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324 results for “ngs”
Practico NGS 2021 - BIO252I - RNA-seq
<p>En este repositorio se encuentran los documentos para el práctico de NGS que tiene como objetivo descubrir los genes diferencialmente expresados en las células NHBE, cuando ellas son infectadas con el virus SARS-Cov-2. Se desea comparar células infectadas versus no infectadas (mock). Cada grupo cuenta con 3 réplicas. Este práctico está basado en datos reales (GEO GSE147507), pero que han sido modificados y escalados para este práctico.</p>
NGS competence network - pipeline benchmark data
<p>VCF files generated with the megSAP pipeline for a pipeline benchmark performed by the NGS competence network.</p>
spindle cell variant diffuse large B-cell lymphoma (NGS annotation file; high confidence calls) hematolrep-2136295
<p>Diffuse large B-cell lymphoma with spindle cell morphology is a rare variant. We present the case of a 74-year-old male who initially presented with a right supraclavicular (lymph) node enlargement. Histological analysis showed a proliferation of spindle-shaped cells with narrow cytoplasms. An immunohistochemical panel was used to exclude other tumors, such as melanoma, carcinoma, and sarcoma. The lymphoma was characterized by a cell-of-origin subtype of germinal center B-cell-like (GCB) based on Hans’ classifier (CD10-negative, BCL6-positive, and MUM1-negative); EBER negativity, and the absence of BCL2, BCL6, and MYC rearrangements. Mutational profiling using a custom panel of 168 genes associated with aggressive B-cell lymphomas confirmed mutations in ACTB, ARID1B, DUSP2, DTX1, HLA-B, PTEN, and TNFRSF14. Based on the LymphGen 1.0 classification tool, this case had an ST2 subtype prediction. The immune microenvironment was characterized by moderate infiltration of M2-like tumor-associated macrophages (TMAs) with positivity of CD163, CSF1R, CD85A (LILRB3), and PD-L1; moderate PD-1 positive T cells, and low FOXP3 regulatory T lymphocytes (Tregs). Immunohistochemical expression of PTX3 and TNFRSF14 was absent. Interestingly, the lymphoma cells were positive for HLA-DP-DR, IL-10, and RGS1, which are markers associated with poor prognosis in DLBCL. The patient was treated with R-CHOP therapy, and achieved a metabolically complete response.</p> <p>Carreras J, Kikuti YY, Miyaoka M, Hiraiwa S, Tomita S, Ikoma H, Kondo Y, Ito A, Nagase S, Miura H, Roncador G, Colomo L, Hamoudi R, Campo E, Nakamura N. Mutational Profile and Pathological Features of a Case of Interleukin-10 and RGS1-Positive Spindle Cell Variant Diffuse Large B-Cell Lymphoma. <em>Hematology Reports</em>. 2023; 15(1):188-200. https://doi.org/10.3390/hematolrep15010020</p>
Virtual NGS data used in the paper "Optimal k-mer values for good-quality triploid genome assemblies" and its assembly results
<p>Despite technological advancements, whole-genome sequencing remains technically challenging for organisms with higher-ploidy genomes. Therefore, the use of short-read sequencing platforms for this purpose has been attempted, but the conditions that result in poor-quality genomes have not been elucidated. Therefore, in the present study, simulated sequences mimicking the accumulation of insertion/deletion mutations were created to clarify the permissible differences between homologous chromosomes and the k-mer sizes for good-quality genome assembly from short-read sequencing data for triploid species. The results illustrated that a narrow range of k-mers permits the generation of high-quality assemblies for any level of difference between homologous chromosomes. <br> This dataset consists of the virtual haploid genome (O.fasta), triploid genome data (reference_sequense), NGS read data (NGS_reads), and assembly results (all_contigs) created in this study.<br> </p>
NOAA-NOS-NGS t-sheet Vector Shorelines for the Eastern Shore of VA and southern MD, 1847-1978
The primary purpose of this dataset is to provide VCRLTER researchers and students with a convenient and comprehensive set of historical NOS t-sheet shorelines spanning the full Virginia Eastern Shore in a single GIS data layer. From NOAA-NOS-NGS source metadata: "These shoreline data represent a vector conversion of a set of NOS raster shoreline manuscripts identified by t-sheet or tp-sheet numbers. These vector data were created by contractors for NOS who vectorized georeferenced raster shoreline manuscripts using Environmental Systems Research Institute, Inc. (ESRI)(r), ArcInfo's(r) ArcScan(r) software to create individual ArcInfo coverages. The individual coverages were ultimately edgematched within a surveyed project area and appended together. The NOAA NESDIS Environmental Data Rescue Program (EDRP) funded this project. The NOAA National Ocean Service, Coastal Services Center, developed the procedures used in this project and was responsible for project oversight. The project intent was to rescue valuable historical data and make it accessible and useful to the coastal mapping community. This process involved the conversion of original analog products to digital mapping products. This file is a further conversion of that product from a raster to a vector product that may be useful for Electronic Charting and Display Information Systems (ECDIS) and geographic information systems (GIS)." Original NOAA-NOS-NGS data were organized by project, with each project containing a single shapefile containing the historical shoreline features from multiple T-sheets based on surveys from roughly the same time period. There were 43 projects containing information from 208 T-sheets and TP-sheets that were found to cover the Eastern Shore of VA and southern MD and ranging in time from 1847 to 1978 (plus one set of shorelines from 2009 for the new Chincoteague bridge and the immediate surrounding area). VCRLTER staff combined these 43 shapefiles into a single shapefile with
NGS-MSTB - Example output Web report
<p><a href="https://github.com/ngs-mstb/micgent">NGS-MSTB</a> Docker image ships with the pre-computed example of assembling a set of complete RSV genomes. This dataset includes the Web report of the assembly results. It is used when building the Docker image.</p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain non-structural variants - 10 SNPs, 10 INDELs, 05 TRANSLOCATIONs, 05 INSERSIONs and their reverse complements. Paired-end illumina RNASEQ reads are simulated in fastq format. </p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain structural variants. There are seven mutated ebola genomes each one for two large deletions, insertions, duplications, translocations, inversions, one complex variant1 (consecutive three mutations - insertion, duplication and deletion) and one complex variants2 (consecutive three mutations - deletion, duplication and deletion). All insertions are novel sequence insertion. Paired-end illumine RNASEQ reads are simulated in fastq format.</p>
Implementation of Genomic Variant Calling Using GATK4, SPARK, WDL, CROMWELL and DOCKER Over Simulated Ebola NGS Dataset.
<p>Ebola genome is manually mutated to contain structural variants. There are seven mutated ebola genomes each one for large deletion, insertion, duplication, translocation, inversion, complex variant1 (consecutive three mutations - insertion, duplication and deletion) and complex variants2 (consecutive three mutations - deletion, duplication and deletion). All insertions are novel sequence insertion. Paired-end illumine RNASEQ reads are simulated in fastq format.</p>
Sample datasets for Galaxy NGS tutorial
<p>Datasets in fastqsanger.gz format representing re-sequencing of human mitochondria </p>
Raw data NGS 12s
<p>Raw data from NGS sequencing targeting the 12S marker. The data were used in a study comparing the effectiveness of conventional methods (electrofishing) with an environmental DNA metabarcoding method, for studying the specific richness of fish communities in estuaries on Reunion Island (JANNEL et al. 2024).</p>
Template-specific optimization of NGS genotyping pipelines reveals allele-specific variation in MHC gene expression
<p>Using high-throughput sequencing for precise genotyping of multi-locus gene families, such as the Major Histocompatibility Complex (MHC), remains challenging, due to the complexity of the data and difficulties in distinguishing genuine from erroneous variants. Several dedicated genotyping pipelines for data from high-throughput sequencing, such as next-generation sequencing (NGS), have been developed to tackle the ensuing risk of artificially inflated diversity. Here, we thoroughly assess three such multi-locus genotyping pipelines for NGS data, the DOC method, AmpliSAS and ACACIA, using MHC class IIβ datasets of three-spined stickleback gDNA, cDNA, and "artificial" plasmid samples with known allelic diversity. We show that genotyping of gDNA and plasmid samples at optimal pipeline parameters was highly accurate and reproducible across methods. However, for cDNA data, gDNA-optimal parameter configuration yielded decreased overall genotyping precision and consistency between pipelines. Further adjustments of key clustering parameters were required tο account for higher error rates and larger variation in sequencing depth per allele, highlighting the importance of template-specific pipeline optimization for reliable genotyping of multi-locus gene families. Through accurate paired gDNA-cDNA typing and MHC-II haplotype inference, we show that MHC-II allele-specific expression levels correlate negatively with allele number across haplotypes. Lastly, sibship-assisted cDNA-typing of MHC-I revealed novel variants linked in haplotype blocks and a higher-than-previously-reported individual MHC-I allelic diversity. In conclusion, we provide novel genotyping protocols for the three-spined stickleback MHC-I and -II genes and evaluate the performance of popular NGS-genotyping pipelines. We also show that fine-tuned genotyping of paired gDNA-cDNA samples facilitates amplification bias-corrected MHC allele expression analysis.</p>
ModEst - Precise estimation of genome size from NGS data
<p>Accurate estimates of genome sizes are important parameters for both theoretical and practical biodiversity genomics. We present here a fast, easy-to-implement and precise method to estimate genome size from the number of bases sequenced and the mean sequencing depth. To estimate the latter, we take advantage of the fact that a precise estimation of the Poisson distribution parameter lambda is possible from truncated data, restricted to the part of the sequencing depth distribution representing the true underlying distribution. With simulations we could show that reasonable genome size estimates can be gained even from low-coverage (10X), highly discontinuous genome drafts. Comparison of estimates from a wide range of taxa and sequencing strategies with flow-cytometry estimates of the same individuals showed a very good fit and suggested that both methods yield comparable, interchangeable results.</p>
Mycobacterium tuberculosis complex NGS made easy: data analysis step-by-step (datasets)
<p>Datasets used in the workshop "<em>Mycobacterium tuberculosis</em> complex NGS made easy: data analysis step-by-step". A capacity development initiative by TB-CAPT, PanACEA and Seq&Treat.</p>
Raw sequencing data of NGS of stomach contents of sympatric species of weakly electric fish (genus: Campylomormyrus)
<p>This dataset contains the raw sequencing data of stomach contents of sympatric species of weakly electric fish (genus: <em>Campylomormyrus</em>) using next generation sequencing.</p> <p>Stomach content samples were collected from five <em>Campylomormyrus</em> species (<em>C. alces</em>, ; <em>C. compressirostris</em>, ; <em>C. curvirostris</em>, ; <em>C. numenius</em>, ; <em>C. tshokwe</em>) and samples of <em>Gnathonemus petersii</em> (<em>G. petersii, </em>), a sister genus of <em>Campylomormyrus.</em></p> <p>The fish specimens, from which these stomach content samples are extracted, were collected during an expedition to the Republic of the Congo in fall 2012.</p> <p>The dataset files are in FASTA format.</p>
Raw NGS Data for "Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins"
<p>This directory contains relevant fastq files used for deep sequencing analysis in the publication “Deep mutational scanning and machine learning reveal structural and molecular rules governing allosteric hotspots in homologous proteins”. </p> <p>Fastq files are provided for presorted, uninduced and induced populations from DMS experiments of four homologs (TtgR, TetR, RolR, and MphR). Three replicates were performed for each sample.</p> <p>Data analysis of this deep sequencing data was performed using custom scripts, which are described in the methods section of the publication.</p>
Original NGS dataset from publication "Next-generation sequencing analysis of a cluster of hepatitis C virus infections in a haematology and oncology center".
<p>Original hepatitis C virus hypervariable region 1 NGS sequences in fastq format from patients analyzed in the study "Next-generation sequencing analysis of a cluster of hepatitis C virus infections in a haematology and oncology center". </p> <p> </p>
NGS data produced in 'Rapid selection and identification of functional CD8+ T-cell epitopes from large peptide-coding libraries'; Nature Communications (2019)
<p>Sharma, G et al. Rapid selection and identification of functional CD8+ T-cell epitopes from large peptide-coding libraries. <em>Nature Communications</em>. Accepted (August 2019)</p> <p><strong>Abstract:</strong></p> <p>Cytotoxic CD8+ T-cells recognize and eliminate infected or malignant cells that present, at their cell surfaces, short peptide epitopes derived from intracellularly processed antigens. However, broadly searching for specific major histocompatibility complex (MHC)-bound peptide epitopes that are naturally processed and capable of eliciting a functional T-cell response has been challenging. Here, we report a method for deep and unbiased T-cell epitope profiling, which is done by using <em>in vitro</em> co-culture of CD8+ T-cells and target cells transduced with high-complexity epitope-encoding minigene libraries. Target cells that are subject to cytotoxic attack from T-cells in co-culture are isolated, before they are lost to apoptosis, by fluorescence-activated cell sorting and characterized by sequencing the minigenes encoded within. In the present study, we validate this highly parallelized method using known murine T-cell receptor/peptide-MHC pairs and diverse minigene-encoded epitope libraries to identify naturally processed and MHC-presented peptide epitopes unambiguously and with high sensitivity.</p>
NGSAP-VC : Genomic Variant Calling as an Installable GALAXY Workflow Using NGS data.
<p>Implementation of genomic variants calling as an installable GALAXY workflows using NGS data. Repository contains two separate sets of simulated ebola test data. One for SNPs and INDELs calling and another for Structural Variants calling.</p>
Fig. 13 in NGS-barcodes, haplotype networks combined to external morphology help to identify new species in the mangrove genus Ngirhaphium Evenhuis & Grootaert, 2002 (Diptera: Dolichopodidae: Rhaphiinae) in Southeast Asia
Fig. 13. Distribution map of Ngirhaphium in Southeast Asia
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.