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25,372 results for “Transcriptomics”
CDS of Urochloa fusca transcriptome - whole seedling (except roots)
<p>The CDS data was obtained from transcriptome of above whole seedling (except roots) of 12 days old <em>Urochloa fusca</em> seedlings.</p>
Diamond-BLASTx of transcriptome contigs of Thalassiosira hyalina and Nitzschia frigida
<p>This is an annotation file, delivering the Diamond-BLASTx results for the contigs of the transcriptome assemblies of Thalassiosira hyalina and Nitzschia frigida. Theswe originate from a time course experiment, in which these two species were exposed to high light stress and monitored over 120h under low and high pCO2. The corresponding Sequencing data is deposited at the EBI ArrayExpress database under accession number E-MTAB-6999. Contigs were created with Trinity Assembler and are available under DOI:10.5281/zenodo.3361258</p> <p>The according publication is currently in review (8/6/2019): Higher sensitivity towards light stress and ocean acidification in an Arctic sympagic compared to a pelagic diatom;</p> <p>Author team: Ane C. Kvernvik, Sebastian D. Rokitta, Eva Leu, Lars Harms, Tove M. Gabrielsen, Björn Rost and Clara J. M. Hoppe</p> <p>Do not hesitate to contact the authors if you like more information!</p>
emmetaobrien/mm_neo_atlas: Transcriptomic Atlas of Mouse Neocortical Layers
<p>In the mammalian cortex, neurons and glia form a patterned structure across six layers whose complex cytoarchitectonic arrangement is likely to contribute to cognition. This dataset contains transcriptomes from layers 1-6b of different areas (primary and secondary) of the adult (postnatal day 56) mouse somatosensory cortex. A total of 5,835 protein-coding genes and 66 noncoding RNA loci are differentially expressed ("patterned") across the layers. Layers 2-6b are each associated with specific functional and disease annotations that provide insights into their biological roles. This dataset extends currently available resources by providing quantitative expression levels, by being genome-wide, by including novel loci, and by identifying candidate alternatively spliced transcripts that are differentially expressed across layers.</p> <p>"A transcriptomic atlas of mouse neocortical layers", TG Belgard et al. Neuron, 25:605-616 (2011).</p> <p><a href="http://wwwfgu.anat.ox.ac.uk/~grantb/mouse_layers/">http://wwwfgu.anat.ox.ac.uk/~grantb/mouse_layers/</a></p>
Supplemental Data for: Segmentation-free inference of cell types from in situ transcriptomics data
<p>Supplemental Data for: Segmentation-free inference of cell types from <em>in situ</em> transcriptomics data</p>
Transcriptomics data and script for publication "Unexpected intracellular biodegradation and recrystallization of gold nanoparticles"
<p>Transcriptomics data from DNA arrays sequencing</p> <p>Folder name : Raw_data_DNA_arrays.zip</p> <p>Number of files : 18 .cel files</p> <p> </p> <p>R script for DNA array analysis</p> <p>File name : Clean_Script.R</p>
Assembled "juvenile head region" transcriptome from the hagfish Eptatretus burgeri (NCBI GenBank Accession: SRX2541845)
<p>1) The raw reads were dwonloaded from NCBI GenBank (SRA run accession: (SRR5234495) with sratoolkit.</p> <p>2) The assembly was performed with Trinity with the folllowing parameters:</p> <p>Trinity --seqType fq --max_memory 100G --left eb-hf-head-region-SRR5234495/eb-hf-head-region-SRR5234495_1.fastq --right eb-hf-head-region-SRR5234495/eb-hf-head-region-SRR5234495_1.fastq --CPU 10 --output trinity-transcriptome-eb/</p> <p>3) ORFs were predeicted with TransDecoder with the following settings:</p> <p>TransDecoder.LongOrfs -t transcriptome-eb-hf-head-region.fasta</p> <p>TransDecoder.Predict -t transcriptome-eb-hf-head-region.fasta</p> <p> </p>
Transcriptome analysis of dark-induced bleaching octocoral
<h3>Transcriptome of dark-induced bleaching soft coral, <em>Lobophytum hsiehi</em></h3> <p>The raw transcriptomic data has been archived in NCBI BioProject under accession number PRJNA1037697.</p> <p>The transcript reads (transcript_sequence.fasta) deposited here were processed using Trinity, TransDecoder, and CD-HIT.</p> <p>The dataset (transcript_and_deg_information.xlsx) provided transcript annotations and results from the differential expression analysis.</p>
scDenorm: a denormalisation tool for Integrating Single-cell Transcriptomics Data
<p>Datasets and Jupyter notebooks to reproduce the analyses presented in the manuscript, scDenorm: a denormalisation tool for Integrating Single-cell Transcriptomics Data.</p>
Comparison of Fixed Single Cell RNA-seq Methods to Enable Transcriptome Profiling of Neutrophils in Clinical Samples - Time course data
<p>Monitoring neutrophil gene expression is a powerful tool for understanding disease mechanisms, developing new diagnostics, therapies and optimizing clinical trials. Neutrophils are sensitive to the processing, storage and transportation steps that are involved in clinical sample analysis. This study is the first to evaluate the capabilities of technologies from 10X Genomics, PARSE Biosciences, and HIVE (Honeycomb Biotechnologies) to generate high-quality RNA data from human blood-derived neutrophils. Our comparative analysis shows that all methods produced high quality data, importantly capturing the transcriptomes of neutrophils. 10X FLEX cell populations in particular showed a close concordance with the flow cytometry data. Here, we establish a reliable single-cell RNA sequencing workflow for neutrophils in clinical trials: we offer guidelines on sample collection to preserve RNA quality and demonstrate how each method performs in capturing sensitive cell populations in clinical practice.</p> <p><strong>This dataset includes only the 10X Flex time course data and analysis.</strong></p>
Analysis and visualization of the Fasciola hepatica spatial transcriptomics dataset
<p>This repository contains various files related to the analysis of the paper: Spatial transcriptomics of a parasitic flatworm provides a molecular map of drug targets and drug-resistance genes.</p>
Dataset and R script - Non-linear transcriptomic responses to compounded environmental changes across temperature and resources in a pest beetle, Callosobruchus maculatus
<p>This dataset contains data and R script for analysis on life history and transcriptomic responses to single dimensional changes in resource (chickpea-27<span>°</span>C) and temperature (cowpea-35<span>°</span>C) and multi-dimensional environmental changes in resource and temperature (chickpea-35<span>°</span>C) in a pest beetle, <em>Callosobruchus maculatus</em> (control treatment = cowpea-27<span>°</span>C). Dataset contains life history data collected in laboratory conditions<em> </em>(tab 1), logFC data (RNA-sequencing; Novogene Co. Ltd.) for Spearman rank correlation tests between treatments (tabs 2-4), read count data (RNA-sequencing; Novogene Co. Ltd.) for differential expression analysis using edgeR (R1-5 = Four samples at cowpea-27<span>°</span>C; R7-12 = Four samples at cowpea-35<span>°</span>C; R13-17 = Four samples at chickpea-27<span>°</span>C; R25-28 = Four samples at chickpea-35<span>°</span>C; tab 5) and edgeR output data for plotting in R (tab 6). </p>
Celiac-superior mesenteric ganglia (CG-SMG) spatial transcriptomics
<p>We prepared the spatial transcriptomics dataset for the celiac and superior mesenteric ganglia (CG-SMG) with 5 sections of 3 mice per Right (R)-CG, SMG, Left (L)-CG).</p>
Time series transcriptomes resolve metabolic pathways underlying crocin's anti-cancer activity | Dataset: sequencing reads (2,6,12,24 hr crocin treatments)
<p><span>Natural products like saffron show promise in treating hepatocellular carcinoma (HCC), but their mechanisms remain unclear. Here, we used time-series transcriptomics to elucidate crocin's anti-cancer mechanisms in HCC cells. We treated HepG2 cells with 1 and 2 mM crocin for 2, 6, 12, and 24 hours and analyzed transcriptomic profiles at each timepoint. The strongest transcriptional response occurred at 2 hours with 1 mM crocin, with diminishing effects at later timepoints. We observed upregulation of metabolic-, adhesion-, and endocytosis-related genes across all timepoints. Pathway analysis revealed activation of DNA damage checkpoints and senescence while proliferation pathways were suppressed. Notably, 52 genes involved in non-alcoholic fatty liver disease were downregulated at 24 hours (FDR p = 8 × 10⁻⁸), suggesting reversal of carcinogenic pathways. Strikingly, crocin consistently downregulated spliceosomal machinery genes across all timepoints while upregulating senescence and autophagy pathways. This spliceosome targeting represents a clinically relevant mechanism, as aberrant splicing drives oncogenesis in more than 90% of cancers. The transcription factor PAX5 was significantly upregulated while oncogenic ELK1 targets were downregulated. Our findings show that crocin treatment is accompanied by HCC cell senescence induction through coordinated spliceosome disruption and metabolic reprogramming, providing novel therapeutic targets for hepatocellular carcinoma.</span></p> <p><strong><span>Keywords: </span></strong><span>Hepatocellular carcinoma (HCC), crocin, transcriptomics, spliceosome, senescence, natural anti-cancer compounds</span></p>
Experiences of Discrimination are Associated with Microbiome and Transcriptome Alterations in the Gut
<p>Experiences of Discrimination are Associated with Microbiome and Transcriptome Alterations in the Gut. Human stool processed microbiome and transcriptomic data. </p>
Galleria larval transcriptome raw 454 data
<p>RNASeq dataset from </p> <p>Vogel, H., Altincicek, B., Glöckner, G. <em>et al.</em> A comprehensive transcriptome and immune-gene repertoire of the lepidopteran model host <em>Galleria mellonella</em>. <em>BMC Genomics</em> <strong>12</strong>, 308 (2011). https://doi.org/10.1186/1471-2164-12-308</p> <h1> </h1>
Dataset associated with A. Hallou, R. He, et al. A computational pipeline for spatial mechano-transcriptomics. bioRxiv 2023.08.03.551894
<p>Dataset associated with:</p> <p>Adrien Hallou, Ruiyang He, Benjamin David Simons and Bianca Dumitrascu. A computational pipeline for spatial mechano-transcriptomics. bioRxiv 2023.08.03.551894; doi: <a href="https://doi.org/10.1101/2023.08.03.551894">https://doi.org/10.1101/2023.08.03.551894</a></p> <p>Licence</p> <p>This dataset is licensed under the <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons Attribution-NonCommercial 4.0 International License</a>.</p>
Data and Analysis Files Repository: Repurposing Large-Format Microarrays for Scalable Spatial Transcriptomics
<p>Data and Analysis Files from "Repurposing Large-Format Microarrays for Scalable Spatial Transcriptomics"</p> <p>ArraySeq_Method.zip contains the following folder and contents:</p> <ul> <li>STARSolo: All code and count matrix output from fastq spatial barcode demultiplexing. </li> <li>Images: All resolution-downsampled H&E image scans from analyzed tissues</li> <li>Space_Ranger: All 10x Space Ranger output from Visium datasets generated in the paper. </li> <li>Analysis: All scripts for analyzing and plotting Array-seq and Visium datasets generated in this paper. Also contains output h5ad files. </li> </ul> <p>ArraySeq_Barcode_generation_n12.rmd: The script used to generate the Array-seq probes with 12-mer spatial barcodes. </p>
Gene Expression Transcriptomics Data for benchmarking Perturbation Models - Part 2
Open the record for dataset details and reuse information.
Comprehensive Transcriptomic Analysis of Spodoptera Frugi-perda Reveals Stage-Specific Gene Expression and P450-Mediated Adaptation Mechanisms
<p><em><span>Spodoptera frugiperda</span></em><span> is a highly adaptable agricultural pest with a complex life cycle, posing significant challenges to pest control. This study conducted a transcriptomic analysis across nine developmental stages, identifying 6,834 differentially expressed genes (DEGs) and 3,072 stage-specific genes (SSGs) critical for their development and adaptability. Significant gene expression shifts were observed during the transition from late larval stages to adulthood. Notably, a high number of SSGs in 6th instar larvae and adult males were enriched in pathways related to oxidative phosphorylation and neural signaling, indicating high metabolic and reproductive demands. Widely shared DEGs associated with ecdysone signaling and detoxification processes underscore robust adaptation mechanisms.</span></p>
Data from: Characterization of a male reproductive transcriptome for Peromyscus eremicus (Cactus mouse)
Rodents of the genus Peromyscus have become increasingly utilized models for investigations into adaptive biology. This genus is particularly powerful for research linking genetics with adaptive physiology or behaviors, and recent research has capitalized on the unique opportunities afforded by the ecological diversity of these rodents. Well characterized genomic and transcriptomic data is intrinsic to explorations of the genetic architecture responsible for ecological adaptations. Therefore, this study characterizes the transcriptome of three male reproductive tissues (testes, epididymis and vas deferens) of Peromyscus eremicus (Cactus mouse), a desert specialist. The transcriptome assembly process was optimized in order to produce a high quality and substantially complete annotated transcriptome. This composite transcriptome was generated to characterize the expressed transcripts in the male reproductive tract of P. eremicus, which will serve as a crucial resource for future research investigating our hypothesis that the male Cactus mouse possesses an adaptive reproductive phenotype to mitigate water-loss from ejaculate. This study reports genes under positive selection in the male Cactus mouse reproductive transcriptome relative to transcriptomes from Peromyscus maniculatus (deer mouse) and Mus musculus. Thus, this study expands upon existing genetic research in this species, and we provide a high quality transcriptome to enable further explorations of our proposed hypothesis for male Cactus mouse reproductive adaptations to minimize seminal fluid loss.
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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.