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  1. AU="Schadt, Eric E"
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  1. Article ; Online: Anti-correlated feature selection prevents false discovery of subpopulations in scRNAseq.

    Tyler, Scott R / Lozano-Ojalvo, Daniel / Guccione, Ernesto / Schadt, Eric E

    Nature communications

    2024  Volume 15, Issue 1, Page(s) 699

    Abstract: While sub-clustering cell-populations has become popular in single cell-omics, negative controls for this process are lacking. Popular feature-selection/clustering algorithms fail the null-dataset problem, allowing erroneous subdivisions of homogenous ... ...

    Abstract While sub-clustering cell-populations has become popular in single cell-omics, negative controls for this process are lacking. Popular feature-selection/clustering algorithms fail the null-dataset problem, allowing erroneous subdivisions of homogenous clusters until nearly each cell is called its own cluster. Using real and synthetic datasets, we find that anti-correlated gene selection reduces or eliminates erroneous subdivisions, increases marker-gene selection efficacy, and efficiently scales to millions of cells.
    MeSH term(s) Single-Cell Gene Expression Analysis ; Algorithms ; Cluster Analysis
    Language English
    Publishing date 2024-01-24
    Publishing country England
    Document type Journal Article
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-43406-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Editorial: Streaming inflammation: From damage to healing and resilience-Volume II.

    Devchand, Pallavi R / Schadt, Eric E / FitzGerald, Garret A

    Frontiers in pharmacology

    2023  Volume 14, Page(s) 1185593

    Language English
    Publishing date 2023-03-24
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2587355-6
    ISSN 1663-9812
    ISSN 1663-9812
    DOI 10.3389/fphar.2023.1185593
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Editorial: Streaming Inflammation: From Damage to Healing and Resilience.

    Devchand, Pallavi R / Schadt, Eric E / FitzGerald, Garret A

    Frontiers in pharmacology

    2022  Volume 13, Page(s) 969453

    Language English
    Publishing date 2022-07-12
    Publishing country Switzerland
    Document type Editorial
    ZDB-ID 2587355-6
    ISSN 1663-9812
    ISSN 1663-9812
    DOI 10.3389/fphar.2022.969453
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Traversing industry and academia in biomedicine: the best of both worlds?

    Gilliland, D Gary / Regev, Aviv / Schadt, Eric E / Tung, Joyce

    Nature reviews. Genetics

    2022  Volume 23, Issue 8, Page(s) 461–466

    Abstract: Careers in biomedicine can take many forms, and one common career decision facing scientists is whether to pursue jobs in academia or industry. In this Viewpoint article, four leading scientists who have spent time in both academia and industry provide ... ...

    Abstract Careers in biomedicine can take many forms, and one common career decision facing scientists is whether to pursue jobs in academia or industry. In this Viewpoint article, four leading scientists who have spent time in both academia and industry provide their perspectives on both types of workplace, such as whether the environments are really as distinct as they are often perceived to be, as well as how academia-industry collaborations can be a driving force in biomedical research and translation.
    MeSH term(s) Biomedical Research ; Industry
    Language English
    Publishing date 2022-05-09
    Publishing country England
    Document type Journal Article
    ZDB-ID 2035157-4
    ISSN 1471-0064 ; 1471-0056
    ISSN (online) 1471-0064
    ISSN 1471-0056
    DOI 10.1038/s41576-022-00486-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5474: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (2.OG)
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  5. Article ; Online: Detecting and phasing minor single-nucleotide variants from long-read sequencing data.

    Feng, Zhixing / Clemente, Jose C / Wong, Brandon / Schadt, Eric E

    Nature communications

    2021  Volume 12, Issue 1, Page(s) 3032

    Abstract: Cellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, and co-infection of multiple pathogens. Detecting and phasing minor variants play an instrumental role in deciphering cellular genetic heterogeneity, but ...

    Abstract Cellular genetic heterogeneity is common in many biological conditions including cancer, microbiome, and co-infection of multiple pathogens. Detecting and phasing minor variants play an instrumental role in deciphering cellular genetic heterogeneity, but they are still difficult tasks because of technological limitations. Recently, long-read sequencing technologies, including those by Pacific Biosciences and Oxford Nanopore, provide an opportunity to tackle these challenges. However, high error rates make it difficult to take full advantage of these technologies. To fill this gap, we introduce iGDA, an open-source tool that can accurately detect and phase minor single-nucleotide variants (SNVs), whose frequencies are as low as 0.2%, from raw long-read sequencing data. We also demonstrate that iGDA can accurately reconstruct haplotypes in closely related strains of the same species (divergence ≥0.011%) from long-read metagenomic data.
    MeSH term(s) Algorithms ; Bacteria ; Borrelia ; Borrelia burgdorferi ; Coinfection/diagnosis ; Computational Biology/methods ; Genome, Human ; Haplotypes ; High-Throughput Nucleotide Sequencing ; Humans ; Metagenome ; Methylation ; Models, Statistical ; Nanopores ; Nucleotides/isolation & purification
    Chemical Substances Nucleotides
    Language English
    Publishing date 2021-05-24
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-021-23289-4
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: The changing privacy landscape in the era of big data.

    Schadt, Eric E

    Molecular systems biology

    2012  Volume 8, Page(s) 612

    MeSH term(s) Databases as Topic ; Humans ; Informed Consent ; Polymorphism, Single Nucleotide/genetics ; Privacy ; Statistics as Topic
    Language English
    Publishing date 2012-09-12
    Publishing country England
    Document type Editorial
    ISSN 1744-4292
    ISSN (online) 1744-4292
    DOI 10.1038/msb.2012.47
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: An algorithm to identify patients aged 0-3 with rare genetic disorders.

    Webb, Bryn D / Lau, Lisa Y / Tsevdos, Despina / Shewcraft, Ryan A / Corrigan, David / Shi, Lisong / Lee, Seungwoo / Tyler, Jonathan / Li, Shilong / Wang, Zichen / Stolovitzky, Gustavo / Edelmann, Lisa / Chen, Rong / Schadt, Eric E / Li, Li

    Orphanet journal of rare diseases

    2024  Volume 19, Issue 1, Page(s) 183

    Abstract: Background: With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, ... ...

    Abstract Background: With over 7000 Mendelian disorders, identifying children with a specific rare genetic disorder diagnosis through structured electronic medical record data is challenging given incompleteness of records, inaccurate medical diagnosis coding, as well as heterogeneity in clinical symptoms and procedures for specific disorders. We sought to develop a digital phenotyping algorithm (PheIndex) using electronic medical records to identify children aged 0-3 diagnosed with genetic disorders or who present with illness with an increased risk for genetic disorders.
    Results: Through expert opinion, we established 13 criteria for the algorithm and derived a score and a classification. The performance of each criterion and the classification were validated by chart review. PheIndex identified 1,088 children out of 93,154 live births who may be at an increased risk for genetic disorders. Chart review demonstrated that the algorithm achieved 90% sensitivity, 97% specificity, and 94% accuracy.
    Conclusions: The PheIndex algorithm can help identify when a rare genetic disorder may be present, alerting providers to consider ordering a diagnostic genetic test and/or referring a patient to a medical geneticist.
    MeSH term(s) Humans ; Algorithms ; Rare Diseases/genetics ; Rare Diseases/diagnosis ; Infant ; Infant, Newborn ; Child, Preschool ; Female ; Male ; Electronic Health Records ; Genetic Diseases, Inborn/diagnosis ; Genetic Diseases, Inborn/genetics ; Phenotype
    Language English
    Publishing date 2024-05-02
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, N.I.H., Extramural
    ZDB-ID 2225857-7
    ISSN 1750-1172 ; 1750-1172
    ISSN (online) 1750-1172
    ISSN 1750-1172
    DOI 10.1186/s13023-024-03188-9
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: variancePartition: interpreting drivers of variation in complex gene expression studies.

    Hoffman, Gabriel E / Schadt, Eric E

    BMC bioinformatics

    2016  Volume 17, Issue 1, Page(s) 483

    Abstract: Background: As large-scale studies of gene expression with multiple sources of biological and technical variation become widely adopted, characterizing these drivers of variation becomes essential to understanding disease biology and regulatory genetics. ...

    Abstract Background: As large-scale studies of gene expression with multiple sources of biological and technical variation become widely adopted, characterizing these drivers of variation becomes essential to understanding disease biology and regulatory genetics.
    Results: We describe a statistical and visualization framework, variancePartition, to prioritize drivers of variation based on a genome-wide summary, and identify genes that deviate from the genome-wide trend. Using a linear mixed model, variancePartition quantifies variation in each expression trait attributable to differences in disease status, sex, cell or tissue type, ancestry, genetic background, experimental stimulus, or technical variables. Analysis of four large-scale transcriptome profiling datasets illustrates that variancePartition recovers striking patterns of biological and technical variation that are reproducible across multiple datasets.
    Conclusions: Our open source software, variancePartition, enables rapid interpretation of complex gene expression studies as well as other high-throughput genomics assays. variancePartition is available from Bioconductor: http://bioconductor.org/packages/variancePartition .
    MeSH term(s) Algorithms ; Computational Biology/methods ; Gene Expression Profiling ; Gene Expression Regulation ; Genetic Variation/genetics ; Genomics/methods ; High-Throughput Nucleotide Sequencing ; Humans ; Linear Models ; Sequence Analysis, RNA/methods ; Software
    Language English
    Publishing date 2016-11-25
    Publishing country England
    Document type Journal Article
    ZDB-ID 2041484-5
    ISSN 1471-2105 ; 1471-2105
    ISSN (online) 1471-2105
    ISSN 1471-2105
    DOI 10.1186/s12859-016-1323-z
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article: Identification of Let-7 miRNA Activity as a Prognostic Biomarker of SHH Medulloblastoma.

    Westphal, Maximillian S / Lee, Eunjee / Schadt, Eric E / Sholler, Giselle S / Zhu, Jun

    Cancers

    2021  Volume 14, Issue 1

    Abstract: Medulloblastoma (MB) is the most common pediatric embryonal brain tumor. The current consensus classifies MB into four molecular subgroups: sonic hedgehog-activated (SHH), wingless-activated (WNT), Group 3, and Group 4. MYCN and let-7 play a critical ... ...

    Abstract Medulloblastoma (MB) is the most common pediatric embryonal brain tumor. The current consensus classifies MB into four molecular subgroups: sonic hedgehog-activated (SHH), wingless-activated (WNT), Group 3, and Group 4. MYCN and let-7 play a critical role in MB. Thus, we inferred the activity of miRNAs in MB by using the ActMiR procedure. SHH-MB has higher MYCN expression than the other subgroups. We showed that high MYCN expression with high let-7 activity is significantly associated with worse overall survival, and this association was validated in an independent MB dataset. Altogether, our results suggest that let-7 activity and MYCN can further categorize heterogeneous SHH tumors into more and less-favorable prognostic subtypes, which provide critical information for personalizing treatment options for SHH-MB. Comparing the expression differences between the two SHH-MB prognostic subtypes with compound perturbation profiles, we identified FGFR inhibitors as one potential treatment option for SHH-MB patients with the less-favorable prognostic subtype.
    Language English
    Publishing date 2021-12-28
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers14010139
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Deciphering bacterial epigenomes using modern sequencing technologies.

    Beaulaurier, John / Schadt, Eric E / Fang, Gang

    Nature reviews. Genetics

    2018  Volume 20, Issue 3, Page(s) 157–172

    Abstract: Prokaryotic DNA contains three types of methylation: N6-methyladenine, N4-methylcytosine and 5-methylcytosine. The lack of tools to analyse the frequency and distribution of methylated residues in bacterial genomes has prevented a full understanding of ... ...

    Abstract Prokaryotic DNA contains three types of methylation: N6-methyladenine, N4-methylcytosine and 5-methylcytosine. The lack of tools to analyse the frequency and distribution of methylated residues in bacterial genomes has prevented a full understanding of their functions. Now, advances in DNA sequencing technology, including single-molecule, real-time sequencing and nanopore-based sequencing, have provided new opportunities for systematic detection of all three forms of methylated DNA at a genome-wide scale and offer unprecedented opportunities for achieving a more complete understanding of bacterial epigenomes. Indeed, as the number of mapped bacterial methylomes approaches 2,000, increasing evidence supports roles for methylation in regulation of gene expression, virulence and pathogen-host interactions.
    MeSH term(s) Bacteria/genetics ; Bacteria/metabolism ; DNA Methylation ; DNA, Bacterial/genetics ; DNA, Bacterial/metabolism ; Genome, Bacterial ; High-Throughput Nucleotide Sequencing/methods ; Sequence Analysis, DNA/methods
    Chemical Substances DNA, Bacterial
    Language English
    Publishing date 2018-12-13
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 2035157-4
    ISSN 1471-0064 ; 1471-0056
    ISSN (online) 1471-0064
    ISSN 1471-0056
    DOI 10.1038/s41576-018-0081-3
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 5474: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)
    Zs.MG 40: Show issues

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