Project description:Data from the VLA lyssavirus genotyping microarray. The array platform for this data is GEO accession GPL8066, and consists of 624 oligos representing two viral families. The data set itself consists of 14 arrays, 7 hybridised with RNA from mice brains infected with 7 genotypes of lyssaviruses, 1 hybridised with RNA from normal mouse brain, and 6 hybridised with RNA from coded samples consisting of infected mouse brains or control mouse brains. Keywords: Lyssavirus genotyping microarray
Project description:Data from the VLA lyssavirus genotyping microarray. The array platform for this data is GEO accession GPL8066, and consists of 624 oligos representing two viral families. The data set itself consists of 14 arrays, 7 hybridised with RNA from mice brains infected with 7 genotypes of lyssaviruses, 1 hybridised with RNA from normal mouse brain, and 6 hybridised with RNA from coded samples consisting of infected mouse brains or control mouse brains. Keywords: Lyssavirus genotyping microarray Data from the VLA lyssavirus genotyping microarray. The array platform for this data is GEO accession GPL8066, and consists of 624 oligos representing two viral families. The data set itself consists of 14 arrays, 7 hybridised with RNA from mice brains infected with 7 genotypes of lyssaviruses, 1 hybridised with RNA from normal mouse brain, and 6 hybridised with RNA from coded samples consisting of infected mouse brains or control mouse brains. Statistical analysis of the data was done with DetectiV software (Watson et al., 2007). The median and array methods of normalization were used in the statistical analysis of the results. In the median method, DetectiV software calculates the mean fluorescence for each set of probes and normalised against background fluorescence of all probes, assuming that most probes are not hybridized. The array method utilizes an entire control array, e.g. RNA from a known uninfected animal, as the negative control and all probe values are divided by their respective elements from the control array.
Project description:The yeast calibration curve dataset was acquired to compare the accuracy of DIA tools with decreasing contents of target peptides. Four samples (Y1, Y2, Y3 and Y4) with decreasing contents (200, 100, 50 and 25 ng, respectively) of analytes (yeast tryptic peptides) and a high content of background peptides (800 ng human tryptic peptides constantly) were analyzed in triplicate using LC-DIA-MS/MS. The DIA data were processed by different DIA tools based on the spectral library generated from the DDA data. The accuracy of different DIA tools was compared.
Project description:Gene expression data was analyzed to map with urine proteomics data gene expression data from kidney biopsies from kidney transplant patients with and without acute rejection, chronic allograft nephropathy and BK virus nephritis was used to study gene expression changes during acute rejection, chronic allograft nephropathy and bk virus nephropathy. Samples labeled STA16, STA22, STA14, and STA18 were included in the CAN vs no-CAN analysis as no-CAN samples as they also qualified as non-CAN samples.
Project description:The demo dataset of ApuQuant for testing consists of DIA data acquired by Orbitrap Astral mass spectrometer. This submission includes two demo datasets together with the corresponding DIA-NN identification results. Demo Data I contains raw files from low-input samples with four technical replicates, as well as the corresponding DIA-NN identification results. Demo Data II contains raw files from dead cell samples with three technical replicates and large-sized cell samples with three technical replicates, together with the corresponding DIA-NN identification results. These datasets are provided as representative test data for evaluating the performance of ApuQuant on challenging DIA proteomics samples, including low-input samples and biologically distinct cell populations. The raw mass spectrometry files and search results can be used for demonstration, benchmarking, and reproducibility assessment of the ApuQuant workflow.
Project description:Metatranscriptomic and metaproteomic analysis of C.quadricolor symbiotic bacteria for discovery of new potential biosynthetic clusters
Project description:Primary human astrocytes were infected with either monkeypox virus (MPXV clade IIb lineage), vaccinia virus (VACV: Acambis 2000), or controls (MC=monkeypox control, AC = Vaccinia control) at an MOI of 10 for 6 h. Samples (n=4) were analyzed by LC-MS/MS with label-free quantification where the data was acquired by data-dependent acquisition (DDA).
Project description:This dataset was generated to validate the real-time quality control and automated data analysis capabilities of Apus, an end-to-end solution for large-cohort mass spectrometry-based proteomics. The dataset consists of 23 longitudinally acquired data-dependent acquisition (DDA) runs from HEK 293T cell digest samples, prepared and analyzed under routine laboratory operating conditions on an Orbitrap Astral mass spectrometer (Thermo Scientific) coupled to a Vanquish Neo nanoflow LC system. The dataset was processed through the complete Apus automated workflow, including real-time data aggregation (ApuPickup), parallelized protein identification (ApuPioneer), high-throughput label-free quantification (ApuHorizon), and comprehensive quality control (ApuMonitor), to demonstrate the system's capability for proactive quality management in a live laboratory setting.