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.
37
datasets available to search
ShareScore release 0.9.0
Dataset results
37 results for “umi”
Reads-per-UMI tables across single-cell RNA sequencing protocols
<p>Data analyzed in <a href="https://www.biorxiv.org/content/10.1101/2023.08.02.551637v1">Lause, Ziegenhain et al. (2023)</a>.</p> <p>Code to obtain these tables from public data sources is available on <a href="https://github.com/berenslab/read-normalization">github</a>.</p> <p> </p> <p>Each row in the table is a UMI-tag detected in a certain cell (column RG) attached to a molecule from a specific gene (column GE) with a certain barcode (column UB). Column N gives the number of times the UMI was detected for that gene and cell.</p> <p>Data sources and protocols are given with the respective file names below.</p> <p><strong>Johnsson2022_Smartseq3_PE.hd1.txt.gz</strong>: Mouse fibroblasts profiled with <strong>Smart-seq3</strong> paired-end; accession E-MTAB-10148, sample plate2,<br> <a href="https://doi.org/10.1038/s41588-022-01014-1">Paper</a><br> <br> <strong>Hagemann-Jensen2020_Smartseq3_SE.hd1.txt.gz: </strong>Mouse fibroblasts profiled with <strong>Smart-seq3</strong> single-end; accession E-MTAB-8735, sample Smartseq3.Fibroblasts.smFISH<br> <a href="https://doi.org/10.1038/s41587-020-0497-0">Paper</a><br> <br> <strong>Hagemann-Jensen2022_Smartseq3xpress.hd1.txt.gz: </strong>HEK293 cells profiled with <strong>Smart-seq3Xpress</strong>; accession E-MTAB-11467.<br> <a href="https://www.biorxiv.org/content/10.1101/2021.07.10.451889v1">Paper</a><br> <br> <strong>Ziegenhain2017.hd1.txt.gz: </strong>Mouse embryonic stem cells profiled by <strong>CEL-seq2, Drop-seq, MARS-seq, </strong>and<strong> SCRB-seq</strong>; GEO accession GSE75790<br> <a href="https://doi.org/10.1016/j.molcel.2017.01.023">Paper</a></p>
Optimized SMRT-UMI protocol produces highly accurate sequence datasets from diverse populations – application to HIV-1 quasispecies
<p>Pathogen diversity resulting in quasispecies can enable persistence and adaptation to host defenses and therapies. However, accurate quasispecies characterization can be impeded by errors introduced during sample handling and sequencing which can require extensive optimizations to overcome. We present complete laboratory and bioinformatics workflows to overcome many of these hurdles. The Pacific Biosciences single molecule real-time platform was used to sequence PCR amplicons derived from cDNA templates tagged with universal molecular identifiers (SMRT-UMI). Optimized laboratory protocols were developed through extensive testing of different sample preparation conditions to minimize between-template recombination during PCR and the use of UMI allowed accurate template quantitation as well as removal of point mutations introduced during PCR and sequencing to produce a highly accurate consensus sequence from each template. Handling of the large datasets produced from SMRT-UMI sequencing was facilitated by a novel bioinformatic pipeline, Probabilistic Offspring Resolver for Primer IDs (PORPIDpipeline), that automatically filters and parses reads by sample, identifies and discards reads with UMIs likely created from PCR and sequencing errors, generates consensus sequences, checks for contamination within the dataset, and removes any sequence with evidence of PCR recombination or early cycle PCR errors, resulting in highly accurate sequence datasets. The optimized SMRT-UMI sequencing method presented here represents a highly adaptable and established starting point for accurate sequencing of diverse pathogens. These methods are illustrated through characterization of human immunodeficiency virus (HIV) quasispecies.</p>
UMI SSU rRNA amplicon datasets
<p>Analysis of 721 SSU rRNA amplicon data from 58 stations in the Pacific Ocean. This item contains following files.</p> <p>abundance.csv</p> <p>- Read count of 155906 OTUs in UMI dataset</p> <p>centroid_seqs.fa</p> <p>- Centroid sequence of each OTU</p> <p>OTU_module_taxon.csv</p> <p>- Results of clustering by WGCNA analysis and assigned taxonomy using the SILVA database</p> <p>Thaumarchaeota.fasta</p> <p>- Sequenced used for phylogenetic analysis of Thaumarchaeota OTUs</p>
Optimized SMRT-UMI protocol produces highly accurate sequence datasets from diverse populations – application to HIV-1 quasispecies
Open the record for dataset details and reuse information.
Kamakura Period Umi-Bune 鎌倉時代海船 Japanese Boat
Replica of the Kamakura Period Umi-Bune, Japanese Boat. The replica was made following museum photos and blueprints so it should be mostly correct. I was selling this model on CGtrader, however, I decided that it's way better to give this model for free because due to the high percentage CGtrader wanted, and generally hassle transfering funds and so on I decided it's only better to give it out for free. This is a replica from historical refs of a LP umi-bune boat. You can use it for your personal projects. I hope this boat may help your historical projects and concepts. Source: Objaverse 1.0 / Sketchfab
Accurate profiling of full length Fv in highly homologous antibody libraries using UMI tagged short reads
<p>Data consists of raw Illumina MiSeq 2x250bp reads from the Fab mini library Mix9A, and Illumina MiSeq 2x300bp reads from the Fab mini library Mix14 at 8 attomole as described in the journal publication "Accurate profiling of full length Fv in highly homologous antibody libraries using UMI tagged short reads".</p>
RAW data: Knockdown of UTX/KDM6A Enriches Precursor Cell Populations in Urothelial Cell Cultures and Cell Lines - single cell RNAseq - Fastq format and UMI counts
<p>This data set of the single cell sequencing experiment of the urothelial cell line HBLAK belongs to the publication: "Knockdown of UTX/KDM6A Enriches Precursor Cell Populations in Urothelial Cell Cultures and Cell Lines" Cancers 2020, 12(4), 1023; https://doi.org/10.3390/cancers12041023.</p> <p> </p>
Ultra II Directional RNA +UMI Qualification Data
<p>This is some of the data used to qualify the <a href="https://www.neb.com/en-us/products/e7416-nebnext-multiplex-oligos-for-illumina-unique-dual-index-umi-adaptors-rna-set-1">NEBNext® Multiplex Oligos for Illumina (Unique Dual Index UMI Adaptors RNA Set 1)</a>.</p> <p>Libraries were prepared from 100 ng of UHR RNA (Agilent) using the <a href="https://www.neb.com/en-us/products/e7760-nebnext-ultra-ii-directional-rna-library-prep-kit-for-illumina">NEBNext Ultra II Directional RNA Library Prep Kit</a> with <a href="https://www.neb.com/en-us/products/e7400-nebnext-rrna-depletion-kit-v2-human-mouse-rat">ribosomal depletion</a>.</p> <p> </p>
Transcriptome profiling of single HEK293 cells with UMIs on Ion Torrent Proton (Run 20160225)
GEO Series GSE89235. Homo sapiens. 76 samples. Type: Expression profiling by high throughput sequencing.
DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Human oligo UMI-STARR-seq]
GEO Series GSE183938. Homo sapiens; synthetic construct. 4 samples. Type: Other.
DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Drosophila genome-wide UMI-STARR-seq]
GEO Series GSE183936. Drosophila melanogaster; synthetic construct. 6 samples. Type: Other.
Induction of neurons from mouse ESC by the bHLH factors Ascl1 and Ngn2 shows distinct genetic dependencies, pluripotency exit, and cell cycle shutdown. [CRISPR-UMI]
GEO Series GSE206871. Mus musculus; Escherichia coli. 2 samples. Type: Other.
UMI-4C in wild-type and p63-null surface ectoderm cells
GEO Series GSE114846. Homo sapiens. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
DeepSTARR predicts enhancer activity from DNA sequence and enables the de novo design of synthetic enhancers [Drosophila oligo UMI-STARR-seq]
GEO Series GSE183937. Drosophila melanogaster; synthetic construct. 12 samples. Type: Other.
UMI-based, single cell RNA sequencing of human nasal epithelial cells grown for 52 days at air liquid interface
GEO Series GSE89236. Homo sapiens. 96 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome profiling of single HEK293 cells with UMIs sequenced on Ion Torrent Proton (Run 20151215)
GEO Series GSE79130. Homo sapiens. 47 samples. Type: Expression profiling by high throughput sequencing.
UMI-4C for quantitative and targeted chromosomal contact profiling
GEO Series GSE76763. Homo sapiens. 53 samples. Type: Other.
Dynamic and stable enhancer-promoter contacts regulate terminal differentiation [UMI-4C]
GEO Series GSE95098. Homo sapiens. 10 samples. Type: Other.
The impact of pro-inflammatory cytokines on the β-cell regulatory landscape provides insights into the genetics of type 1 diabtes [UMI-4C]
GEO Series GSE136865. Homo sapiens. 30 samples. Type: Other.
Lentiviral-based mutagenesis to identify mutations that confer resistance to anti-cancer drugs [umi]
GEO Series GSE164661. Homo sapiens. 2 samples. Type: Other.
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.