Cargando…

GenomicSuperSignature facilitates interpretation of RNA-seq experiments through robust, efficient comparison to public databases

Millions of transcriptomic profiles have been deposited in public archives, yet remain underused for the interpretation of new experiments. We present a method for interpreting new transcriptomic datasets through instant comparison to public datasets without high-performance computing requirements....

Descripción completa

Detalles Bibliográficos
Autores principales:	Oh, Sehyun, Geistlinger, Ludwig, Ramos, Marcel, Blankenberg, Daniel, van den Beek, Marius, Taroni, Jaclyn N., Carey, Vincent J., Greene, Casey S., Waldron, Levi, Davis, Sean
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2022
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237024/ https://www.ncbi.nlm.nih.gov/pubmed/35760813 http://dx.doi.org/10.1038/s41467-022-31411-3

Ejemplares similares

Reliable Analysis of Clinical Tumor-Only Whole-Exome Sequencing Data
por: Oh, Sehyun, et al.
Publicado: (2020)

RaggedExperiment: the missing link between genomic ranges and matrices in Bioconductor
por: Ramos, Marcel, et al.
Publicado: (2023)

Multiomic Integration of Public Oncology Databases in Bioconductor
por: Ramos, Marcel, et al.
Publicado: (2020)

Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously
por: Foltz, Steven M., et al.
Publicado: (2023)

Seq2Ref: a web server to facilitate functional interpretation
por: Li, Wenlin, et al.
Publicado: (2013)

Toward a gold standard for benchmarking gene set enrichment analysis
por: Geistlinger, Ludwig, et al.
Publicado: (2020)

Orchestrating a community-developed computational workshop and accompanying training materials
por: Davis, Sean, et al.
Publicado: (2018)

Curated single cell multimodal landmark datasets for R/Bioconductor
por: Eckenrode, Kelly B., et al.
Publicado: (2023)

Global Alliance for Genomics and Health Meets Bioconductor: Toward Reproducible and Agile Cancer Genomics at Cloud Scale
por: Carey, Vincent J., et al.
Publicado: (2020)

CNVRanger: association analysis of CNVs with gene expression and quantitative phenotypes
por: da Silva, Vinicius, et al.
Publicado: (2019)

seqMINER: an integrated ChIP-seq data interpretation platform
por: Ye, Tao, et al.
Publicado: (2011)

Robustness of single-cell RNA-seq for identifying differentially expressed genes
por: Liu, Yong, et al.
Publicado: (2023)

Assessment of statistical methods from single cell, bulk RNA-seq, and metagenomics applied to microbiome data
por: Calgaro, Matteo, et al.
Publicado: (2020)

Robust static super-replication of barrier options
por: Maruhn, Jan H
Publicado: (2009)

Widespread modulation of gene expression by copy number variation in skeletal muscle
por: Geistlinger, Ludwig, et al.
Publicado: (2018)

Super-robust superamphiphobic surface with anti-icing property
por: Wang, Huanhuan, et al.
Publicado: (2019)

Computational approaches for interpreting scRNA‐seq data
por: Rostom, Raghd, et al.
Publicado: (2017)

Design, execution, and interpretation of plant RNA-seq analyses
por: Upton, Racheal N., et al.
Publicado: (2023)

Ten simple rules for large-scale data processing
por: Fungtammasan, Arkarachai, et al.
Publicado: (2022)

Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+
por: Eng, Chee-Huat Linus, et al.
Publicado: (2019)

Robust, fiducial-free drift correction for super-resolution imaging
por: Wester, Michael J., et al.
Publicado: (2021)

Robustness of differential gene expression analysis of RNA-seq
por: Stupnikov, A., et al.
Publicado: (2021)

Cross-platform normalization of microarray and RNA-seq data for machine learning applications
por: Thompson, Jeffrey A., et al.
Publicado: (2016)

TAS-Seq is a robust and sensitive amplification method for bead-based scRNA-seq
por: Shichino, Shigeyuki, et al.
Publicado: (2022)

HGNChelper: identification and correction of invalid gene symbols for human and mouse
por: Oh, Sehyun, et al.
Publicado: (2022)

SpeedSeq: Ultra-fast personal genome analysis and interpretation
por: Chiang, Colby, et al.
Publicado: (2015)

An interpretable framework for clustering single-cell RNA-Seq datasets
por: Zhang, Jesse M., et al.
Publicado: (2018)

Relaxed abduction: robust information interpretation for industrial applications
por: Hubauer, Thomas
Publicado: (2016)

Heat-Passing Framework for Robust Interpretation of Data in Networks
por: Fang, Yi, et al.
Publicado: (2015)

RNA-seq identified a super-long intergenic transcript functioning in adipogenesis
por: Yi, Fan, et al.
Publicado: (2013)

Bioconductor’s EnrichmentBrowser: seamless navigation through combined results of set- & network-based enrichment analysis
por: Geistlinger, Ludwig, et al.
Publicado: (2016)

RepSeq Data Representativeness and Robustness Assessment by Shannon Entropy
por: Chaara, Wahiba, et al.
Publicado: (2018)

SCnorm: robust normalization of single-cell RNA-seq data
por: Bacher, Rhonda, et al.
Publicado: (2017)

Summarizing internal dynamics boosts differential analysis and functional interpretation of super enhancers
por: Liu, Xiang, et al.
Publicado: (2022)

RNA-seq data science: From raw data to effective interpretation
por: Deshpande, Dhrithi, et al.
Publicado: (2023)

MERRILL: Micromagnetic Earth Related Robust Interpreted Language Laboratory
por: Ó Conbhuí, Pádraig, et al.
Publicado: (2018)

Robust electrocardiogram delineation model for automatic morphological abnormality interpretation
por: Nurmaini, Siti, et al.
Publicado: (2023)

Fast and robust optical flow for time-lapse microscopy using super-voxels
por: Amat, Fernando, et al.
Publicado: (2013)

Exploiting Molecular Dynamics in Composite Coatings to Design Robust Super‐Repellent Surfaces
por: Guo, Rui, et al.
Publicado: (2022)

Biomimetic Robust Starch Composite Films with Super-Hydrophobicity and Vivid Structural Colors
por: Wang, Yateng, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_021ev92dematv5du7ujsfmiuq4