 cohorts, and 8 populations. Besides, ADVP provides investigators with a seamless integration of genomic and publicly available functional annotations across multiple databases per harmonized variant and gene records, thus facilitating further understanding and analyses of these genetics findings. Conclusion: ADVP is a valuable resource for investigators to quickly and systematically explore high-confidence AD genetic findings and provides insights into population-specific AD genetic architecture. ADVP is continually maintained and enhanced by NIAGADS and is freely accessible at https://advp.niagads.org.
MeSH term(s)	Alzheimer Disease/genetics ; Endophenotypes ; Genetic Predisposition to Disease/genetics ; Genome-Wide Association Study ; Humans ; Polymorphism, Single Nucleotide
Language	English
Publishing date	2022-01-07
Publishing country	Netherlands
Document type	Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
ZDB-ID	1440127-7
ISSN	1875-8908 ; 1387-2877
ISSN (online)	1875-8908
ISSN	1387-2877
DOI	10.3233/JAD-215055
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