Similar Datasets
Project description:The rise of sample multiplexing in quantitative proteomics for the dissection of complex phenotypic comparisons has been advanced by the development of ever more sensitive and robust instrumentation. Here, we evaluated the utility of the Orbitrap Eclipse Tribrid mass spectrometer (advanced quadrupole filter, optimized FTMS scan overhead) and new instrument control software features (Precursor Fit filtering, TurboTMT and Real-time Peptide Search filtering). Multidimensional comparisons of these novel features increased total peptide identifications by 20% for SPS-MS3 methods and 14% for HRMS2 methods. Importantly Real-time Peptide Search filtering enabled a ~2X throughput improvement for quantification. Across the board, these sensitivity increases were attained without sacrificing quantitative accuracy. New hardware and software features enable more efficient characterization in pursuit of comparative whole proteome insights.
2022-01-07 | PXD016766 | Pride
Project description:We performed a genome-wide analysis of lncRNA expression to identify novel targets for the further study of liver metastasis in CRC. Samples obtained from CRC patients were analyzed using Arraystar human 8×60K lncRNA/mRNA v3.0 microarrays chips to find differentially expressed lncRNAs and mRNAs; The results were confirmed by quantitative reverse transcription-polymerase chain reaction (qRT-PCR). The differentially expressed lncRNAs and mRNAs were identified through fold-change filtering. Gene ontology (GO) and pathway analyses were performed using standard enrichment computational methods.
2016-05-18 | GSE75050 | GEO
Project description:Small ubiquitin-like modifiers (SUMOs) and ubiquitin are frequent post-translational modifications of proteins that play pivotal roles in all cellular processes. We previously reported mass spectrometry-based proteomics methods that enable profiling of lysines modified by endogenous SUMO or ubiquitin in an unbiased manner, without requiring genetic engineering. Here we investigated the applicability of precursor mass filtering enabled by MaxQuant.Live (MQL) to our SUMO and ubiquitin proteomics workflows, which efficiently avoided sequencing of precursors too small to be modified but otherwise indistinguishable by mass-to-charge ratio. Using peptide mass filtering, we achieved much higher precursor selectivity, ultimately resulting in up to 30% more SUMO and ubiquitin sites identified from replicate samples. Real-time ‘untargeting’ of unmodified peptides by MQL resulted in 90% SUMO-modified precursor selectivity from a 25% pure sample, demonstrating great applicability for digging deeper into ubiquitin-like modificomes. We adapted the mass filtering strategy to the new Exploris 480 mass spectrometer, achieving comparable gains in SUMO precursor selectivity and identification rates. Collectively, mass filtering via MQL significantly increased identification rates of SUMO- and ubiquitin-modified peptides from the exact same samples, without the requirement for prior knowledge or spectral libraries.
2021-02-05 | PXD022367 | Pride
Project description:The miRNA microarray analysis was performed to explore the expression profiles of miRNAs using the same liver tissues of NFD-fed mice and HFD-fed mice Summary: An abstract of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: miRCURY™ LNA expression array information. Data Analysis for miRNAs: 1. Low intensity filtering and data normalization: After low intensity miRNAs filtering, raw signal intensities are normalized in Median method. (miRNAs that intensities>=30 in all samples are chosen for calculating normalization factor) 2. Quality assessment of miRNA data after filtering: Contains box plot, Correlation Matrix and scatter plot for miRNAs after normalization. 3. Differentially expressed miRNAs screening: Contains significant differentially expressed miRNAs that pass Volcano Plot filtering. (Fold Change>=1.5, P-value<=0.05) 4. Heat map and hierarchical clustering: Hierarchical clustering on the significant differentially expressed miRNAs that passed Volcano Plots filtering. Sample RNA Quality Control: Sample quality control data file from Nanodrop 1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction for microarray, experiment, and data analysis. FAQ: Frequently asked question Additional miRNA Array Analysis (charge an extra fee): Prediction Analysis for Microarrays (PAM analysis) miRNA Target Gene Prediction and Functional Analysis Additional files provided: Graphs (*.jpg) Raw Intensity File(*.xls, raw miRNAs signal intensity) Layout File (*.gal, the files contain information on the positioning of the capture probes on the array and microRNA annotations for your species of interest) Raw data files produced by GenePix Pro 6.0
2022-11-23 | E-MTAB-8731 | biostudies-arrayexpress
Project description:The miRNA microarray analysis was performed to explore the expression profiles of miRNAs using the same liver tissues of NFD, LSF and HSF groups Summary: An abstract of the experiment and the data analysis. Project Description: Sample and experiment information. Array Information: miRCURY™ LNA expression array information. Data Analysis for miRNAs: 1. Low intensity filtering and data normalization: After low intensity miRNAs filtering, raw signal intensities are normalized in Median method. (miRNAs that intensities>=30 in all samples are chosen for calculating normalization factor) 2. Quality assessment of miRNA data after filtering: Contains box plot, Correlation Matrix and scatter plot for miRNAs after normalization. 3. Differentially expressed miRNAs screening: Contains significant differentially expressed miRNAs that pass Volcano Plot filtering. (Fold Change>=1.5, P-value<=0.05) 4. Heat map and hierarchical clustering: Hierarchical clustering on the significant differentially expressed miRNAs that passed Volcano Plots filtering. Sample RNA Quality Control: Sample quality control data file from Nanodrop 1000 spectrophotometer and standard denaturing agarose gel electrophoresis. Methods: A brief introduction for microarray, experiment, and data analysis. FAQ: Frequently asked question Additional miRNA Array Analysis (charge an extra fee): Prediction Analysis for Microarrays (PAM analysis) miRNA Target Gene Prediction and Functional Analysis Additional files provided: Graphs (*.jpg) Raw Intensity File(*.xls, raw miRNAs signal intensity) Layout File (*.gal, the files contain information on the positioning of the capture probes on the array and microRNA annotations for your species of interest) Raw data files produced by GenePix Pro 6.0
2022-11-24 | E-MTAB-9168 | biostudies-arrayexpress