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Multi-omics Data Integration, Interpretation, and Its Application

Indhupriya Subramanian, Srikant Verma, Shiva Kumar, Abhay Jere, Krishanpal Anamika
2020 Bioinformatics and Biology Insights  
We provide the methodology, use-cases, and limitations of these tools; brief account of multi-omics data repositories and visualization portals; and challenges associated with multi-omics data integration  ...  With the advent of high-throughput techniques and availability of multi-omics data generated from a large set of samples, several promising tools and methods have been developed for data integration and  ...  Priyabrata Panigrahi for initial discussion and participation in the selection of tools and methods. Authors would also like to thank Pratap Sanap for his input on tools categorization.  ... 
doi:10.1177/1177932219899051 pmid:32076369 pmcid:PMC7003173 fatcat:dchnmbmzh5di7jcuc7ilxjsk3e

Computational strategies for single-cell multi-omics integration

Nigatu Adossa, Sofia Khan, Kalle T Rytkönen, Laura L Elo
2021 Computational and Structural Biotechnology Journal  
Current advances especially in single-cell multi-omics hold high potential for breakthroughs by integration of multiple different omics layers.  ...  Finally, we explore the challenges and prospective future directions of single-cell multi-omics data integration, including examples of adopting multi-view analysis approaches used in other disciplines  ...  Additionally, the current multimodal analysis tools mostly focus on integrative clustering of multi-omics data with the aim to identify the shared cell type heterogeneity.  ... 
doi:10.1016/j.csbj.2021.04.060 pmid:34025945 pmcid:PMC8114078 fatcat:qap257yttzdetjrqs4aijcwaq4

Next Generation Sequencing in Cancer Research and Clinical Application [chapter]

Derek Shyr, Qi Liu
2014 Omics in Clinical Practice  
The wide application of next-generation sequencing (NGS), mainly through whole genome, exome and transcriptome sequencing, provides a high-resolution and global view of the cancer genome.  ...  clinical application, summarize the current integrative oncogenomic projects, resources and computational algorithms, and discuss the challenge and future directions in the research and clinical application of  ...  Acknowledgements This work was supported by National Cancer Institute grants U01 CA163056, P30 CA068485, P50 CA098131, and P50 CA090949 and QL's work was partially supported by the State Key Program of  ... 
doi:10.1201/b17137-5 fatcat:2nl2wlqsr5h6vo7urlernmn44u

Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis

Otília Menyhárt, Balázs Győrffy
2021 Computational and Structural Biotechnology Journal  
Progressive initiatives to enforce the standardization of sample processing and analytical pipelines, multidisciplinary training of experts for data analysis and interpretation are vital to facilitate  ...  One major obstacle is the uneven maturity of different omics approaches and the growing gap between generating large volumes of data compared to data processing capacity.  ...  Acknowledgements The authors wish to acknowledge the support of ELIXIR Hungary (www.elixir-hungary.org).  ... 
doi:10.1016/j.csbj.2021.01.009 pmid:33613862 pmcid:PMC7868685 fatcat:u7l3qybr5rhr5mcvj2o4q72zue

Multi-Omics Model Applied to Cancer Genetics

Francesco Pettini, Anna Visibelli, Vittoria Cicaloni, Daniele Iovinelli, Ottavia Spiga
2021 International Journal of Molecular Sciences  
heterogenicity of the backgrounds of people approaching precision medicine.  ...  We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field.  ...  data analysis by improving data science applications of multiple omics datasets: • The MultiAssayExperiment Bioconductor database [95] contains the information of different multi-omics experiments  ... 
doi:10.3390/ijms22115751 pmid:34072237 fatcat:xo4fgxhu5faupcvs4oi3yvbywy

Multiview learning for understanding functional multiomics

Nam D Nguyen, Daifeng Wang
2020 PLoS Computational Biology  
omics.  ...  In particular, multiview learning is more effective than previous integrative methods for learning data's heterogeneity and revealing cross-talk patterns.  ...  These cross-talk patterns are contributed by each facet of learning in either alignment-based methods or factorization-based methods.  ... 
doi:10.1371/journal.pcbi.1007677 pmid:32240163 pmcid:PMC7117667 fatcat:jqpizdutnrgtnlymfmjhh4qo4q

Computational Oncology in the Multi-Omics Era: State of the Art

Guillermo de Anda-Jáuregui, Enrique Hernández-Lemus
2020 Frontiers in Oncology  
We will discuss the current roles of computation in oncology in the context of multi-omic technologies, which include: data acquisition and processing; data management in the clinical and research settings  ...  In this multi-omics context, the use of integrative approaches is mandatory in order to gain further insights on oncological phenomena, and to move forward toward the precision medicine paradigm.  ...  Tumor heterogeneity caused by the concurrence of multiple cell lineages and differentiation stages, determined to an extent by the processes of clonal evolution.  ... 
doi:10.3389/fonc.2020.00423 pmid:32318338 pmcid:PMC7154096 fatcat:lrlg3yyo2ffkdaz2whv2egyklq

High-Order Correlation Integration for Single-Cell or Bulk RNA-seq Data Analysis

Hui Tang, Tao Zeng, Luonan Chen
2019 Frontiers in Genetics  
Here we propose an effective data integration framework named as HCI (High-order Correlation Integration), which takes an advantage of high-order correlation matrix incorporated with pattern fusion analysis  ...  On the other hand, the PFA can identify intrinsic sample patterns efficiently from different input matrices by optimally adjusting the signal effects.  ...  We integrated these three input datasets by pattern fusion analysis.  ... 
doi:10.3389/fgene.2019.00371 pmid:31080457 pmcid:PMC6497731 fatcat:ahnuiyumjfby5igrnvkebwnde4

Experimental and Bioinformatic Approaches to Studying DNA Methylation in Cancer

Angelika Merkel, Manel Esteller
2022 Cancers  
Second, we focus on the computational analysis from primary data processing to the identification of unique methylation signatures.  ...  Additionally, we discuss challenges such as sparse data and cellular heterogeneity.  ...  Recent statistical approaches for integrative multi-omics analysis (including similarity-and correlation-based, Bayesian, fusion and other multi-variate methods) have greatly improved subtyping of cancers  ... 
doi:10.3390/cancers14020349 pmid:35053511 pmcid:PMC8773752 fatcat:5tcxmri2anbrrhwthe3kobrd2q

Next generation sequencing in cancer research and clinical application

Derek Shyr, Qi Liu
2013 Biological Procedures Online  
The wide application of next-generation sequencing (NGS), mainly through whole genome, exome and transcriptome sequencing, provides a high-resolution and global view of the cancer genome.  ...  clinical application, summarize the current integrative oncogenomic projects, resources and computational algorithms, and discuss the challenge and future directions in the research and clinical application of  ...  Acknowledgements This work was supported by National Cancer Institute grants U01 CA163056, P30 CA068485, P50 CA098131, and P50 CA090949 and QL's work was partially supported by the State Key Program of  ... 
doi:10.1186/1480-9222-15-4 pmid:23406336 pmcid:PMC3599179 fatcat:7qnr22ut6netlfe332wirmj35i

Integration of Online Omics-Data Resources for Cancer Research

Tonmoy Das, Geoffroy Andrieux, Musaddeque Ahmed, Sajib Chakraborty
2020 Frontiers in Genetics  
To understand the underlying mechanisms that drive the acquisition of cancer hallmarks it is required to interrogate cancer cells using multiple levels of information flow represented by different omics  ...  We catalog various online omics-data resources such as The Cancer Genome Atlas (TCGA) along with various TCGA-associated data portals and tools for multi-omics analysis and visualization, the International  ...  Pattern Fusion Analysis (PFA) The PFA framework established by Shi et al. can perform information-alignment and bias correction for the fusion local sample-patterns originating from each dataset into a  ... 
doi:10.3389/fgene.2020.578345 pmid:33193699 pmcid:PMC7645150 fatcat:adq25boimjbkjgrrdpdwgtmfma

Metabolomics technology and bioinformatics for precision medicine

2018 Briefings in Bioinformatics  
We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of  ...  Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment  ...  The research in the authors' laboratories is financially supported by the grant from NIH NIAID (grant number 5R01AI111962-02) and NIH NIDDK (grant number DK109524-01).  ... 
doi:10.1093/bib/bbx170 pmid:29304189 pmcid:PMC6954408 fatcat:g3uufpuepnfdxo7fzv2cuq5rgu

OncoRep: an n-of-1 reporting tool to support genome-guided treatment for breast cancer patients using RNA-sequencing

Tobias Meißner, Kathleen M Fisch, Louis Gioia, Andrew I Su
2015 BMC Medical Genomics  
Challenges that arise are i) preprocessing and analyzing RNA-Seq data in the n-of-1 setting, ii) extracting clinically relevant and actionable targets from complex data, iii) integrating drug databases  ...  CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder.  ...  It is a heterogenous disease comprising multiple tumor entities associated with distinctive histological patterns, different biological features and clinical behaviors 2, 3 .  ... 
doi:10.1186/s12920-015-0095-z pmid:25989980 pmcid:PMC4494802 fatcat:5utdleckkrejzbbm2kjfn56ifq

Single-cell multi-omics sequencing: application trends, COVID-19, data analysis issues and prospects

Lu Huo, Jiao Jiao Li, Ling Chen, Zuguo Yu, Gyorgy Hutvagner, Jinyan Li
2021 Briefings in Bioinformatics  
We also summarize machine learning and bioinformatics techniques used in the analysis of the intercorrelated multilayer heterogeneous data.  ...  Increasing in complexity, single-cell multi-omics sequencing, or single-cell multimodal omics sequencing, is to profile in parallel multiple layers of omics information from a single cell.  ...  Thus, single-cell multi-omics sequencing and the integration of diverse modalities from single-cell datasets face the challenge of data fusion.  ... 
doi:10.1093/bib/bbab229 pmid:34111889 pmcid:PMC8344433 fatcat:n5wva7mjqzfsldiahwzn2cun5e

Omics-Based Strategies in Precision Medicine: Toward a Paradigm Shift in Inborn Errors of Metabolism Investigations

Abdellah Tebani, Carlos Afonso, Stéphane Marret, Soumeya Bekri
2016 International Journal of Molecular Sciences  
In this review, we present state-of-the-art multi-omics data analysis strategies in a clinical context. The challenges of omics-based biomarker translation are discussed.  ...  Driven by high-throughput omics technologies and the computational surge, it enables multi-scale and insightful overviews of cells, organisms, and populations.  ...  Acknowledgments: This work was supported by Normandy University, the Institut National de la Santé et de la Recherche Médicale (INSERM), the Conseil Régional de Normandie, Labex SynOrg (ANR-11-LABX-0029  ... 
doi:10.3390/ijms17091555 pmid:27649151 pmcid:PMC5037827 fatcat:426cvphidjgd3mtta76lcdoj7q
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