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2,556 results for “RNAseq”

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zenodo32/100

IgSeqR RNAseq tutorial dataset

<p>Data hosted for IgSeqR tutorial. A tutorial relating to sample 822 is hosted in our github repo: https://github.com/ForconiLab/IgSeqR/tree/main</p> <p>Data is derived from Biostudies dataset E-MTAB-12017.</p> <p>IgSeqR preprint: https://www.biorxiv.org/content/10.1101/2024.09.03.611002v1</p> <p>IgSeqR publication: TBC</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>

opencc-by-4.0Nov 2024View details →
zenodo32/100

Single Cell RNAseq Pancreatic Cancer Atlas

<p>Complete object for scRNAseq PDAC atlas.</p> <p>&nbsp;</p> <p>Please cite: Loveless IM, Kemp SB, Hartway KM, Mitchell JT, Wu Y, Zwernik SD, Salas-Escabillas DJ, Brender S, George M, Makinwa Y, Stockdale T, Gartrelle K, Reddy RG, Long DW, Wombwell A, Clark JM, Levin AM, Kwon D, Huang L, Francescone R, Vendramini-Costa DB, Stanger B, Alessio A, Waters AM, Cui Y, Fertig EJ, Kagohara LT, Theisen B, Crawford HC, Steele NG. Human pancreatic cancer single cell atlas reveals association of CXCL10+ fibroblasts and basal subtype tumor cells. Clin Cancer Res. 2024 Dec 5. doi: 10.1158/1078-0432.CCR-24-2183. Epub ahead of print. PMID: 39636224..&nbsp;</p>

opencc-by-4.0Nov 2024View details →
zenodo32/100

Quantification of RNAseq and CUT&RUN from MeCP2 adult knockout hippocampus

Open the record for dataset details and reuse information.

opencc-by-4.0Dec 2023View details →
zenodo32/100

Xena TCGA TARGET TCGx RNAseq Data

<p>TCGA, TARGET and TGx RNA-seq data downloaded from XenaBrowser.</p> <p>The data is formatted into a MultiAssayExperiment object, and compressed with R&#39;s qs package.&nbsp;</p>

opencc-by-4.0Mar 2022View details →
dryad32/100

Tumor RNAseq and nCounter for ERY974 monotherapy and/or combination with chemotherapy

<p>We examined pharmacodynamic (PD) of ERY974, CD3 and GPC3-targeting T cell bispecific antibody (TRAB), in tumors of huminized/NOG mice administered with ERY974 and/or chemotherapy. First, we examined the RNAsea data of ERY974 monothrapy for tumors of PC10, NCI-H446, MKN45, and MKN74 of humanized/NOG mice. We found that gene expression related with immune cells at baseline is correlated with efficacy of ERY974. Then,we examined the PD of ERY974 combined with chemotherapy (paclitaxel, cisplatin and capecitabine). In NCI-H446, a representative of non-inflamed-tumor, we examined the tumor RNA of huminized/NOG mice administered with ERY974 and/or paclitaxel, or cisplatin. In MKN45, a representative of non-inflamed-tumor, we examined the tumor RNA of huminized/NOG mice administered with ERY974 and/or capecitabine. For capecitabine combination, we firstly examined the suitable timing among day 3,7,and 14 when combination effect was cleary observed, and found that day 14 is the most suitable timing. From all the data, we found that combination of chemotherpay increased ERY974-induced gene expression related with T cell marker and T cell activation. To examine if our findings  are observed in other TRABs in common, we parepred for the EGFR-TRAB, and examined the RNA analysis of MKN45 tumor of huminized/NOG mice administred with EGFR-TRAB and/or paclitaxel. We confirmed that paclitaxel increased EGFR-TRAB-induced gene expression related with T cell marker and T cell activation. We concluded that combination of TRABs with chemotharpy is suitable strategy to erradicate non-inflamed tumors.</p>

opencc-zeroMay 2022View details →
zenodo32/100

ICB_Hugo_RNAseq

<p>Processed RNAseq data used for ICB_Hugo data object.</p> <p>Publication:&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/26997480/">https://pubmed.ncbi.nlm.nih.gov/26997480/</a>.</p> <p>Raw data obtained from&nbsp;<a href="https://www.ebi.ac.uk/ena/browser/view/PRJNA312948?show=reads">https://www.ebi.ac.uk/ena/browser/view/PRJNA312948?show=reads</a>.</p> <p>Processed with&nbsp;<a href="https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto">https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto</a></p> <p>Dataset details:&nbsp;<a href="https://predictio.ca/dataset/5">https://predictio.ca/dataset/5</a>.</p>

opencc-by-4.0Aug 2022View details →
zenodo32/100

ICB_Jung_RNAseq

<p>Processed RNAseq data used for ICB_Jung data object.</p> <p>Publication:&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/31537801/">https://pubmed.ncbi.nlm.nih.gov/31537801/</a>.</p> <p>Raw data obtained from&nbsp;<a href="https://www.ebi.ac.uk/ena/browser/view/PRJNA557841?show=reads">https://www.ebi.ac.uk/ena/browser/view/PRJNA557841?show=reads</a>.</p> <p>Processed with&nbsp;<a href="https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto">https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto</a></p> <p>Dataset details:&nbsp;<a href="https://predictio.ca/dataset/23">https://predictio.ca/dataset/23</a>.</p>

opencc-by-4.0Aug 2022View details →
zenodo32/100

ICB_Gide_RNAseq

<p>Processed RNAseq data used for ICB_Gide data object.</p> <p>Publication&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/30753825/">https://pubmed.ncbi.nlm.nih.gov/30753825/</a>.</p> <p>Raw data obtained from :<a href="https://www.ebi.ac.uk/ena/browser/view/PRJEB23709?show=reads">https://www.ebi.ac.uk/ena/browser/view/PRJEB23709?show=reads</a>.</p> <p>Processed with&nbsp;<a href="https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto">https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto</a></p> <p>Dataset details:&nbsp;<a href="https://predictio.ca/dataset/20">https://predictio.ca/dataset/20</a>.</p>

opencc-by-4.0Aug 2022View details →
zenodo32/100

ICB_Riaz_RNAseq

<p>Processed RNAseq data used for ICB_Riaz data object.</p> <p>Publication:&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/29033130/">https://pubmed.ncbi.nlm.nih.gov/29033130/</a>.</p> <p>Raw data obtained from&nbsp;<a href="https://www.ebi.ac.uk/ena/browser/view/PRJNA356761?show=reads">https://www.ebi.ac.uk/ena/browser/view/PRJNA356761?show=reads</a>.</p> <p>Processed with&nbsp;<a href="https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto">https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto</a></p> <p>Dataset details:&nbsp;<a href="https://predictio.ca/dataset/12">https://predictio.ca/dataset/12</a>.</p>

opencc-by-4.0Aug 2022View details →
zenodo32/100

single-nucleus RNAseq data from female Aedes aegypti antenna

<p>Single-nucleus RNA sequencing data accompanying Herre*, Goldman* et al. (2022),&nbsp;&quot;Non-Canonical Odor Coding in the Mosquito&quot; (https://doi.org/10.1016/j.cell.2022.07.024)</p> <p>For further analysis see:&nbsp;https://github.com/VosshallLab/Younger_Herre_Vosshall2020/tree/main/snRNAseq_SupplementaryData</p> <p>For raw sequencing files see NCBI BioProject: PRJNA794050</p>

opencc-by-4.0Jan 2022View details →
zenodo32/100

ICB_Fumet2_RNAseq

<p>Processed RNAseq data used for ICB_Fumet2&nbsp;data object.</p> <p>Publication:&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/30753825/">https://www.ncbi.nlm.nih.gov/pubmed/35051357</a>.</p> <p>Raw data obtained from:&nbsp;<a href="https://www.ebi.ac.uk/ena/browser/view/PRJEB23709?show=reads">https://www.ebi.ac.uk/ena/browser/view/PRJNA786565?show=reads</a>. (Sample Title column corresponds to the sample id)</p> <p>Sample metadata to map between run accession and sample title:&nbsp;<a href="http://ftp.ncbi.nlm.nih.gov/geo/series/GSE190nnn/GSE190266/matrix%C2%A0">https://ftp.ncbi.nlm.nih.gov/geo/series/GSE190nnn/GSE190265/matrix/</a></p> <p>Processed with&nbsp;<a href="https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto">https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto</a>.</p>

opencc-by-4.0Oct 2022View details →
zenodo32/100

ICB_Fumet1_RNAseq

<p>Processed RNAseq data used for ICB_Fumet1 data object.</p> <p>Publication:&nbsp;<a href="https://pubmed.ncbi.nlm.nih.gov/30753825/">https://pubmed.ncbi.nlm.nih.gov/35051357/</a>.</p> <p>Raw data obtained from:&nbsp;<a href="https://www.ebi.ac.uk/ena/browser/view/PRJEB23709?show=reads">https://www.ebi.ac.uk/ena/browser/view/PRJNA786567?show=reads</a>. (Sample Title column corresponds to the sample id)</p> <p>Sample metadata to map between run accession and sample title:&nbsp;<a href="http://ftp.ncbi.nlm.nih.gov/geo/series/GSE190nnn/GSE190266/matrix ">https://ftp.ncbi.nlm.nih.gov/geo/series/GSE190nnn/GSE190266/matrix&nbsp;</a></p> <p>Processed with&nbsp;<a href="https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto">https://github.com/LupienLab/kallisto_snakemake/tree/main/Run_Kallisto</a>.</p> <p>Dataset details:&nbsp;<a href="https://predictio.ca/dataset/20">https://www.predictio.ca/dataset/8</a>.</p>

opencc-by-4.0Oct 2022View details →
dryad32/100

RNAseq of partially paralyzed zebrafish embryos at 5 days post-fertilization compared to normal siblings

<p>Sofa potato (sop) is a mutant zebrafish line, whose synaptic transmission at the neuromuscular junction is absent due to a point mutation in the δ subunit gene of the acetylcholine receptor (AChR), leading to paralysis of its skeletal muscles. To explore genetic changes in embryos caused by the lack of synaptic transmission, we performed RNA-seq analysis of normal siblings (<em>sop</em><sup>+/?</sup>) and <em>sop </em>homozygous embryos<em> (sop<sup>-/-</sup>) </em>at 5 days post-fertilization.</p>

opencc-zeroMay 2024View details →
zenodo32/100

Mouse RNASeq data for "The tumor microbiome reacts to hypoxia and can influence response to radiation treatment in colorectal cancer", part 1

Open the record for dataset details and reuse information.

opencc-by-4.0May 2024View details →
zenodo32/100

Mouse RNASeq data for "The tumor microbiome reacts to hypoxia and can influence response to radiation treatment in colorectal cancer", part 2

Open the record for dataset details and reuse information.

opencc-by-4.0May 2024View details →
zenodo32/100

CRUK ACRCelerate CRC GEMM bulk RNAseq

<p>A comprehensive dataset comprising transcriptomic analysis of a world-leading collection of preclinical genetically engineered mouse models (GEMMs) of colorectal cancer (CRC). These patient-relevant models are driven by the mutation of key genes, or aberrant regulation of pathways central to human disease, including, but not limited to APC, TP53, KRAS, BRAF, TGFBR1 and NOTCH. Models within this cohort represent all stages of CRC, spanning from early lesion to late-stage metastatic disease; organoid, tumouroid, orthotopic engrafted disease and ultimately autochthonous primary and disseminated tumours. Moreover, models which discriminate key clinical features such as mismatch repair deficiency and proficiency (MMRd/MMRp), colitis association and anatomical location (right-sided/left-sided) are included.</p> <p>A schematic of available models appears as Figure 1, with further details found in Table 1.</p> <p>For access to the data set please contact: <a>gemmdata@crukscotlandinstitute.ac.uk</a></p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p> <p>&nbsp;</p>

openSep 2024View details →
zenodo32/100

Fishbook_RNAseq_3

<p>Fishbook RNAseq dataset 3</p>

opencc-by-4.0Aug 2021View details →
zenodo32/100

Fishbook_RNAseq_2

<p>Fishbook RNAseq dataset 2</p>

opencc-by-4.0Aug 2021View details →
zenodo32/100

Fishbook_RNAseq_4

<p>Fishbook RNAseq dataset 4</p>

opencc-by-4.0Aug 2021View details →
zenodo32/100

Fishbook_RNAseq_1

<p>Fishbook RNAseq dataset 1</p>

opencc-by-4.0Aug 2021View details →

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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record