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3,801 results for “ATAC-seq”
Genomica ed Epigenomica Biocomputazionale: ATAC-seq Mesoderm differentiation data2
<p>Data collection of FastQ files used for teaching purposes.</p> <p>This subset was obtained from Koh, P., Sinha, R., Barkal, A. <em>et al.</em> An atlas of transcriptional, chromatin accessibility, and surface marker changes in human mesoderm development. <em>Sci Data</em> <strong>3</strong>, 160109 (2016). https://doi.org/10.1038/sdata.2016.109</p>
Single cell ATAC-seq Mouse Kidney Data: Chromatin-accessibility estimation from single-cell ATAC data with scOpen
<p>We provide results regarding the bioinformatic analysis of scATAC-seq from mouse UUO kidney at different time points.</p>
ATAC-seq Bioanalyzer profiles from iPSC-derived macrophages
<p>Agilent Bioanalyzer profiles for the iPSC-derived macrophage ATAC-seq samples. </p>
mimb_ATAC-seq
<p>Sample dataset for mimb_ATAC-seq</p>
Test data for running snakePipes : ATAC-seq workflow
<p><strong>Test files for running snakePipes workflows</strong></p> <p><strong>snakePipes</strong> are pipelines built using snakemake and python for the analysis of epigenomic datasets. Please refer to <a href="https://snakepipes.readthedocs.io/en/latest/">this link</a> for further information on snakePipes.</p> <p>This folder contains test files that can be used to run the ATAC-seq workflow under snakePipes. To test the workflow, follow the following steps : </p> <ul> <li>Download or prepare genome fasta, indices and annotations for fruit fly (<strong>dm6</strong>) genome.</li> <li>Download and install snakePipes via `conda create -n snakePipes -c mpi-ie -c bioconda -c conda-forge snakePipes`</li> <li>Update <a href="https://snakepipes.readthedocs.io/en/latest/content/running_snakePipes.html#genome-configuration-file">Genome configuration file</a> with path to indices and annotations.</li> <li>Move to this repository and run the example <strong>command.sh</strong></li> </ul>
ATAC-Seq (training data)
<p>Training dataset for a Galaxy ATAC-seq tutorial.</p>
ATAC-seq - Definitive endoderm differentiation of human pluripotent stem cells in G1 phase
<p>Backup copy of the processed ATAC-seq data at http://ngs.sanger.ac.uk/production/endoderm/</p>
Mapped ATAC-seq data for mock and HSV-1 strain 17 infection and infection with null mutants of HSV-1
<p>Sample annotation:</p> <table> <tbody> <tr> <td>Mock_1</td> <td>mock infection, replicate 1</td> </tr> <tr> <td>Mock_2</td> <td>mock infection, replicate 2</td> </tr> <tr> <td>WT_1</td> <td>HSV-1 wt, strain 17, replicate 1</td> </tr> <tr> <td>WT_2</td> <td>HSV-1 wt, strain 17, replicate 2</td> </tr> <tr> <td>WT_plus_PAA_1</td> <td>HSV-1 wt, strain 17, +PAA, replicate 1</td> </tr> <tr> <td>WT_plus_PAA_2</td> <td>HSV-1 wt, strain 17, +PAA, replicate 2</td> </tr> <tr> <td>dICP0_1</td> <td>HSV-1 lacking expression of ICP0, replicate 1</td> </tr> <tr> <td>dICP0_2</td> <td>HSV-1 lacking expression of ICP0, replicate 2</td> </tr> <tr> <td>dICP22_1</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 1</td> </tr> <tr> <td>dICP22_2</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 2</td> </tr> <tr> <td>dICP22_3</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 3</td> </tr> <tr> <td>dICP22_4</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, replicate 4</td> </tr> <tr> <td>dICP22_plus_PAA_1</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, +PAA, replicate 1</td> </tr> <tr> <td>dICP22_plus_PAA_2</td> <td>HSV-1 lacking expression of ICP22, HSV-1 strain F mutant R325, +PAA, replicate 2</td> </tr> <tr> <td>dICP27_1</td> <td>HSV-1 lacking expression of ICP27, KOS, replicate 1</td> </tr> <tr> <td>dICP27_2</td> <td>HSV-1 lacking expression of ICP27, KOS, replicate 2</td> </tr> <tr> <td>dVHS_1</td> <td>HSV-1 lacking expression of UL41, replicate 1</td> </tr> <tr> <td>dVHS_2</td> <td>HSV-1 lacking expression of UL41, replicate 2</td> </tr> </tbody> </table>
ATAC-seq and Stacc-seq bigwigs tracks of mouse preimplantation embryo
<p>ATAC-seq and Stacc-seq bigwigs tracks of mouse preimplantation embryo.</p> <p>ATAC-seq stages: early 2-cell + alpha amanitin, early 2-cell, 2-cell, 4-cell and 8-cell stage.</p> <p>Stacc-seq stages: MII oocyte, PN3 zygote, early 2-cell, 2-cell and 8-cell stage.</p> <p> </p> <p>bigWigs track were generated either by using all the reads (default) or by using only the reads overlapping significant ATAC/pol II binding site (as identified by Genrich, p<0.05). Since in these developmental stages the signal could be quite noisy, we believe that the latter set of bigWigs is more informative.</p> <p>To generate the latter set of peaks bamCoverage (<a href="https://deeptools.readthedocs.io/en/develop/content/tools/bamCoverage.html">https://deeptools.readthedocs.io/en/develop/content/tools/bamCoverage.html</a>) was used by providing to --blackListFileName a bed file containing all the regions of the mm10 genome not overlapping any significant ATAC/pol II peaks elongated at both ends by 1 kb.<br> <br> For further details see methods in Ansaloni et al., 2023, (link here reported upon publication).</p>
Training material for the mapping and quantification of single-cell ATAC-seq 10X Datasets
<p>The data provided here is part of the Galaxy Training Network tutorial that analyses 10x genomics single-cell ATAC-seq data from the 10x platform. </p> <p>Due to time constraints during training, the datasets were subsampled to reads that map to chrY.</p> <p>The 10x Genomics Datasets follow the <a href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution</a> license.</p>
CrossMP: Enabling Cross-Modality Translation between Single-Cell RNA-Seq and Single-Cell ATAC-Seq through Web-Based Portal - Appendix
Open the record for dataset details and reuse information.
RUNX1 loss renders hematopoietic and leukemic cells dependent on interleukin-3 and sensitive to JAK inhibition [ATAC-seq]
GEO Series GSE231950. Homo sapiens. 11 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
mouse RNA-seq, human RNA-seq, ATAC-seq, and scRNA-seq analyses data
GEO Series GSE224702. Homo sapiens; Mus musculus. 45 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing.
The pioneer factor SOX9 competes for epigenetic factors to switch stem cell fates [ATAC-Seq]
GEO Series GSE208066. Mus musculus. 24 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Functional reprogramming of monocytes in acute and convalescent severe COVID-19 patients [ATAC-seq]
GEO Series GSE198255. Homo sapiens. 30 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Next Generation Sequencing profile of leukemia from distinct cells-of-origin [ATAC-seq]
GEO Series GSE81805. Mus musculus. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
ATAC-seq from HG02623 (ENCSR821JHD)
GEO Series GSE172722. Homo sapiens. 1 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
ATAC-seq from pancreas (ENCSR705KEB)
GEO Series GSE169809. Homo sapiens. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Unbiased profiling of clinical kinase inhibitors’ effects in activated macrophages using chromatin modifications as high-content readouts [ATAC-Seq]
GEO Series GSE218966. Mus musculus. 18 samples. Type: Other.
ATAC-seq from gastroesophageal sphincter (ENCSR670REK)
GEO Series GSE170959. Homo sapiens. 1 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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