Benchmarking DIA-type Proteomics Using Large-Scale Inter-Patient Heterogeneity Dataset
Ontology highlight
ABSTRACT:
PROVIDER: EGAS00001005589 | EGA |
REPOSITORIES: EGA
Similar Datasets
Project description:Real patient variability Benchmark Dataset for Optimization of DIA data analysis workflows
| EGAD00010002223 | EGA
Project description:Data independent acquisition (DIA) has become a well-established method in LC-MS driven proteomics. Nonetheless, there are still a lot of possibilities at the data analysis level. By benchmarking different DIA analysis workflows through a ground truth sample mimicking real differential abundance samples, consisting of a differential spike-in of UPS2 in a constant yeast background, we provide a roadmap for DIA data analysis of shotgun samples based on whether sensitivity, precision or accuracy is of the essence. Three different commonly used DIA software tools (DIA-NN, EncyclopeDIA and SpectronautTM) were tested in both spectral library mode and spectral library free mode. In spectral library mode we used the independent spectral library prediction tools Prosit and MS2PIP together with DeepLC, next to the classical DDA-based spectral libraries. In total we benchmarked 12 DIA workflows. DIA-NN in library free mode or using in silico predicted libraries shows the highest sensitivity maintaining a high reproducibility and accuracy.
2024-05-06 | PXD044981 | Pride
Project description:This repository is related to the work "Benchmarking commonly usedsoftware suites and analysis workflows for DIA proteomics and phosphoproteomics". The following files are stored here: 1. four MS datasets generated in this work, including two two-species benchmark datasets acquired on QE HF and timsTOF Pro, and two TNF-alpha induced phosphoproteomics datasets acquired on QE HF-X and timsTOF Pro; 2. all spectral libraries used in this work; 3. raw MS data search reports with analysis logs included if software reported; 4. preprocessed MS data search reports for any result from HF and TIMS DIA benchmark datasets; 5. FASTAs used in this work; 6. a description file (Description_of_iProX_and_public_data.xlsx) for the stored files in this repository and other public data used in this work. Note: 3 and 4 are packed into one zip file for each data search experiment.
2022-12-08 | PXD034709 |
Project description:We describe an improved individual nucleotide resolution CLIP protocol (iiCLIP), which can be completed within 4 days from UV crosslinking to libraries for sequencing. For benchmarking, we directly compared PTBP1 iiCLIP libraries with the iCLIP2 protocol produced under standardised conditions with 1 million HEK293 cells, and with public eCLIP and iCLIP PTBP1 data. There are 3 PTBP1 iiCLIP libraries, 1 input iiCLIP library and 1 PTBP1 iCLIP2 library produced in this study.
2022-08-01 | E-MTAB-10881 | biostudies-arrayexpress
Project description:SILAC labelled Hela cell lysates were mixed in defined ratios and analysed using both DDA and DIA methods, to serve as a benchmark for the novel plexDIA features of DIA-NN.
2023-10-19 | PXD039578 | Pride
Project description:Comprehensive mass spectrometry (MS)-based proteomics is now feasible, but reproducible quantification remains challenging, especially for post-translational modifications such as phosphorylation. Here, we compare the most popular quantification techniques for global phosphoproteomics: label-free quantification (LFQ), stable isotope labeling by amino acids in cell culture (SILAC) and MS2- and MS3-measured tandem mass tags (TMT). In a mixed species comparison with fixed phosphopeptide ratios, we find LFQ and SILAC to be the most accurate techniques. MS2-based TMT yields the highest precision but lowest accuracy due to ratio compression, which MS3-based TMT can partly rescue. However, MS2-based TMT outperforms MS3-based TMT when analyzing phosphoproteome changes in the DNA damage response, since its higher precision and larger identification numbers allow detection of a greater number of significantly regulated phosphopeptides. Finally, we utilize the TMT multiplexing capabilities to develop an algorithm for determining phosphorylation site stoichiometry, showing that such applications benefit from the high accuracy of MS3-based TMT.
| S-EPMC5849679 | biostudies-literature
Project description:Quantum computers promise to solve certain problems more efficiently than their digital counterparts. A major challenge towards practically useful quantum computing is characterizing and reducing the various errors that accumulate during an algorithm running on large-scale processors. Current characterization techniques are unable to adequately account for the exponentially large set of potential errors, including cross-talk and other correlated noise sources. Here we develop cycle benchmarking, a rigorous and practically scalable protocol for characterizing local and global errors across multi-qubit quantum processors. We experimentally demonstrate its practicality by quantifying such errors in non-entangling and entangling operations on an ion-trap quantum computer with up to 10 qubits, and total process fidelities for multi-qubit entangling gates ranging from [Formula: see text] for 2 qubits to [Formula: see text] for 10 qubits. Furthermore, cycle benchmarking data validates that the error rate per single-qubit gate and per two-qubit coupling does not increase with increasing system size.
| S-EPMC6877623 | biostudies-literature
Project description:We use an integrated benchmarking approach to empirically establish guidelines for data acquisition, statistical approach, and replicate numbers for accurate quantification. We evaluated three workflows for protein- and peptide-level quantitative accuracy: data dependent acquisition (DDA), data independent acquisition (DIA), and chemical labeling via tandem mass tags (TMT). The former two datasets were generated in our lab, so we have published them here.
2020-04-06 | MSV000085239 | MassIVE