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.
3,818
datasets available to search
ShareScore release 0.9.0
Dataset results
3,818 results for “Differential Expression”
Correspondence on Li Yumei et al.: Exaggerated false positives by popular differential expression methods when analyzing human population samples.
<p>Scripts for manuscript</p>
Comparative analysis of differential gene expression indicates divergence in ontogenetic strategies of leaves in two conifer genera
<p><em>Juniperus flaccida</em> (drooping juniper) and <em>Pinus cembroides</em> (pinyon pine) are conifers native to North America, spanning Mexico and the Southwestern region of the United States. Although from two different lineages, both species exhibit heteroblastic growth. Morphologically, their leaves undergo a change between the juvenile and adult life stage. <em>J. flaccida</em> leaves appear needle-like at youth and scale-like at maturity, whereas the <em>P. cembroides</em> will transition from needle-like leaves to brown scale-like leaves. The objective was to perform a comparative transcriptomic analysis to quantify and examine differential expression in juvenile and adult individuals from both species. RNA from twelve samples was sequenced on HiSeq 1500 (100bp PE) and analyzed with available software. Because there are no reference genomes for these species, they were assembled<em> de novo </em>from the RNA-Seq reads. Following assembly, the coding regions were identified and redundant transcripts were removed. Quality filtered reads were aligned to the reference transcriptomes (one for each species), counts were generated from the alignment files, and differential expression analysis was performed with DESeq2 via Kallisto. Up and down-regulated genes (padj<0.1) across both age classes (juvenile vs adult) were observed in each species and compared.</p>
Time-series transcriptome analysis identified differentially expressed genes in broiler chicken infected with mixed Eimeria species
<p>Coccidiosis caused by the <em>Eimeria</em> species is a highly problematic disease in the chicken industry. Here, we used RNA sequencing to observe the time-dependent host responses of <em>Eimeria</em>-infected chickens to examine the genes and biological functions associated with immunity to the parasite. Transcriptome analysis was performed at three time points: 4, 7, and 21 days post-infection (dpi). Based on the changes in gene expression patterns, we defined three groups of genes that showed differential expression. This enabled us to capture evidence of endoplasmic reticulum stress at the initial stage of <em>Eimeria</em> infection. Furthermore, we found that innate immune responses against the parasite were activated at the first exposure; they then showed gradual normalization. Although the cytokine-cytokine receptor interaction pathway was significantly operative at 4 dpi, its downregulation led to an anti-inflammatory effect. Additionally, the construction of gene co-expression networks enabled identification of immunoregulation hub genes and critical pattern recognition receptors after <em>Eimeria</em> infection. Our results provide a detailed understanding of the host-pathogen interaction between chicken and <em>Eimeria</em>. The clusters of genes defined in this study can be utilized to improve chickens for coccidiosis control.</p>
S1_The_differentially_expressed_genes_enriched_in_GO_clusters
<p>This is supporting information to the article <em>Downregulation of ammonium uptake improves the growth and tolerance of Kluyveromyces marxianus at high temperature</em>, which has been submitted to <em>MicrobiologyOpen</em>.</p>
On taming the effect of transcript level intra-condition count variation during differential expression analysis: a story of dogs, foxes and wolves: Bowtie2 counts and kallisto abundances
<p>Intra [1] and inter [2-5] study RNA-seq read datasets representing the varying brain compartments of foxes (n=24), as well as dogs (n=14) and wolves (n=6), as described in Lobo <em>et al.</em>, (2022) (under review), were mapped to the dog reference transcriptome [6], which contained 26,107 annotated transcripts (Ensembl CanFam3.1, release 92) [7], using Bowtie2 v.2.3.4.1 [8] and using kallisto v0.46.1 [9]. Count data obtained following each mapping approach for each dataset had high correlations (Lobo <em>et al.</em>, Figure S2). Bowtie2 counts were subsequently used in multiple differential analysis experiments in order to explore the effects of intra-condition count variation on the detection of differentially expressed transcripts. The individual count and abundance datasets for each corresponding RNA-seq dataset are available here.</p> <p> </p> <p>A preprint of Lobo et al., 2022, currently under review for PLOS ONE, is available [10]. The preprint however does not contain reviewer requested information on simulations as this, along with other additions including an additional author RL, has been subsequently added during the review process. These additions will be made available following review via a link to the final paper. </p> <p> </p> <p>Related software to this project are:<br> 1. <a href="http://sourceforge.net/projects/cstone/">CStone</a> <br> 2. <a href="http://sourceforge.net/projects/csreadgen/">CSReadGen</a><br> 3. <a href="https://sourceforge.net/projects/cview/">CView</a> <br> 4. <a href="https://sourceforge.net/projects/chimsim/">ChimSim</a><br> 5. <a href="https://sourceforge.net/projects/tvscript/">TVScript</a> <</p> <p> </p> <p>General details of the projects involved are available: <a href="https://cibio.up.pt/en/projects/is-hybridization-between-wolves-and-dogs-shaping-the-evolutionary-trajectory-of-wolf-populations-in-human-dominated-landscapes/">dog-wolf</a> and <a href="https://cibio.up.pt/en/projects/de-novo-based-sequence-assembly-of-next-generation-sequence-data-without-chimeras-improved-annotation-gene-expression-profiles-and-haplotype-br-reconstruction/">chimerism</a>.</p> <p> </p> <p><strong>References</strong></p> <p>1. Wang X, Pipes L, Trut L, Herbeck Y, Vladimirova A, Gulevich R, et al. Genomic responses to selection for tame/aggressive behaviors in the silver fox (Vulpes vulpes). Proc Natl Acad Sci. 2018;115: 10398–10403. doi:10.1073/pnas.1800889115</p> <p> </p> <p>2. Roy M, Kim N, Kim K, Chung WH, Achawanantakun R, Sun Y, et al. Analysis of the canine brain transcriptome with an emphasis on the hypothalamus and cerebral cortex. Mamm Genome. 2013;24: 484–499. doi:10.1007/s00335-013-9480-0</p> <p> </p> <p>3. Fushan AA, Turanov AA, Lee SG, Kim EB, Lobanov A V, Yim SH, et al. Gene expression defines natural changes in mammalian lifespan. Aging Cell. 2015;14: 352–365. doi:10.1111/acel.12283</p> <p> </p> <p>4. Hoeppner MP, Lundquist A, Pirun M, Meadows JRS, Zamani N, Johnson J, et al. An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts. PLoS One. 2014;9(3):91172. doi:10.1371/journal.pone.0091172</p> <p> </p> <p>5. Albert FW, Somel M, Carneiro M, Aximu-Petri A, Halbwax M, Thalmann O, et al. A Comparison of Brain Gene Expression Levels in Domesticated and Wild Animals. Akey JM, editor. PLoS Genet. 2012;8:e1002962. doi:10.1371/journal.pgen.1002962</p> <p> </p> <p>6. Hoeppner MP, Lundquist A, Pirun M, Meadows JRS, Zamani N, Johnson J, et al. An improved canine genome and a comprehensive catalogue of coding genes and non-coding transcripts. PLoS One. 2014;9(3):91172. doi:10.1371/journal.pone.0091172</p> <p> </p> <p>7. Yates AD, Achuthan P, Akanni W, Allen J, Allen J, Alvarez-Jarreta J, et al. Ensembl 2020. Nucleic Acids Res. 2020;48: D682–D688. doi:10.1093/NAR/GKZ966</p> <p> </p> <p>8. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012. doi:10.1038/nmeth.1923</p> <p> </p> <p>9. Bray NL, Pimentel H, Melsted P, Pachter L. Near-optimal probabilistic RNA-seq quantification. Nat Biotechnol 2016 345. 2016;34: 525–527. doi:10.1038/nbt.3519</p> <p> </p> <p>10. Lobo D, Godinho R, Archer JP. On taming the effect of transcript level intra-condition count variation during differential expression analysis: a story of dogs, foxes and wolves. bioRxiv. 2022; 2022.01.24.477470. doi:10.1101/2022.01.24.477470</p>
Data for: Differentially expressed genes comparing WT plants vs xal1-2
<p><span>The balance between cell proliferation, differentiation, and elongation rates emerge from regulatory gene differentiation networks coupled to various signal transduction pathways, including those of reactive oxygen species (ROS). The <em>Arabidopsis thaliana</em> primary root has become a useful system to unravel such networks, as well as their interaction with signals that alter organ growth. The role of transcription factors, that regulate organ development, in mediating the role of ROS in root growth is just beginning to be studied. Here, we report that the MADS-box transcription factor <em>XAANTAL1</em> (<em>XAL1</em>) mediates hydrogen peroxide (H<sub>2</sub>O<sub>2</sub>) role in primary root growth and it is involved in the morphogenesis of the columella stem cell differentiation in response to H<sub>2</sub>O<sub>2</sub>. Interestingly, our data suggest that <em>XAL1</em> is a positive regulator of H<sub>2</sub>O<sub>2</sub> concentration in the root meristem via regulating transcript accumulation of several peroxidases. Moreover, we found that <em>XAL1</em> is necessary for the H<sub>2</sub>O<sub>2</sub>-induced inhibition of primary root growth through the negative regulation activities of the peroxidases and catalases. Furthermore, <em>XAL1</em> and <em>RETINOBLASTOMA-RELATED</em> (<em>RBR</em>) are also necessary to positively regulate columella stem cell differentiation that is triggered by moderate H<sub>2</sub>O<sub>2</sub> treatments. </span></p>
List of differential expressed genes for the different conditions
Open the record for dataset details and reuse information.
Genes with differential expression across ancestries are enriched in ancestry-specific disease effects likely due to gene-by-environment interactions
<p>This repository contains raw data, preprocessing scripts, and analysis code to replicate S-LDXR analysis from Wang et al.</p> <p>The project directory is organized as follows:<br>- `compute_de.r`: The script to compute anc-de genes<br>- `create_annot.100kb.sh`: code to create annotations for S-LDXR<br>- `create_annot.r`: R function used to create annotations for S-LDXR<br>- `DEstats.tgz`: Differential gene expression statistics between EAS and EUR for each 7 main cell types + PCs of each cell within each cell type<br>- `list_genes.txt`: Gene list as QCed as in Gazal et al. 2022 Nat Genet<br>- `Lupus_study_adjusted_compressed.h5ad.gz`: The single-cell dataset of Perez*, Gordon*, Subramaniam* et al. 2022 Science used in this study<br>- `README.sh`: This README file<br>- `sldxr_annotations.tgz`: Main S-LDXR annotations used in this study<br>- `sldxr_ref_files.tgz`: S-LDXR reference files (baseline-LD-X annotations, regression weights and EAS and EUR 1000G genotype reference files)<br>- `sumstats.tgz`: GWAS summary statistics of 31 traits in EAS and EUR populations<br>- `code_figures.tgz`: Code files for main figures</p>
Dataset for Improved differential expression analysis of miRNA-seq data by modeling competition to be counted
Open the record for dataset details and reuse information.
Raw data and metadata associated with the manuscript: "Organ and ontogeny-specific steroidal glycoside diversity is associated with differential expression of steroidal glycoside pathway genes in two Solanum dulcamara leaf chemotypes"
<p>Raw LC-MS and RT-qPCR data and metadata associated with the manuscript: "Ontogeny and organ-specific steroidal glycoside diversity is associated with differential expression of steroidal glycoside pathway genes in two <em>Solanum dulcamara</em> leaf chemotypes", accepted at Plant Biology.</p>
Differential gene expression results from DESeq2
<p>Differential gene expression results from DESeq2</p>
Datasets for : High-resolution detection and differential expression analysis of transcription start sites using MAPCap
<p>This dataset corresponds to the study: High-resolution detection and differential expression analysis of transcription start sites using MAPCap (Bhardwaj et. al. 2018)</p> <p>It includes:</p> <p> - TSS identified using MAPCap in stage 15 embryos and larvae.</p> <p> - Differentially expressed TSS using MAPCap (FDR < 0.05) in larvae.</p> <p> - Common and stage-specific enhancer TSS identified in this study</p>
Differential Gene Expression Dataset of Thalassiosira hyalina and Nitzschia frigida: Response to light stress under contemporary and elevated pCO2
<p>This is a time-course gene expression dataset on the transcriptomic responses of <em>Thalassiosira hyalina</em> and <em>Nitzschia frigida</em> to light stress under contemporary and elevated 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>
Fig. 5 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 5 Differential transcript expression analysis. Bar charts represent the enriched molecular functions associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 4 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 4 Differential transcript expression analysis. Bar charts represent the enriched biological processes associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Fig. 2 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 2 Scheme of the methodology employed in this study. In a first approach, the reference transcriptome (workflow in grey) was assembled de novo from three distinct life cycle stages: the feeding stage alone (asexual generation; note that in young feeding stages, the buccal funnel is located inside in the trunk), the feeding stage with Prometheus larva(e) attached to its trunk (sexual generation) and the free-swimming chordoid larva. Secondly, in the differential gene expression analysis (workflow in black), only two different conditions were investigated: feeding stages with Prometheus larva(e) attached to its trunk and feeding stages alone. Finally, sequenced reads were mapped to the reference transcriptome
Fig. 6 in Transcriptome profiling of Symbion pandora (phylum Cycliophora): insights from a differential gene expression analysis
Fig. 6 Differential transcript expression analysis. Bar charts represent the enriched cellular components associated with the upregulated genes in a feeding stages with Prometheus larva(e) and b feeding stages alone
Single cell RNA-seq data from: Differentiation signals induce APOBEC3A expression via GRHL3 in squamous epithelia and squamous cell carcinoma
<p>Seurat object for single cell RNA-seq of 10 head and neck squamous cell carcinoma patients, epithelial cells only. From "Differentiation signals induce APOBEC3A expression via GRHL3 in squamous epithelia and squamous cell carcinoma ". <span><span>Two APOBEC (apolipoprotein-B mRNA editing enzyme catalytic polypeptide-like) </span><span>DNA </span><span>cytosine deaminase enzymes (APOBEC3A and APOBEC3B) generate somatic mutations in cancer, driving tumour development and drug resistance. Here we used single cell RNA sequencing to study </span></span><span><span>APOBEC3A</span></span><span><span> and </span></span><span><span>AP</span><span>OB</span><span>EC3B</span></span><span><span> expression in healthy and malignant mucosal epithelia, </span><span>validating</span> <span>key</span><span> observations </span><span>with</span><span> immunohistochemistry, spatial </span><span>transcriptomics</span><span> and functional experiments. Wh</span><span>ereas</span> </span><span><span>APOBEC3B</span></span><span><span> is expressed in keratinocytes entering mitosis, we show that </span></span><span><span>APOBEC3A</span></span><span><span> expression is confined</span> <span>largely</span><span> to</span><span> terminally differentiating cells</span><span> and </span><span>requires </span><span>Grainyhead</span><span>-like transcription factor 3 (GRHL3). T</span><span>hus</span><span>, in normal tissue,</span><span> neither </span><span>deaminase</span> <span>appears to be</span><span> expressed at </span><span>high levels</span><span> during DNA replication, the c</span><span>ell cycle stage</span> <span>associated with</span><span> APOBEC-mediated mutagenesis. </span><span>In</span><span> contrast, we show that in squamous cell carcinoma, there is expansion of </span></span><span><span>GRHL3</span></span><span> <span>expression and </span><span>activity to a subset of cells undergoing DNA replication and concomitant extension of </span></span><span><span>APOBEC3A</span></span><span><span> expression to proliferating cells. </span></span><span><span>These findings </span><span>suggest</span><span> that</span> <span>APOBEC3A</span><span> may play a functional role during keratinocyte differentiation</span><span> and offer</span> </span><span><span>a mechanism for acquisition of APOBEC3A mutagenic activity in tumour</span><span>s</span><span>.</span></span><span> </span></p>
PCOS Combined with Obesity Aggravates the Metabolic and Immune Abnormality in Females Supplement_2_Differentially_expressed_statistics_Metabolomics
<p><span>This table represents the data of Figure 3/4. In this table, we show all the metabolites measured. Meanwhile, we show the anion mode and the cation mode separately, and on this basis, we count the differential metabolites between different combinations of PO/PN/NPN/NPO.<br>Differential metabolites were screened by fold change &gt. 1.5 or less than 0.67.</span></p>
Data from: De novo assembly of a tadpole shrimp (Triops newberryi) transcriptome and preliminary differential gene expression analysis
Next-generation sequencing techniques, such as RNA sequencing, have provided a wealth of genomic information for nonmodel species. Transcriptomic information can be used to quantify the patterns of gene expression, which can identify how environmental differences invoke organismal stress responses and provide a gauge in predicting species adaptability. In our study, we used RNA sequencing to characterize the first transcriptome from a naupliar tadpole shrimp (Triops newberryi) to identify the genes expressed during the early life history stages and which could be important for future genomic studies. RNA was extracted from naupliar T. newberryi that were reared in a laboratory-controlled setting and in two different water types, a native and a non-native condition. A total of six replicates, three per condition, were sequenced with the Illumina Hi-Seq 2000 achieving 365 M 50-nt reads. High-quality reads were produced and de novo assembly was used to construct a T. newberryi transcriptome that was approximately 24.8 M base pairs. More than 10 000 peptides were predicted from the assembly, and genes were sorted into gene ontology categories. The use of different water conditions allowed for a preliminary differential gene expression analysis in order to compare the changes in gene expression between conditions. There were 299 differentially expressed genes between water conditions that might serve as a focal point for future genomic studies of Triops acclimation to different environments. The Triops transcriptome could serve as vital genomic information for additional studies on Branchiopod crustaceans.
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.