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.
12
datasets available to search
ShareScore release 0.7.1
Dataset results
12 results for “fast5”
Raw Fast5 data for "Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and the 16S-ITS-23S of the rrn operon" - PART I
<p>Raw Fast5 data for "Microbiota profiling with long amplicons using Nanopore sequencing: full-length 16S rRNA gene and the 16S-ITS-23S of the rrn operon". See Supplementary Table 2 for associating each sample to its barcode.</p> <p>- FC1_1 includes data for the HM mock community from BEI resources and skin microbiome of the chin in dogs.</p> <p>- FC1_2 includes data for the dorsal skin samples</p> <p>- FC2 includes data for the Zymobiomics mock community and Staphylococcus pseudintermedius isolate</p> <p> </p> <p> </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep1 (run3)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 1 (run 3)</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run1)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 1).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) Mettl3 Knockout
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run3-1)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 3-1; the files are splited two two parts because of limitations of file size).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 2)</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep1 (run2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 1 (run 2). </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep1 (run1 and 4)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 1 (run 1 and 4). </p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run3-2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 3-2; the files are splited two two parts because of limitations of file size).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run4-2)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 4-2; the files are splited two two parts because of limitations of file size).</p>
ONT direct RNA sequencing Fast5 files from mouse embryonic stem cell (C57BL/6J x CAST/EiJ) - Rep2 (run4-1)
<p>We present a novel approach that leverages Oxford Nanopore direct RNA sequencing technology to detect allele-biased patterns of N6-methyladenosine (m6A) modifications in native mRNAs. Our approach utilized human and mouse cells with known genetic variants to ascertain allelic origin of each mRNA molecule. We employed a supervised machine learning model to detect read-level modification ratios, providing a comprehensive understanding of allele-specific m6A modification (ASM) patterns. To analyze the effects of allele specific m6A modification in mouse, we used hybrid mosue embryonic stem cells (C57BL/6J x CAST/EiJ). This page contains replicate 2 (run 4-1; the files are splited two two parts because of limitations of file size).</p>
Q Score Segmented FAST5 Evaluation Data Set
<p>Q Score segmented raw FAST5 data set used for accuracy characterization of the novel Alignment Matrix soft decoding algorithm (<a href="https://doi.org/10.5281/zenodo.11454877">https://doi.org/10.5281/zenodo.11454877</a>) applied to the HEDGES DNA-information storage code. Implementation of the HEDGES code used for accuracy assessment of our algorithm is based on the publication of Press et al. (<a href="https://doi.org/10.1073/pnas.2004821117">https://doi.org/10.1073/pnas.2004821117</a>).</p> <p><strong> </strong></p> <p>Each archive in this data set generally corresponds to a certain design length and HEDGES rate. For example, 1250, 1667, 3333, and 5000 correspond to HEDGES rates of 0.125, 0.167, 0.33, and 0.5 respectively. Additionally, archives labeled with "half" and "quarter" indicate DNA molecule designs that are approximately half and quarter the length of archives labeled "full". Archives labeled with "s1" or "s2" correpsond to data for strands indexed as 1 and 2 for the 0.167 hedges "full" design. Within each archive are FAST5 directories that each correspond to Q Score segment ranges that were used to evaluate the impact of Q Score on soft decoding byte error rate. Each FAST5 directory is clearly labeled with the start and end Q Score value that was used to construct the data set. </p> <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.