IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v13y2022i1d10.1038_s41467-022-32205-3.html
   My bibliography  Save this article

Connecting omics signatures and revealing biological mechanisms with iLINCS

Author

Listed:
  • Marcin Pilarczyk

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Mehdi Fazel-Najafabadi

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Michal Kouril

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    Cincinnati Children’s Hospital Medical Center)

  • Behrouz Shamsaei

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Juozas Vasiliauskas

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Wen Niu

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Naim Mahi

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Lixia Zhang

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Nicholas A. Clark

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Yan Ren

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Shana White

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Rashid Karim

    (University of Cincinnati
    University of Cincinnati)

  • Huan Xu

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Jacek Biesiada

    (University of Cincinnati)

  • Mark F. Bennett

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Sarah E. Davidson

    (University of Cincinnati)

  • John F. Reichard

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Kurt Roberts

    (University of Cincinnati)

  • Vasileios Stathias

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    University of Miami)

  • Amar Koleti

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    University of Miami)

  • Dusica Vidovic

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    University of Miami)

  • Daniel J. B. Clarke

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    Icahn School of Medicine at Mount Sinai)

  • Stephan C. Schürer

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    University of Miami)

  • Avi Ma’ayan

    (LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    Icahn School of Medicine at Mount Sinai)

  • Jarek Meller

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

  • Mario Medvedovic

    (University of Cincinnati
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC)
    LINCS Data Coordination and Integration Center (DCIC))

Abstract

There are only a few platforms that integrate multiple omics data types, bioinformatics tools, and interfaces for integrative analyses and visualization that do not require programming skills. Here we present iLINCS ( http://ilincs.org ), an integrative web-based platform for analysis of omics data and signatures of cellular perturbations. The platform facilitates mining and re-analysis of the large collection of omics datasets (>34,000), pre-computed signatures (>200,000), and their connections, as well as the analysis of user-submitted omics signatures of diseases and cellular perturbations. iLINCS analysis workflows integrate vast omics data resources and a range of analytics and interactive visualization tools into a comprehensive platform for analysis of omics signatures. iLINCS user-friendly interfaces enable execution of sophisticated analyses of omics signatures, mechanism of action analysis, and signature-driven drug repositioning. We illustrate the utility of iLINCS with three use cases involving analysis of cancer proteogenomic signatures, COVID 19 transcriptomic signatures and mTOR signaling.

Suggested Citation

  • Marcin Pilarczyk & Mehdi Fazel-Najafabadi & Michal Kouril & Behrouz Shamsaei & Juozas Vasiliauskas & Wen Niu & Naim Mahi & Lixia Zhang & Nicholas A. Clark & Yan Ren & Shana White & Rashid Karim & Huan, 2022. "Connecting omics signatures and revealing biological mechanisms with iLINCS," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
  • Handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32205-3
    DOI: 10.1038/s41467-022-32205-3
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-022-32205-3
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-022-32205-3?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Patrick Wu & QiPing Feng & Vern Eric Kerchberger & Scott D. Nelson & Qingxia Chen & Bingshan Li & Todd L. Edwards & Nancy J. Cox & Elizabeth J. Phillips & C. Michael Stein & Dan M. Roden & Joshua C. D, 2022. "Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    2. Jing Chen & Zhen Hu & Mukta Phatak & John Reichard & Johannes M Freudenberg & Siva Sivaganesan & Mario Medvedovic, 2013. "Genome-Wide Signatures of Transcription Factor Activity: Connecting Transcription Factors, Disease, and Small Molecules," PLOS Computational Biology, Public Library of Science, vol. 9(9), pages 1-12, September.
    3. David E. Harrison & Randy Strong & Zelton Dave Sharp & James F. Nelson & Clinton M. Astle & Kevin Flurkey & Nancy L. Nadon & J. Erby Wilkinson & Krystyna Frenkel & Christy S. Carter & Marco Pahor & Ma, 2009. "Rapamycin fed late in life extends lifespan in genetically heterogeneous mice," Nature, Nature, vol. 460(7253), pages 392-395, July.
    4. Zichen Wang & Caroline D. Monteiro & Kathleen M. Jagodnik & Nicolas F. Fernandez & Gregory W. Gundersen & Andrew D. Rouillard & Sherry L. Jenkins & Axel S. Feldmann & Kevin S. Hu & Michael G. McDermot, 2016. "Extraction and analysis of signatures from the Gene Expression Omnibus by the crowd," Nature Communications, Nature, vol. 7(1), pages 1-11, November.
    5. Erin C. Bush & Forest Ray & Mariano J. Alvarez & Ronald Realubit & Hai Li & Charles Karan & Andrea Califano & Peter A. Sims, 2017. "PLATE-Seq for genome-wide regulatory network analysis of high-throughput screens," Nature Communications, Nature, vol. 8(1), pages 1-7, December.
    6. Charles M. Perou & Therese Sørlie & Michael B. Eisen & Matt van de Rijn & Stefanie S. Jeffrey & Christian A. Rees & Jonathan R. Pollack & Douglas T. Ross & Hilde Johnsen & Lars A. Akslen & Øystein Flu, 2000. "Molecular portraits of human breast tumours," Nature, Nature, vol. 406(6797), pages 747-752, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Matteo Marchesini & Andrea Gherli & Elisa Simoncini & Lucas Moron Dalla Tor & Anna Montanaro & Natthakan Thongon & Federica Vento & Chiara Liverani & Elisa Cerretani & Anna D’Antuono & Luca Pagliaro &, 2024. "Orthogonal proteogenomic analysis identifies the druggable PA2G4-MYC axis in 3q26 AML," Nature Communications, Nature, vol. 15(1), pages 1-22, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yang, Xi & Hoadley, Katherine A. & Hannig, Jan & Marron, J.S., 2023. "Jackstraw inference for AJIVE data integration," Computational Statistics & Data Analysis, Elsevier, vol. 180(C).
    2. Manish G & Anil Kumar Badana & Rama Rao Malla, 2017. "Emerging Diagnostic and Prognostic Biomarkers of Triple Negative Breast Cancer," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 1(3), pages 561-565, August.
    3. Jacob Elnaggar & Fern Tsien & Lucio Miele & Chindo Hicks & Clayton Yates & Melisa Davis, 2019. "An Integrative Genomics Approach for Associating Genetic Susceptibility with the Tumor Immune Microenvironment in Triple Negative Breast Cancer," Biomedical Journal of Scientific & Technical Research, Biomedical Research Network+, LLC, vol. 15(1), pages 1-12, February.
    4. Egashira, Kento & Yata, Kazuyoshi & Aoshima, Makoto, 2024. "Asymptotic properties of hierarchical clustering in high-dimensional settings," Journal of Multivariate Analysis, Elsevier, vol. 199(C).
    5. María Elena Martínez & Jonathan T Unkart & Li Tao & Candyce H Kroenke & Richard Schwab & Ian Komenaka & Scarlett Lin Gomez, 2017. "Prognostic significance of marital status in breast cancer survival: A population-based study," PLOS ONE, Public Library of Science, vol. 12(5), pages 1-14, May.
    6. Yishai Shimoni, 2018. "Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub-classification," PLOS Computational Biology, Public Library of Science, vol. 14(2), pages 1-15, February.
    7. Junhee Seok & Ronald W Davis & Wenzhong Xiao, 2015. "A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data," PLOS ONE, Public Library of Science, vol. 10(5), pages 1-15, May.
    8. Qing Qu & Yan Mao & Xiao-chun Fei & Kun-wei Shen, 2013. "The Impact of Androgen Receptor Expression on Breast Cancer Survival: A Retrospective Study and Meta-Analysis," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-1, December.
    9. Bourret, Pascale & Keating, Peter & Cambrosio, Alberto, 2011. "Regulating diagnosis in post-genomic medicine: Re-aligning clinical judgment?," Social Science & Medicine, Elsevier, vol. 73(6), pages 816-824, September.
    10. G. Gambardella & G. Viscido & B. Tumaini & A. Isacchi & R. Bosotti & D. di Bernardo, 2022. "A single-cell analysis of breast cancer cell lines to study tumour heterogeneity and drug response," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    11. Yoo-Ah Kim & Stefan Wuchty & Teresa M Przytycka, 2011. "Identifying Causal Genes and Dysregulated Pathways in Complex Diseases," PLOS Computational Biology, Public Library of Science, vol. 7(3), pages 1-13, March.
    12. Daniel J. Ham & Anastasiya Börsch & Kathrin Chojnowska & Shuo Lin & Aurel B. Leuchtmann & Alexander S. Ham & Marco Thürkauf & Julien Delezie & Regula Furrer & Dominik Burri & Michael Sinnreich & Chris, 2022. "Distinct and additive effects of calorie restriction and rapamycin in aging skeletal muscle," Nature Communications, Nature, vol. 13(1), pages 1-20, December.
    13. Pauliina M. Munne & Lahja Martikainen & Iiris Räty & Kia Bertula & Nonappa & Janika Ruuska & Hanna Ala-Hongisto & Aino Peura & Babette Hollmann & Lilya Euro & Kerim Yavuz & Linda Patrikainen & Maria S, 2021. "Compressive stress-mediated p38 activation required for ERα + phenotype in breast cancer," Nature Communications, Nature, vol. 12(1), pages 1-17, December.
    14. Radhakrishnan Nagarajan & Marco Scutari, 2013. "Impact of Noise on Molecular Network Inference," PLOS ONE, Public Library of Science, vol. 8(12), pages 1-12, December.
    15. R Joseph Bender & Feilim Mac Gabhann, 2013. "Expression of VEGF and Semaphorin Genes Define Subgroups of Triple Negative Breast Cancer," PLOS ONE, Public Library of Science, vol. 8(5), pages 1-15, May.
    16. Marron, J.S., 2017. "Big Data in context and robustness against heterogeneity," Econometrics and Statistics, Elsevier, vol. 2(C), pages 73-80.
    17. Deepak Poduval & Zuzana Sichmanova & Anne Hege Straume & Per Eystein Lønning & Stian Knappskog, 2020. "The novel microRNAs hsa-miR-nov7 and hsa-miR-nov3 are over-expressed in locally advanced breast cancer," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-23, April.
    18. Mariana Segovia-Mendoza & Margarita Isabel Palacios-Arreola & Luz María Monroy-Escamilla & Alexandra Estela Soto-Piña & Karen Elizabeth Nava-Castro & Yizel Becerril-Alarcón & Roberto Camacho-Beiza & D, 2022. "Association of Serum Levels of Plasticizers Compounds, Phthalates and Bisphenols, in Patients and Survivors of Breast Cancer: A Real Connection?," IJERPH, MDPI, vol. 19(13), pages 1-22, June.
    19. L. Mathur & B. Szalai & N. H. Du & R. Utharala & M. Ballinger & J. J. M. Landry & M. Ryckelynck & V. Benes & J. Saez-Rodriguez & C. A. Merten, 2022. "Combi-seq for multiplexed transcriptome-based profiling of drug combinations using deterministic barcoding in single-cell droplets," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    20. Chi-Cheng Huang & Shih-Hsin Tu & Heng-Hui Lien & Jaan-Yeh Jeng & Ching-Shui Huang & Chi-Jung Huang & Liang-Chuan Lai & Eric Y Chuang, 2013. "Concurrent Gene Signatures for Han Chinese Breast Cancers," PLOS ONE, Public Library of Science, vol. 8(10), pages 1-1, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:13:y:2022:i:1:d:10.1038_s41467-022-32205-3. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.