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642 results for “multiplexed”
Multiplexed long-read plasmid validation and analysis using OnRamp
<p>Plasmid read data and references from "Multiplexed long-read plasmid validation and analysis using OnRamp "</p> <p>Experiments:</p> <ol> <li>AAZ605 - 7 plasmids</li> <li>AFQ178 - 9 plasmids</li> <li>ACK577 - 30 plasmids</li> <li>AEZ576 - 15 plasmids</li> <li>plasmids_ref_7.fasta</li> <li>plasmids_ref_9.fasta</li> <li>plasmids_ref_15.fasta</li> <li>plasmids_ref_30.fasta</li> </ol> <p> </p>
Supporting data for "Long distance multiplexed quantum teleportation from a telecom photon to a solid-state qubit"
<p>This repository contains the data supporting the article "Long distance multiplexed quantum teleportation from a telecom photon to a solid-state qubit" by Dario Lago-Rivera, Jelena V. Rakonjac, Samuele Grandi and H. de Riedmatten.</p> <p>The individual .zip files contain the raw detection files for the main results of the article, i.e. the short distance teleportation, the teleportation results as a function of the repetition rate of the experiment and the teleportation experiment across 1 km of optical fibre.</p>
Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers
<p>This repository contains the raw IMC data of ZTMA 26 as continuation of dataset <strong>10.5281/zenodo.7494413.</strong> The zip files starting with ZTMA contain the raw IMC measurements (mcd and txt) of those parts of the TMA. The TMA measurements are split up into parts in order to avoid huge files.</p> <p>Additionally, this repository contains the metadata of the patients analyzed in this study, the panel information and the single-cell data that was extracted from the multiplexed images together with the associated metadata in SingleCellExperiment format for analysis in R.</p> <p>The analysis.zip folder contains files that were written out during the analysis according to the scripts in https://github.com/BodenmillerGroup/BC_LN_metastses.</p> <p>The single-cell and other data outputs from CellProfiler can be found in the cpout.zip file.</p> <p>The IF_whole_sections.zip file contains the IF images of the primary breast cancer sections (czi files) and the extracted single-cell data.</p>
Multiplex imaging of breast cancer lymph node metastases identifies prognostic single-cell populations independent of clinical classifiers
<p>This repository contains the raw IMC data of ZTMA 21 and 25 of the matched primary breast cancer and lymph node metastasis study presented in Fischer and Jackson et al., 2023. The code that was used to process and analyze this data can be found at https://github.com/BodenmillerGroup/BC_LN_metastses.</p> <p>The zip files starting with ZTMA contain the raw IMC measurements (mcd and txt) of the respective parts of the TMA. The TMA measurements are split up into parts in order to avoid huge files.</p>
Multiplexed On-Yeast Serological Assay for Immune Escape Screening of SARS-CoV-2 Variants
<p>Experimental data and scripts used for the development of a Yeast-based serological Assay:</p> <ol> <li>The<strong> Python scripts</strong> folder includes all scripts used in this study to analyze sera titers and plotting data.</li> <li>The<strong> Raw data</strong> folder includes: <ol> <li>The Y<strong>east Immunoassay development</strong> folder includes the flow cytometric data for serum depletion and reduction of ligand depletion effects.</li> <li>The <strong>Yeast serological data folder</strong> includes the raw data of all tested sera and related data for their analyses.</li> </ol> </li> <li>The <strong>Snapgene plasmid maps </strong>folder includes the plasmid maps for the three SARS-CoV-2 VOCs for Snapgene.</li> </ol> <p> </p> <p> </p>
Analysis results reported in "Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps"
<p>Analysis results reported in "Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps" (<a href="https://www.biorxiv.org/content/10.1101/2022.05.07.490900v1">biorxiv</a>) of <a href="https://doi.org/10.5281/zenodo.7299516">4i data</a>. Analysis of this dataset was done with <a href="https://pypi.org/project/campa/">CAMPA</a>, and all scripts to reproduce these results are available in the<a href="https://github.com/theislab/campa_ana"> CAMPA reproducibility repository</a>.</p>
4i dataset for "Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps"
<p>4i dataset described and analysed in "Learning consistent subcellular landmarks to quantify changes in multiplexed protein maps" (<a href="https://www.biorxiv.org/content/10.1101/2022.05.07.490900v1">biorxiv</a>). Analysis of this dataset was done with <a href="https://pypi.org/project/campa/">CAMPA</a>. The data is in CAMPA-readable format; for more information on the data format, see the <a href="https://campa.readthedocs.io/en/develop/overview.html#data-format">CAMPA documentation</a> .</p> <p>The data contains preprocessed wells of 184A1 and HeLa cells with different chemical treatments and 43 channels. For more information on the data, see the <a href="https://github.com/theislab/campa_ana/blob/develop/workflow/00_setup_and_download_data.ipynb">CAMPA reproducibility repository</a>. </p>
Data from: 3-D deconvolution of human skin immune architecture with Multiplex Annotated Tissue Imaging System (MANTIS)
<p><span class="pre-line-wrapping ng-binding">Routine clinical assays, such as conventional immunohistochemistry, often fail to resolve the regional heterogeneity of complex inflammatory skin conditions. Here we introduce MANTIS (Multiplexed Annotated Tissue Imaging System), a flexible analytic pipeline compatible with routine practice, specifically designed for spatially-resolved immune phenotyping of the skin in experimental or clinical samples. Based on phenotype attribution matrices coupled to alpha-shape algorithms, MANTIS projects a representative digital immune landscape, while enabling automated detection of major inflammatory clusters and concomitant single-cell data quantification of biomarkers. We observed that severe pathological lesions from systemic lupus erythematosus, Kawasaki syndrome, or COVID-19-associated skin manifestations share common quantitative immune features, while displaying a non-random distribution of cells with the formation of disease-specific dermal immune structures. Given its accuracy and flexibility, MANTIS is designed to solve the spatial organization of complex immune environments to better apprehend the pathophysiology of skin manifestations.</span></p>
MultiplexMS: A mass spectrometry-based multiplexing strategy for ultra-high-throughput analysis of complex mixtures
<p>Abstract: Throughput for chemical analysis of natural products mixtures has not kept pace with recent developments in genome sequencing technologies and laboratory automation for high-throughput screening, leading to a disconnect between chemical and biological profiling at the library scale that limits new molecule discovery. Here we report a new strategy for sample multiplexing that can increase mass spectrometry-based profiling up to 30-fold over traditional methods. This strategy involves the analysis of pooled samples and subsequent computational deconvolution to reconstruct peak lists for each sample in the set. We validated this approach using <em>in silico</em> experiments and demonstrated that the method has a high precision (>97%) for large, pooled samples (n = 30), particularly for infrequently occurring metabolites (n < 10) of relevance in drug discovery applications. Finally, we repeated a recently reported biological activity profiling study on 925 natural products extracts, leading to the rediscovery of all previously reported bioactive metabolites using just 5% of the previously required MS acquisition time. This new method is compatible with mass spectrometry data from any instrument vendor and is supported by an open-source software package available at <a href="https://github.com/liningtonlab/MultiplexMS">https://github.com/liningtonlab/MultiplexMS</a>.Throughput for chemical analysis of natural products mixtures has not kept pace with recent developments in genome sequencing technologies and laboratory automation for high-throughput screening, leading to a disconnect between chemical and biological profiling at the library scale that limits new molecule discovery. Here we report a new strategy for sample multiplexing that can increase mass spectrometry-based profiling up to 30-fold over traditional methods. This strategy involves the analysis of pooled samples and subsequent computational deconvolution to reconstruct peak lists for each sample in the set. We validated this approach using <em>in silico</em> experiments and demonstrated that the method has a high precision (>97%) for large, pooled samples (n = 30), particularly for infrequently occurring metabolites (n < 10) of relevance in drug discovery applications. Finally, we repeated a recently reported biological activity profiling study on 925 natural products extracts, leading to the rediscovery of all previously reported bioactive metabolites using just 5% of the previously required MS acquisition time. This new method is compatible with mass spectrometry data from any instrument vendor and is supported by an open-source software package available at <a href="https://github.com/liningtonlab/MultiplexMS">https://github.com/liningtonlab/MultiplexMS</a>.</p>
Multiplexed PET data: (89Zr + 124I) mouse phantom - Doubles and Triple Coincidences - Inveon PET/CT scanner
<p>Dataset from a simultaneous 89Zr and 124I PET acquisition performed with a 3D-printed mouse phantom with the preclinical PET/CT Inveon scanner. </p> <p>It includes:</p> <p>1 ) Sinogram of Double Coincidences: With the same format as the Inveon scanner. It includes Prompt and Background . Background includes Randoms+Scatter+Promptgamma coincidences. It has already been corrected by attenuation and normalization.</p> <p>2 ) Sinogram of Triple Coincidences: With the same format as the Inveon scanner. It includes Prompt and Background . Background includes Randoms+Scatter+Promptgamma coincidences. It has already been corrected by attenuation and normalization. </p> <p>3 ) Triple Coincidences with V-LOR format (pairs of sinogram bins for each triple coincidence)</p> <p>4 ) Mask with the gaps in the sinogram</p> <p>5 ) CT image reconstructed by the scanner </p> <p> </p>
Dataset for Spatial and polarization division multiplexing harnessing on-chip optical beam forming
<p>This dataset contains the raw data for the figures (Fig. 1, Fig. 2, Fig. 3, Fig. 4, Fig. 5, Fig. 6, Fig. S1, Fig. S2 and Fig. S3) in the publication entitled "Spatial and polarization division multiplexing harnessing on-chip optical beam forming" published by Laser & Photonics Reviews (DOI: 10.1002/lpor.202300298). Datafiles are in .txt format.</p> <p>All relevant information regarding the dataset, how it was obtained and its context is contained in the manuscript and the supporting information.</p>
Supplemental Datasets for 'Multiplexed effector screening for recognition by endogenous resistance genes using positive defense reporters in wheat protoplasts'
<p>Supplemental Datasets:</p><p><strong>Number </strong></p><p><strong>File name </strong></p><p><strong>Description </strong></p><p>S1 </p><p>S1_Figure1_Data.csv </p><p>Luminescence data for Figure 1, protoplast time course experiment </p><p>S2 </p><p>S2_RNAseqSampleTable.csv </p><p>List of samples and treatment groups for RNAseq experiment </p><p>S3 </p><p>S3_LFC_1_genes.xlsx </p><p>Lists of Gabo/GaboSr50, Fielder and all cultivar genes upregulated by log fold threshold of 1 </p><p>S4 </p><p>S4_GOTerms_Table.xlsx </p><p>GO terms analysis Query tables and g:profiler results tables </p><p>S5 </p><p>S5_LFC2_genes.xlsx </p><p>Lists of Gabo/GaboSr50, Fielder and all cultivar genes upregulated by log fold threshold of 2 </p><p> </p><p>S6 </p><p>S6_Primers.xlsx </p><p>List of primers used </p><p>S7 </p><p>S7_PlasmidList.xlsx </p><p>List of plasmids used </p><p>S8 </p><p>S8_Figures3-5Data.xlsx </p><p>Luminescence data used for generating Figures 3 - 7</p><p>S9</p><p> </p><p>S9_Figures3-7Stat.xlsx</p><p> </p><p>Stats output for Figures 3 - 7</p><p> </p><p>S10</p><p> </p><p>S10_SuppFiguresData.xlsx</p><p> </p><p>Data for Supplementary Figures S1 and S2</p><p> </p>
Multiplexing PCR allows the identification of within-species genetic diversity in ancient eDNA
<p><span>Sedimentary ancient DNA (<em>seda</em>DNA) has rarely been used to obtain population-level data due to either a lack of taxonomic resolution for the molecular method used, limitations in the reference material or inefficient methods. Here, we present the potential of multiplexing different PCR primers to retrieve population-level genetic data from <em>seda</em>DNA samples. <em>Vaccinium</em> <em>uliginosum</em> (Ericaceae) is a widespread species with a circumpolar distribution and three lineages for present-day populations. We searched 18 plastid genomes for intraspecific variable regions and developed 61 primers to target these. Initial multiplex PCR testing resulted in a final set of 38 primers. These primers were used to analyse 20 lake <em>seda</em>DNA samples (11,200 cal. yr BP to present) from five different localities in northern Norway, the Alps and the Polar Urals. All known V<em>. uliginosum</em> lineages in these regions and all primers could be recovered from the <em>seda</em>DNA data, where for each sample 28.1 primers containing 34.15 variant sequences were obtained on average. All sediment samples were dominated by a single lineage, except three alpine samples which had co-occurrence of two different lineages. Furthermore, lineage turnover was observed in the Alps and northern Norway, suggesting that present-day phylogeographical studies may overlook past genetic patterns. Multiplexing primers is a promising tool for generating population-level genetic information from <em>seda</em>DNA. The relatively simple method, combined with high sensitivity, provides a scalable method that will allow researchers to track populations through time and space using environmental DNA.</span></p>
Enhanced design of multiplexed coded masks for Fresnel incoherent correlation holography
<p>Original Dataset of figures of the published article Enhanced design of multiplexed coded masks for Fresnel incoherent correlation holography in <a href="https://www.nature.com/srep"><em>Scientific Reports</em></a> <strong>volume 13</strong>, Article number: 7390 (2023).</p> <p>https://doi.org/10.1038/s41598-023-34492-2</p>
Raw ptychography data for manuscript with title 'Multiplexing limitis in ptychography'
<p>- Given are the HDF files containing the raw diffraction patterns, and the reconstructed files.<br>- The metadata for the reconstruction of each dataset is stored in the raw files, and in the reconstructed files<br>- For each scenario, the Fourier ring correlation (FRC) was calculated against the reconstruction with a single beam as reference, and against the corresponding region for the simulated dataset.</p> <p>The reconstruction of these datasets was carried out with ptylab:<br>Loetgering, L., Du, M., Boonzajer Flaes, D., Aidukas, T., Wechsler, F., Penagos Molina, D. S., Rose, M., Pelekanidis, A., Eschen, W., Hess, J., Wilhein, T., Heintzmann, R., Rothhardt, J., & Witte, S. (2023). PtyLab.m/py/jl: a cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography. In Optics Express (Vol. 31, Number 9, pp. 13763–13797).<br>Zenodo. https://doi.org/10.5281/zenodo.8287047<br>Github: https://github.com/PtyLab/PtyLab.py</p> <p>EDIT:<br>The first version of this repository corresponds to the datasets used in the preprint:<br>Molina, Daniel Penagos; Eschen, Wilhelm; Liu, Chang; Limpert, Jens; Rothhardt, Jan (2024). Multiplexing information limits in ptychography. Optica Open. Preprint. https://doi.org/10.1364/opticaopen.25941427.v2</p> <p>A second set of datasets was added. These correspond to the experimental results in the final version of the published paper:<br>Daniel S. Penagos Molina, Wilhelm Eschen, Chang Liu, Jens Limpert, and Jan Rothhardt, "Multiplexing information limits in multi-beam ptychography," Opt. Express 33, 12925-12938 (2025)</p> <p>- Data were measured at the Institute of Applied Physics in Jena.</p> <p>Please contact me (santiago.penagos@uni-jena.de) for additional support.</p>
Efficacy of a Multiplex BangasureTM RT-PCR Kit for the Detection of COVID-19
ClinicalTrials.gov study NCT05190016. IPD Sharing: NO. Countries: 1. Publications: 14.
Improvements Through the Use of a Rapid Multiplex PCR Enteric Pathogen Detection Kit in Children With Hematochezia
ClinicalTrials.gov study NCT03362970. IPD Sharing: NO. Countries: 1. Publications: 5.
Multiplexing Prism Fitting for Field Expansion of Monocular Vision
ClinicalTrials.gov study NCT06027216. IPD Sharing: NO. Countries: 1. Publications: 3.
Multiplexing PCR allows the identification of within-species genetic diversity in ancient eDNA
Open the record for dataset details and reuse information.
Demo dataset for: SPACEc, a streamlined, interactive Python workflow for multiplexed image processing and analysis
Open the record for dataset details and reuse information.
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OpenNeuro
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