Demo dataset for MSCohort analysis
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo Sapiens
SUBMITTER: 
Wei Sun
PROVIDER: PXD050389 | iProX | Wed Mar 06 00:00:00 GMT 2024
REPOSITORIES: iProX
Similar Datasets
Project description:The demo datasets available for MSCohort analysis. You can download to inspect their formats and practice using the software tool.
2024-10-24 | PXD057133 |
Project description:Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collected 2638 files acquired by data independent acquisition (DIA) and paired DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data showed that DIA-based LC-MS/MS related consensus QC metric is more sensitive than DDA-based QC in detecting MS status changes. We then optimized 15 DIA-QC metrics, and invited to manually assess the quality of 2638 DIA files generated by 21 mass spectrometers based on each metric. Based on the annotation results, we developed an AI model for DIA-based QC in the training set of 2059 DIA files, and predicted the liquid chromatography (LC) performance with an AUC of 0.91 and the MS performance with an AUC of 0.97 in an independent validation dataset (n = 523). Finally, we developed an offline software called iDIA-QC for convenient adoption of this methodology for LC-MS QC
2025-05-06 | PXD051878 | Pride
Project description:Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collected 2638 files acquired by data independent acquisition (DIA) and paired DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data demonstrated that DIA-based LC-MS/MS-related consensus QC metrics exhibit higher sensitivity compared to DDA-based QC metrics in detecting changes in LC-MS status. We then optimized 15 metrics and invited 21 experts to manually assess the quality of 2638 DIA files based on those metrics. Based on the annotation results, we developed an AI model for DIA-based QC in the training set of 2110 DIA files. This model predicted the liquid chromatography (LC) performance with an AUC of 0.91 and the MS performance with an AUC of 0.97 in an independent validation dataset (n = 528). Finally, we developed an offline software called iDIA-QC for convenient adoption of this methodology for LC-MS QC.
2025-05-07 | PXD055173 | Pride
Project description:Quality control (QC) in mass spectrometry (MS)-based proteomics is mainly based on data-dependent acquisition (DDA) analysis of standard samples. Here, we collected 2638 files acquired by data independent acquisition (DIA) and paired DDA files from mouse liver digests using 21 mass spectrometers across nine laboratories over 31 months. Our data demonstrated that DIA-based LC-MS/MS-related consensus QC metric exhibit higher sensitivity compared to DDA-based QC metric in detecting changes in LC-MS status. We then optimized 15 metrics and invited 21 experts to manually assess the quality of 2638 DIA files based on those metrics. Based on the annotation results, we developed an AI model for DIA-based QC in the training set of 2110 DIA files. This model predicted the liquid chromatography (LC) performance with an AUC of 0.91 and the MS performance with an AUC of 0.97 in an independent validation dataset (n = 528). Finally, we developed an offline software called iDIA-QC for convenient adoption of this methodology for LC-MS QC.
2024-11-08 | PXD052871 | Pride
Project description:This dataset contains all research data collected for irAE-CNS conducted between 2019.1 and 2024.9. The collection includes files comprising experimental measurements, survey responses, processed analyses. Data formats include CSV, RDATA, and Excel. The complete dataset is organized into categories. All files follow consistent naming conventions and include detailed metadata describing collection methods, instruments/settings used, and processing steps.
2026-02-13 | PAD000030 | Pride
Project description:A study aimed at identification of proteins associated with CRISPR/Cas-induced depletion of creatine kinase B (CKB) in SAOS-LM5 metastatic osteosarcoma cell line using LC-MS/MS in data-independent acquisition (DIA)-parallel accumulation serial fragmentation (diaPASEF) mode. Here we prepared two KO cell lines, SAOS-LM5 CKB KO 6C and SAOS-LM5 CKB KO 11B, as well as control SAOS-LM5 scrambled cell line. After filter-aided sample preparation (FASP) protein digestion and peptide desalting, the samples were conducted to total proteome analysis. The data acquisition was performed in diaPASEF mode on timsTOF Pro 2 mass spectrometer. Data were processed in Spectronaut 19.0 in directDIA mode. This project covers the raw files from the diaPASEF measurements as well as search results from the Spectronaut 19.0 software.
2026-01-23 | PXD065263 | Pride
Project description:<p>The marine microbiome contributes to nearly half of our planet’s net primary production. It plays a central role in the ocean’s carbon cycle through both passive and active release of metabolites into seawater, forming a pool of dissolved compounds known as the marine exometabolome.</p><p><br></p><p>Here, we introduce an untargeted metabolomics dataset of marine dissolved organic compounds collected aboard the scientific research vessel Tara during the AtlantECO Mission Microbiomes expedition (2021-2022). A total of 367 samples were collected from multiple depths across 107 sites in the South Atlantic Ocean, covering environments influenced by major river plumes (e.g., Amazon, Senegal), coastal upwelling systems, and the Weddell Sea. Metabolites were analyzed in positive ionization mode using ultra-high pressure liquid chromatography coupled to high-resolution mass spectrometry (UHPLC-HRMS) and tandem MS. Available data includes both raw (i.e, chromatograms and mass spectra) and pre-processed formats (i.e, intensity tables and annotation files). This dataset provides a resource for the investigation of marine metabolic diversity and dynamics and supports comparative studies across marine environments.</p>
2026-05-19 | MTBLS14508 | MetaboLights
Project description:This project stores the search results of MaxQuant2.0.3.0 of 162 HCC cell line raw files and 48 raw files for spectral library generation, and search results of DIA-NN version 1.8 and Spectronaut version15.2 of HepG2, HCCLM3 and TGFB1-stimulated HCCLM3.
2022-11-11 | PXD037159 | Pride
Project description:MSRefine software test data, including two kinds of data, .raw and .d files.
2022-05-16 | PXD033948 |
Project description:The Aging, Dementia and Traumatic Brain Injury Study is a detailed neuropathologic, molecular and transcriptomic characterization of brains of control and TBI exposure cases from a unique aged population-based cohort from the Adult Changes in Thought (ACT) study. This study was developed by a consortium consisting of the University of Washington, Kaiser Permanente Washington Health Research Institute, and the Allen Institute for Brain Science, and was supported by the Paul G. Allen Family Foundation. This freely available resource (http://aging.brain-map.org/) presents a systematic and extensive data set of study participant metadata, quantitative histology and protein measurements of neuropathology, and RNA sequencing (RNA-seq) analysis of hippocampus and neocortex. Specific methodological details are available on the “Documentation” tab at http://aging.brain-map.org/. Included in this data set are normalized RNA-Seq FPKM files used for analysis in "Neuropathological and transcriptomic characteristics of the aged brain", published in eLife. Other processed data files as well as sample and donor meta-data and QC metrics are available at http://aging.brain-map.org/download/index Controlled access to raw data files is available via https://www.niagads.org/datasets/ng00059
2017-10-16 | GSE104687 | GEO