Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
373
datasets available to search
ShareScore release 0.7.1
Dataset results
373 results for “Nanopore”
Nanopore long reads enable the first complete genome assembly of a Malaysian Vibrio parahaemolyticus isolate bearing the pVa plasmid associated with acute hepatopancreatic necrosis disease
<p>Supplemental File 1: Main genome assemblies (Unpolished Flye assembly, Polished Flye assembly, Unicycler Hybrid Assembly and Unicycler Illumina-only assembly) generated in this study for comparison and their BUSCO output.</p> <p>Supplemental File 2: Phyre2 protein modelling output of the putative MVP1 TcdA toxin</p> <p>Supplemental File 3: Phyre2 protein modelling output of the putative MVP1 TcdB toxin</p> <p>Supplemental File 4: Phyre2 protein modelling output of the putative MVP1 TccC toxin</p> <p>Supplemental File 5: InterProScan output of the NCBI-predicted MVP1 proteome.</p> <p>Supplemental Table 1: NCBI BlastN output using the <em>fuc</em> genes of <em>Vibrio parahaemolyticus</em> MVP1 as the query to search against the Vibrio reference WGS database as of 21 Oct 2019</p>
Nanopore raw signal data to Benchmarking the MinION: Evaluating long reads for microbial profiling
<p>This dataset contains original raw signal data of a blind study sequencing mock community samples. The samples are differing by nucleic acid quantification technique and composition, and consist of twelve prokaryotic species each. The raw signal data permits future basecalling and may assist in development of applications requiring signal level data.</p> <p>Sample 1 (Barcode 1): heterogenous, adjusted by ddPCR</p> <p>Sample 2 (Barcode 2): heterogenous, adjusted by Qubit</p> <p>Sample 3 (Barcode 3): equimolar, adjusted by ddPCR</p> <p>Sample 4 (Barcode 3): equimolar, adjusted by Qubit</p> <p>FLO-MIN106, SQK-LSK108; Flowcell FAH89600</p> <p>Please consider citing our paper</p> <p>Leidenfrost, R.M., Pöther, D., Jäckel, U. <em>et al.</em> Benchmarking the MinION: Evaluating long reads for microbial profiling. <em>Sci Rep</em> <strong>10, </strong>5125 (2020). https://doi.org/10.1038/s41598-020-61989-x</p> <p>https://doi.org/10.1038/s41598-020-61989-x</p>
NanoGalaxy: Nanopore long-read sequencing data analysis in Galaxy
<p>The data presented in "NanoGalaxy: A Galaxy tool kit with workflows for third-generation sequence analysis" to illustrate the functionality of the tools was obtained from: Wick, Ryan R., et al. "Completing bacterial genome assemblies with multiplex MinION sequencing." <em>Microbial genomics</em> 3.10 (2017).</p> <p>+</p> <p>Li, Ruichao, et al. "Efficient generation of complete sequences of MDR-encoding plasmids by rapid assembly of MinION barcoding sequencing data." <em>Gigascience</em> 7.3 (2018): gix132.</p>
Dataset for Lattice Boltzmann simulation of water flow through rough nanopores
<p>All the datasets used to produce the figures in our paper "<strong>Lattice Boltzmann simulation of water flow through rough nanopores</strong>".</p>
Data from: Chromosome-level genome assembly of a cyprinid fish Onychostoma macrolepis by integration of Nanopore Sequencing, Bionano and Hi-C technology
<p><i>Onychostoma macrolepis</i> is an emerging commercial cyprinid fish species. It is a model system for studies of sexual dimorphism and genome evolution. Here, we report the chromosome-level assembly of the<i> O.macrolepis</i> genome obtained from the integration of Nanopore long-read sequencing with physical maps produced using Bionano and Hi-C technology. A total of 87.9 Gb of Nanopore sequence provided approximately 100-fold coverage of the genome. The preliminary genome assembly was 883.2 Mb in size with a contig N50 size of 11.2 Mb. The 969 corrected contigs obtained from Bionano optical mapping were assembled into 853 scaffolds and produced an assembly of 886.5 Mb with a scaffold N50 of 16.5 Mb. Finally, using the Hi-C data, 881.3 Mb (99.4% of genome) in 526 scaffolds were anchored and oriented in 25 chromosomes ranging in size from 25.27 to 56.49 Mb. In total, 24,770 protein-coding genes were predicted in the genome, and ~96.85% of the genes were functionally annotated. The annotated assembly contains 93.3% complete genes from the BUSCO reference set. In addition, we identified 409 Mb (46.23% of the genome) of repetitive sequence, and 11,213 non-coding RNAs, in the genome. Evolutionary analysis revealed that <i>O.macrolepis</i> diverged from common carp approximately 24.25 million years ago. The chromosomes of <i>O.macrolepis</i> showed an unambiguous correspondence to the chromosomes of zebrafish. The high-quality genome assembled in this work provides a valuable genomic resource for further biological and evolutionary studies of <i>O. macrolepis</i>.</p>
Rapid and Inexpensive Whole-Genome Sequencing of SARS-CoV2 using 1200 bp Tiled Amplicons and Oxford Nanopore Rapid Barcoding
<p>Description of 1200bp amplicon primer sets and .bed and .tsv files for SARS-CoV-2 assembly using the ARTIC bioinformatics pipeline.</p>
Oxford Nanopore Direct RNA Sequencing datasets for detecting rRNA modifications in the Brassica oleracea mitoribosome
<p>Oxford Nanopore Direct RNA Sequencing (DRS) was applied for the detection of rRNA modifications in the <em>Brassica oleracea</em> mitoribosome. A comparison between native rRNA transcripts and in vitro transcribed (IVT) rRNA transcripts that were devoid of any modification indicated systematic base-calling errors and/or variations in current intensities that led to the prediction of the modified nucleotides (Begik et al., 2018).</p> <p>For Nanopore (DRS) library preparation, custom reverse transcription adapters (RTAs) containing Deeplexicon multiplexing barcodes (BC1, BC2 or BC3) were designed for sequence-specific ligation to the 3’-ends of <em>B. oleracea</em> mitochondrial rRNAs.</p> <p>Basecalling and demultiplexing of ONT direct RNA sequencing data were performed by Guppy and Deeplexicon, respectively.</p> <p>For the analysis and visualization of current intensities, a full description is available in the associated publication.</p> <p>The <strong>Eventalign_18S.R</strong> Rscript was used to make the nanopore <strong>18S </strong>signal analysis</p> <p>The <strong>Eventalign_26S.R</strong> Rscript was used to make the nanopore <strong>26S </strong>signal analysis</p> <p>The raw data for the scripts are in the following folders:</p> <p>- For 26S: 26S_Native.barcode01 and 26S_IVT.barcode03<br>- For 18S: 18S_Native.barcode01 and 18S_IVT.barcode02</p> <p>These folders contain the read alignment files output from minimap2 (in .bam format) and the eventalign files generated by the f5c software (in tsv format).</p> <p>The FASTA folder contains the mitochondrial 18S and 26S rRNA gene reference sequence in fasta format</p>
Data and code from "Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation"
<p>Data and code for reproducing the main results of the paper "Nanoporous graphene-based thin-film microelectrodes for in vivo high-resolution neural recording and stimulation".</p>
Using a mobile Nanopore sequencing lab for end-to-end genomic surveillance of Plasmodium falciparum: a feasibility study
Open the record for dataset details and reuse information.
Data from: Estimating bloodstain age in the short term based on DNA fragment length using nanopore sequencer
<p>We used a nanopore sequencer to quantify DNA fragments > 10,000 bp in size and then evaluated their relationship with short-term bloodstain age. Moreover, DNA degradation was investigated after bloodstains were wetted once with water. Bloodstain samples on cotton gauze were stored at room temperature and low humidity for up to 6 months. Bloodstains stored for 1 day were wetted with nuclease-free water, allowed to dry, and stored at room temperature and low humidity for up to 1 week. The proportion of fragments > 20,000 bp in dry bloodstains tended to decrease over time, particularly for fragments > 50,000 bp in size. This trend was modeled using a power approximation curve, with the highest R2 value (0.6475) noted for fragments > 50,000 bp in size; lower values were recorded for shorter fragments. The proportion of longer fragments was significantly reduced in bloodstains that were dried after being wetted once, and there was significant difference in fragments > 50,000 bp between dry conditions and once-wetted. This result suggests that even temporary exposure to water causes significant DNA fragmentation, but not extensive degradation. Thus, bloodstains that appear fresh but have a low proportion of long DNA fragments may have been wetted previously. Our results indicate that evaluating the proportion of long DNA fragments yields information on both bloodstain age and the environment in which they were stored.</p>
Nanopore reads for course 27255 2024
Open the record for dataset details and reuse information.
A near telomere-to-telomere phased reference assembly for the male mountain gorilla (Gorilla beringei beringei) -Oxford Nanopore reads
<p>The critically endangered mountain gorilla <em>Gorilla beringei beringei</em> faces numerous threats to its survival, highlighting the urgent need for genomic resources to aid conservation efforts. Here, we present a near telomere-to-telomere, haplotype-phased reference genome assembly for a male mountain gorilla generated using Pacbio HiFi and Oxford Nanopore Ultralong data. The resulting assembly exhibits exceptional contiguity, with contig N50 of ~ 95 Mbps for the combined pseudohaplotype (3,540,458,497 bps, and 56.5 Mbps (3.1 Gbps) and 51.0 Mbps (3.2 Gbps) for the maternal and paternal haplotypes and an average QV of 65.15 (error rate = 3.1 x 10-7) and 0% switch errors detected. These represent substantial improvements over most other available primate genomes. This high-quality reference genome provides an invaluable resource for future studies on gorilla evolution, adaptation, and conservation, ultimately contributing to the long-term survival of this iconic species.</p> <p>This repository hosts the Oxford Nanopore ultralong reads.</p> <p>The preprint for this work is available at bioRXiv, doi: https://doi.org/10.1101/2024.10.28.620258. </p>
Matched Oxford Nanopore Technologies and Bisulfite Sequencing of the GM24385 Cell Line
<p>One of the most widespread genomic modifications is 5-methylcytosine (5mC), which most frequently occurs at <a href="https://en.wikipedia.org/wiki/CpG_site">CpG</a> dinucleotides. Compared to whole-genome bisulfite sequencing, the traditional method of 5mC detection, nanopore technology can offer many advantages such as simplicity of sample prep and subsequent analysis.</p> <p>In order to demonstrate the utility and convenience of Oxford Nanopore Technologies’ sequencing platform for performing detection and analysis of 5mC, we have sequenced the HG002 Genome in a Bottle Sample GM24385 with both traditional bisulfite sequencing and using nanopore sequencing. Both technologies, old and new, were applied to the same sample from a single DNA extraction.</p> <p><em>Bisulfite sequencing</em></p> <p>Bisulfite sequencing was performed by a commercial provider and processed with the commonly used <a href="https://www.bioinformatics.babraham.ac.uk/projects/bismark/">bismark</a> package to obtain the proportion of reads displaying methylation at CpG sites throughout the whole genome. </p> <p><em>Nanopore sequencing</em></p> <p>Nanopore sequencing was performed using the same sample of GM24385 material sent for bisulfite sequencing. Sequencing was performed on the MinION platform, across multiple flowcells, as part of ongoing platform development activities. The sequencing was not performed explicitly for the analysis presented here; we are making available all sequencing runs undertaken with this sample for the benefit of the community.</p> <p><em>Data Access</em></p> <p>Data is available as part of the Registry of Open Data on AWS: https://registry.opendata.aws/ont-open-data/. This dataset can be accessed through the S3 prefix:</p> <blockquote> <p>s3://ont-open-data/gm24385_mod_2021.09/</p> </blockquote> <p><em>Further Information</em></p> <ul> <li>https://labs.epi2me.io/gm24385-5mc/</li> <li>https://labs.epi2me.io/gm24385-5mc-remora</li> </ul>
Supplementary Information of Amplicon-based nanopore sequencing of patients with COVID-19 omicron (B.1.1.529) variant from India
<p><strong>We report sequencing of omicron variants from SARS-CoV-2 in 75 patients, using Nanopore long-read sequencing chemistry. We highlight the nature of mutations in spike glycoprotein that are unique and common to other populations.</strong></p> <p> </p>
Supplementary Data - Nanopore cDNA With and Without mtDNA
<p>Update (v1.5.8-SUPcaller): added scripts and data files for mt-Nd1 comparisons for different basecaller versions:</p> <ul> <li>LAST_gci_*.csv - gap-compressed identity statistics</li> <li>compStats_*.csv - called base-level statistics</li> <li>process.txt - script example file demonstrating how to generate statistics</li> <li>smealgol.r - R script to generate gap-compressed identities from LAST output</li> <li>est_vs_actual.png - density plots comparing gap-compressed identity with mean estimated accuracy from the caller</li> <li>GCI_albacore_guppy.png - violin plots comparing gap-compressed identity with different callers</li> <li>BaseQ_vs_GCI.png - scatter plots comparing gap-compressed identity with mean estimated accuracy from the caller</li> </ul> <p>Update (v1.5.7-Nd1Reads): added mt-Nd1 read subset from CGDec2017 run:</p> <ul> <li>4T1-WT_reads_CGDec2017_singlePlusMulti.tar</li> </ul> <p>Update (v1.5.6-countAnalysis): added / updated a script to convert transcript mappings to a count table:</p> <ul> <li>count_analysis.r</li> </ul> <p>Update (v1.5.5-Int): added intermediate (post-demultiplexing) demonstration dataset:</p> <ul> <li>SampleDESet_60k_demultiplexed.tar.gz</li> </ul> <p>Also updated count tables and DESeq2 results:</p> <ul> <li>raw_counts_2019-Nov-29.csv</li> <li>DE_orig_VST_GRCm38_CG_GL261_2019-Nov-29.csv.gz</li> <li>DE_shrunk_VST_GRCm38_CG_GL261_2019-Nov-29.csv.gz</li> </ul> <p>Update (v1.5.4-MT): updated demonstration dataset (now 40Mb) to include mitochondrial transcripts, and exclude non-target sequences from chimeric reads:</p> <ul> <li>reads_SampleDESet_sampled_60k.fastq.gz</li> <li>Mm_subset.GRCm38.ensembl_v98.fa</li> </ul> <p>Update (v1.5.3-Ensembl): added/updated Ensembl reference transcripts, including non-coding RNA:</p> <ul> <li>ensembl_mm10_geneFeatureLocations.txt.gz - genome annotation</li> <li>Mus_musculus.GRCm38.ensembl_v98.fa.gz - transcript sequences</li> </ul> <p>Update (v1.5.2-Demo): added 60Mb demonstration dataset for teaching / learning purposes (<em>reads_SampleDESet_sampled_60k.fastq.gz</em>). This dataset can be used for testing demultiplexing, or carrying out differential expression analysis on nanopore reads. There are 15k reads sampled from each run (subset on ~300 genes), plus 7.5k chimeric reads from the Dec17 run, plus 7.5k reads sampled from from CG009/BC08. The gene subset includes ~100 genes differentially-expressed between 4T1WT and 4T1ρ<sup>0</sup> cell lines, plus an additional ~200 genes with minimal differential expression observed between any 4T1 cell lines (i.e. a housekeeping gene set):</p> <ul> <li>BC01, BC02, BC04, BC06 - 4T1 cell line reads from three sequencing runs (005, 005, 004, Dec17)</li> <li>BC03, BC05, BC07 - 4T1ρ<sup>0</sup> (without mtDNA) cell line reads from three sequencing runs (005, 004, Dec17)</li> <li>BC08 - 4T1ρ<sup>0</sup>SC (from subcutaneous tumour) cell line reads from one sequencing run (009)</li> </ul> <p>[note: v1.5.1-Demo has the wrong sequence ID for BC08 reads]</p> <p>Update (v1.5.0-Called): added full 4T1 call set (called using guppy high-accuracy v3.2.2), gene transcript count tables, and differential expression results</p> <p>Update (v1.4.1-Chimeric): added more example called chimeric reads of various [unclassified] categories</p> <p>Update (v1.4.0-Chimeric): added example chimeric reads, one formed [presumably] during sample prep ["conjugation"], another formed in-silico ["double read"]</p> <p>Update (v1.3.0-DESeq2): added count table and metadata file for DESeq2 analysis</p> <p>Update (v1.2.1-10k): added 10k of FASTQ reads from a more recent run (part of the same differential expression project).</p> <p>Supplementary data to go with David Eccles' poster about nanopore cDNA sequencing with and without mitochondrial DNA.</p> <p>Reference mouse mtDNA and mtDNA reads from 4T1 cells (from MinION cDNA sequencing, and from SRA run SRR6747859).</p> <ul> <li>fwd_4T1_BC06.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from Wildtype 4T1 strain, filtered as transcript-forward orientation</li> <li>rev_4T1_BC06.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from Wildtype 4T1 strain, filtered as transcript-reverse orientation</li> <li>fwd_4T1_BC07.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from 4T1ρ0 strain (no mitochondrial DNA), filtered as transcript-forward orientation</li> <li>rev_4T1_BC07.correctedReads.uniqueOnly.fasta.gz -- Canu-corrected cDNA reads from 4T1ρ0 strain (no mitochondrial DNA), filtered as transcript-reverse orientation</li> </ul> <p>Other intermediate data files are also included, see `4way_mapping_process.txt` for more details.</p> <p>The mpileup differential coverage script can be found <a href="https://github.com/gringer/bioinfscripts/blob/master/mpileupDC.pl">here</a>.</p>
Ptychographic X-ray speckle tracking (PXST) scan of the nanoporous gold sample
<p>The PXST scan of a 2.5 micron-thick piece of nanoporous gold measured at P11 beamtime of the PETRA III synchrotron radiation facility. The beam was focused with a pair of MLLs with focal lengths of 1.25 mm and 1.15 mm and numerical apertures of 0.014 and 0.015, in the vertical and horizontal directions, respectively. The X-ray beam photon energy was 17.5 keV.</p>
Addiitional Files: The diagrams of population structure, highly divergent regions, GC content and Nanopore reads depth, SNP number and Nanopore reads depth, and analyses of co-linearity against Nipponbare reference genome in 251 accessions.
<p>Additional Files for " <strong>A Super Pan-Genomic Landscape of Rice".</strong></p> <p>Addtional File1: Supplementary File1.Population structure of 251 rice accessions inferred by ADMIXTURE from K=6 to K=15.</p> <p>Additional File2: Supplementary File2.The diagram of co-linearity for assembled genome against Nipponbare refercne genome in 251 rice accessions.</p> <p>Additional File3: Supplementary File3. Highly divergent regions based on SV.</p> <p>Additional File4: Supplementary File4. The diagram of SNP number and Nanopore reads depth per 100kb windows in 251 rice accessions.</p> <p>Additonal File5:Supplementary File5. The diagram of GC content and the Nanopore reads depth per 10kb windows in 251 rice accessions.</p> <p> </p>
Data for for Detecting cell-of-origin and cancer-specific methylation features of cell-free DNA from Nanopore sequencing
<p>Datasets accompanying the paper https://doi.org/10.1101/2021.10.18.464684</p>
Dataset for Fig. 1d, Replicate 1 of DNA Nanopore Computing
<p>FAST5 files containing raw nanopore current data for the manuscript "A nanopore interface for higher bandwidth DNA computing".</p> <p>This set includes the data used for Replicate 1 of Fig. 1d.</p> <table> <thead> <tr> <th scope="col">File Name</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>DESKTOP_CHF4GRO_20190328_FAK62104_MN21390_sequencing_run_03_28_19_run03_d.fast5</td> <td>Replicate 1, 0.02 uM</td> </tr> <tr> <td>DESKTOP_CHF4GRO_20190328_FAK62104_MN21390_sequencing_run_03_28_19_run03_f.fast5</td> <td>Replicate 1, 0.1 uM</td> </tr> <tr> <td>DESKTOP_CHF4GRO_20190328_FAK62104_MN21390_sequencing_run_03_28_19_run03_h.fast5</td> <td> <p>Replicate 1, 0.2 uM</p> </td> </tr> <tr> <td>DESKTOP_CHF4GRO_20190328_FAK62104_MN21390_sequencing_run_03_28_19_run03_j.fast5</td> <td>Replicate 1, 0.5 uM</td> </tr> <tr> <td>DESKTOP_CHF4GRO_20190328_FAK62104_MN21390_sequencing_run_03_28_19_run03_l.fast5</td> <td>Replicate 1, 1.0 uM</td> </tr> </tbody> </table> <p> </p>
Dataset for Fig. 4d, Replicate 1 of DNA Nanopore Computing
<p>FAST5 files containing raw nanopore current data for the manuscript "A nanopore interface for higher bandwidth DNA computing".</p> <p>This set includes the data used for Replicate 1 of Fig. 4d.</p> <table> <thead> <tr> <th scope="col">File Name</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>DESKTOP_CHF4GRO_20210221_FAP42740_MN21390_sequencing_run_02_21_21_run01_b.fast5</td> <td>No circuits activated</td> </tr> <tr> <td>DESKTOP_CHF4GRO_20210221_FAP42740_MN21390_sequencing_run_02_21_21_run01_d.fast5</td> <td>Circuits 5 and 9 activated </td> </tr> <tr> <td>DESKTOP_CHF4GRO_20210221_FAP42740_MN21390_sequencing_run_02_21_21_run01_f.fast5</td> <td>Circuits 1, 7, and 8 activated</td> </tr> </tbody> </table> <p> </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.