Cargando…

Enhanced differential expression statistics for data-independent acquisition proteomics

We describe a new reproducibility-optimization method ROPECA for statistical analysis of proteomics data with a specific focus on the emerging data-independent acquisition (DIA) mass spectrometry technology. ROPECA optimizes the reproducibility of statistical testing on peptide-level and aggregates...

Descripción completa

Detalles Bibliográficos
Autores principales:	Suomi, Tomi, Elo, Laura L.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2017
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5517573/ https://www.ncbi.nlm.nih.gov/pubmed/28724900 http://dx.doi.org/10.1038/s41598-017-05949-y

Ejemplares similares

Introducing untargeted data-independent acquisition for metaproteomics of complex microbial samples
por: Pietilä, Sami, et al.
Publicado: (2022)

A comprehensive evaluation of popular proteomics software workflows for label-free proteome quantification and imputation
por: Välikangas, Tommi, et al.
Publicado: (2017)

A systematic evaluation of normalization methods in quantitative label-free proteomics
por: Välikangas, Tommi, et al.
Publicado: (2016)

Benchmarking tools for detecting longitudinal differential expression in proteomics data allows establishing a robust reproducibility optimization regression approach
por: Välikangas, Tommi, et al.
Publicado: (2022)

ROTS: An R package for reproducibility-optimized statistical testing
por: Suomi, Tomi, et al.
Publicado: (2017)

Computational solutions for spatial transcriptomics
por: Kleino, Iivari, et al.
Publicado: (2022)

Urinary proteome profiling for children with autism using data-independent acquisition proteomics
por: Meng, Wenshu, et al.
Publicado: (2021)

Technical advances in proteomics: new developments in data-independent acquisition
por: Hu, Alex, et al.
Publicado: (2016)

DIALib-QC an assessment tool for spectral libraries in data-independent acquisition proteomics
por: Midha, Mukul K., et al.
Publicado: (2020)

COVID-19-specific transcriptomic signature detectable in blood across multiple cohorts
por: Välikangas, Tommi, et al.
Publicado: (2022)

MSLibrarian: Optimized Predicted Spectral Libraries for Data-Independent Acquisition Proteomics
por: Isaksson, Marc, et al.
Publicado: (2022)

Comparative Proteome Signatures of Trace Samples by Multiplexed Data-Independent Acquisition
por: Ctortecka, Claudia, et al.
Publicado: (2021)

Proteome Remodeling of the Eye Lens at 50 Years Identified With Data-Independent Acquisition
por: Cantrell, Lee S., et al.
Publicado: (2022)

SimPhospho: a software tool enabling confident phosphosite assignment
por: Suni, Veronika, et al.
Publicado: (2018)

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control
por: Yang, Yi, et al.
Publicado: (2021)

PhosPiR: an automated phosphoproteomic pipeline in R
por: Hong, Ye, et al.
Publicado: (2021)

Correction to: PhosPiR: an automated phosphoproteomic pipeline in R
por: Hong, Ye, et al.
Publicado: (2022)

In silico spectral libraries by deep learning facilitate data-independent acquisition proteomics
por: Yang, Yi, et al.
Publicado: (2020)

Data Independent Acquisition Reveals In-Depth Serum Proteome Changes in Canine Leishmaniosis
por: Martinković, Franjo, et al.
Publicado: (2023)

Improved risk prediction of chemotherapy‐induced neutropenia—model development and validation with real‐world data
por: Venäläinen, Mikko S., et al.
Publicado: (2021)

Strategies for consistent and automated quantification of HDL proteome using data-independent acquisition
por: Souza Junior, Douglas Ricardo, et al.
Publicado: (2023)

Data‐independent acquisition‐based SWATH‐MS for quantitative proteomics: a tutorial
por: Ludwig, Christina, et al.
Publicado: (2018)

Quantitative Proteomic Analysis of the Senescence‐Associated Secretory Phenotype by Data‐Independent Acquisition
por: Neri, Francesco, et al.
Publicado: (2021)

Optimized data-independent acquisition approach for proteomic analysis at single-cell level
por: Wang, Yuefan, et al.
Publicado: (2022)

HIF prolyl hydroxylase PHD3 regulates translational machinery and glucose metabolism in clear cell renal cell carcinoma
por: Miikkulainen, Petra, et al.
Publicado: (2017)

Characterization of proteome profile data of chemicals based on data-independent acquisition MS with SWATH method
por: Ishiguro, Hiromu, et al.
Publicado: (2023)

Specter: linear deconvolution for targeted analysis of data-independent acquisition mass spectrometry proteomics
por: Peckner, Ryan, et al.
Publicado: (2018)

Optimization of Data-Independent Acquisition Mass Spectrometry for Deep and Highly Sensitive Proteomic Analysis
por: Kawashima, Yusuke, et al.
Publicado: (2019)

MaxDIA enables library-based and library-free data-independent acquisition proteomics
por: Sinitcyn, Pavel, et al.
Publicado: (2021)

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data Independent Acquisition
por: Heil, Lilian R., et al.
Publicado: (2023)

Dear-DIA(XMBD): Deep Autoencoder Enables Deconvolution of Data-Independent Acquisition Proteomics
por: He, Qingzu, et al.
Publicado: (2023)

Comprehensive Proteomic Profiling of Wheat Gluten Using a Combination of Data-Independent and Data-Dependent Acquisition
por: Bromilow, Sophie N. L., et al.
Publicado: (2017)

A Sensitive and Controlled Data-Independent Acquisition Method for Proteomic Analysis of Cell Therapies
por: Lombard-Banek, Camille, et al.
Publicado: (2022)

Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition
por: Heil, Lilian R., et al.
Publicado: (2023)

Dynamic Urinary Proteome Changes in Ovalbumin-Induced Asthma Mouse Model Using Data-Independent Acquisition Proteomics
por: Qin, Weiwei, et al.
Publicado: (2021)

Proteomic comparison of osteoarthritic and reference human menisci using data-independent acquisition mass spectrometry
por: Folkesson, E., et al.
Publicado: (2020)

Calibr improves spectral library search for spectrum-centric analysis of data independent acquisition proteomics
por: Wang, Jen-Hung, et al.
Publicado: (2022)

Streamlined single-cell proteomics by an integrated microfluidic chip and data-independent acquisition mass spectrometry
por: Gebreyesus, Sofani Tafesse, et al.
Publicado: (2022)

A Versatile Isobaric Tag Enables Proteome Quantification in Data-Dependent and Data-Independent Acquisition Modes
por: Tian, Xiaobo, et al.
Publicado: (2020)

Quantitative proteomic characterization of human sperm cryopreservation: using data-independent acquisition mass spectrometry
por: Fu, Longlong, et al.
Publicado: (2019)

Cannot write session to /tmp/vufind_sessions/sess_jecflnpssfe6usqt3n2v53b8pg