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65 results for “C.elegans”
Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes - Supplementary Tables
<p>This repository contains the Supplementary Tables for Suriyalaksh et al. Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes.</p> <p>The list of table files can be found in <a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/Supplementary%20table%20guide.pdf">Supplementary Tables guide.pdf</a></p> <p>Tables S1, S2 and S3 corresponding to physical gene-gene interaction data are in a separate repository doi:10.5281/zenodo.4382337</p> <p>Details about some of the Supplementary tables:</p> <p>TableS4_inferred_networks.csv - list of inferred GRNs for specified input combinations (set of input regulators, length of the time sequence, NI tool and prior used).</p> <p><a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/TableS5_consensus_network_member.xlsx">TableS5_consensus_network_member.xlsx</a> - list of groups of topologically similar GRNs (from Table S4)</p> <p>Table S6: edge lists (source,target) for each one of the three consensus networks selected according to the GS validation metrics: middle PFE/AUFE, max AUFE, max PFE.<br> TableS6a_max_AUFE_GRN.txt - max AUFE; largest network - this is the one we used in the main analysis and discussion<br> TableS6b_max_PFE_GRN.xt - max PFE<br> TableS6c_middle_AUFE_PFE_GRN.txt - middle PFE/AUFE</p> <p><a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/TableS7_qRTPCR_ddCt_network_accuracy.csv">TableS7_qRTPCR_ddCt_network_accuracy.csv</a> - gene expression count differences for RNAi knockdown GRN validation experiments. </p> <p>Table S8: Group membership for each one of the nodes in each one of the selected networks according to the SBM that best describes the observed network topology. Each column shows the group membership for each level in a SBM block hierarchy. Our analysis is in the second most coarse-grained level (level 1).</p> <p>TableS8a_max_AUFE_SBM.csv<br> TableS8b_max_PFE_SBM.csv<br> TableS8c_middle_AUFE_PFE_SBM.csv</p> <p><a href="https://zenodo.org/api/files/431155b3-c2b2-4fff-92bb-e93cad8bf5c2/TableS9_glp_gs_datasets.pdf">TableS9_glp_gs_datasets.pdf</a> - list of datasets used for defining functional clusters.</p> <p>TableS14a_glp_l1_vs_fem_l1_lifespan_assay.xlsx - Day13 survival of fem-3(q20)ts vs day 19 survival of glp-1(e2144)ts;rrf-3(pk1426) RNAi from L1</p> <p>TableS14b_glp_l1_vs_glp_l4_lifespan_assay.xlsx - Day 19 survival of glp-1(e2144)ts;rrf-3(pk1426) RNAi from L4 vs day 19 survival of glp-1(e2144)ts;rrf-3(pk1426) RNAi from L1</p> <p>TableS15a_glp1_in_vivo_fluorescence_data.xlsx - in vivo fluorescent reporter data of glp-1(e2144)ts;rrf-3(pk1426)</p> <p>TableS15b_fem3_in_vivo_fluorescence_data.xlsx - in vivo fluorescent reporter data of fem-3(q20)ts</p> <p>TableS17_input_regulators_annotated.csv - list input regulators used as input for Network Inference Tools annotated by source type (2nd column): GenAge, known transcription factors (TF) and gene with high variability in the gene expression time series (HV). The third column lists whether that regulator has an orthologue in human (y) according to WormBase (v 278).</p> <p>TableS20_epistasis_lifespan_data.xlsx - Epistasis lifespan data of glp-1(e2144)ts</p> <p>All the image (TIF) files represent representative images in the following genetic backgrounds (below) that have been treated </p> <p>with empty vector (EV) or RNAi against the gene highlighted in the title of the image. See methods section for details. </p> <p><strong>femliu1: </strong></p> <p><em>fem-3(q20)ts.; dhs-3p::dhs-3::gfp</em></p> <p><strong>femsod3:</strong></p> <p><em>fem-3(q20)ts.; sod-3p::gfp</em></p> <p><strong>glp1lgg1:</strong></p> <p><em>glp-1(e2144); lgg-1p:lgg-1:gfp</em></p>
Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes - Database of Physical gene-gene Interactions in young adult C.elegans.
<p>This repository contains Supplementary Information for manuscript Suriyalaksh et al Gene Regulatory Network inference in long lived C.elegans reveals modular properties that are predictive of novel ageing genes corresponding to the curation of physical gene-gene interactions for young adult C elegans worms </p> <p>We manually curated 239,001 regulatory interactions from 289 young adult wild-type (WT) C.elegans datasets, consisting of 126 genes and 495 unique transcription factors (see TableS1_datasets_for_prior.csv for references). </p> <p>This repository contains 3 different files:</p> <p>TableS1_datasets_for_prior.csv - contains datasets used as sources for physical gene-gene or TF-gene interactions</p> <p>TableS2_physical_priors.xlsx - contains three tabs:<br> ChIPATAC - contains physical TF-gene interactions from 115 L4 or young-adult ChIP-seq datasets from modERN (Kudron et al., 2018) + ChIP-seq datasets (GSE28350, GSE81521) from (Hochbaum et. al, 2011, Li et. al, 2016).</p> <p>eY1HATAC- contains 3,501 TF-gene interactions from eY1H assay by Fuxman Bass et al. (2016).</p> <p>motifATAC - contains 202 unique TF DNA recognition motifs using “direct evidence” option from CiS-BP motif database (Weirauch et al., 2014), obtained through RTFBSDB R package (Wang et al., 2016) - see TableS1</p> <p>TableS3_WT_functional_priors.csv - contains functional knockdown data that we use as gold standard to validate inferred networks in Suriyalaksh et al. (see TableS1_datasets_for_prior.csv for sources)</p> <p>---</p> <p>Description of methodology to obtain regulatory interactions in TableS2:</p> <p>Regulatory sequences for each gene were acquired from ENSEMBL (Aken et al., 2017), obtained using biomaRt R package (accessed on 31st Oct 2017). This study used WBcel235/ce11 version of the C. elegans genome, and WormBase WS260 genome annotations.</p> <p>For motifs, TFs whose motifs overlapped with an open ATAC-seq region by at least one base pair were kept. For ChIP-seq, TF binding sites that overlapped with an open ATAC-seq region by at least one base pair were kept using bedtools intersect and bedtools merge commands.</p> <p>An interaction from a TF to a gene was inferred by aligning transcription start sites (TSS) using bedtools window commands with 1000 bp window size to the TF-binding locations from ChIP-seq and motifs.</p> <p>For eY1H data, an interaction is included if the TSS site of the target gene overlaps with an open ATAC-seq region by at least one base pair.</p> <p>For gene-gene interactions, of the 298 studies compiled in WormExp v1.0 database (Yang et al, 2016, updated 27/07/16), 98 studies were included in the database spanning 126 different genes (see Table S1 in this repository).</p>
C.elegans embryo early development tracked with TrackMate
<p><em>C.elegans</em> embryo early development.</p> <p>This movie is a maximum-intensity projection (MIP) of a longer movie used initially in:</p> <blockquote> <p>Tinevez JY, Dragavon J, Baba-Aissa L, Roux P, Perret E, Canivet A, Galy V, Shorte S. A quantitative method for measuring phototoxicity of a live cell imaging microscope. Methods Enzymol. 2012;506:291-309. doi: 10.1016/B978-0-12-391856-7.00039-1. PMID: 22341230.</p> </blockquote> <p>This is very short movie, that stops after the 2nd cell division. We made a MIP so that this movie can be used in a tutorial to demonstrate the usage of the mask detector in TrackMate.</p> <p>The dataset includes the TrackMate XML file resulting from tracking this movie.</p> <p> </p>
C.elegans developing embryo (ELEPHANT demo dataset)
<p>This data is a short subset of one of the training data from the Cell Tracking Challenge (http://celltrackingchallenge.net/) formatted in BigDataViewer format.</p> <p>Dataset name: C.elegans developing embryo</p> <p>Training data#: 01</p> <p>Timepoints: t050 - t059</p> <p>See details here (http://celltrackingchallenge.net/3d-datasets/).</p> <p>The use of the data is limited for testing the ELEPHANT software.</p> <p><strong>Acknowledgements</strong></p> <p>We are grateful to Robert H. Waterston for kindly giving us a permission to distribute this data for testing the ELEPHANT software.</p> <p><strong>Original paper</strong></p> <p>Murray, J., Bao, Z., Boyle, T. <em>et al.</em> Automated analysis of embryonic gene expression with cellular resolution in <em>C. elegans</em>. <em>Nat Methods</em> <strong>5, </strong>703–709 (2008). https://doi.org/10.1038/nmeth.1228</p>
Expression Data from International C.elegans Experiment 1st
The effect of microgravity on gene expression in C.elegans was comprehensively analysed by DNA microarray. This is the first DNA microarray analysis for C.elegans grown under microgravity. Hyper gravity and clinorotation experiments were performed as reference against the flight experiment.
Transgenerational inheritance of an acquired small RNA-based antiviral response in C.elegans
GEO Series GSE33334. Caenorhabditis elegans. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Identification of transcription factor CEH-14 binding sites in C.elegans
GEO Series GSE17454. Caenorhabditis elegans. 3 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
ChIP-seq of UNC-30 and UNC-55 in C.elegans
GEO Series GSE102213. Caenorhabditis elegans. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Pol III transcribed genes, RNA-Seq, C.elegans
GEO Series GSE232720. Caenorhabditis elegans. 6 samples. Type: Non-coding RNA profiling by high throughput sequencing.
RNA-seq for C.elegans lin-52 vs N2 (UV & non-UV)
GEO Series GSE152235. Caenorhabditis elegans. 12 samples. Type: Expression profiling by high throughput sequencing.
(6-4)PP and CPD Damage-seq data for L1 stage wildtype, csb-1 and xpc-1 C.elegans
GEO Series GSE280347. Caenorhabditis elegans. 24 samples. Type: Other.
Differentially expressed genes between C.elegans with low physical ability and with high physical ability
GEO Series GSE99020. Caenorhabditis elegans. 4 samples. Type: Expression profiling by array.
The high-throughput cleavage assays on 137 C.elegans pri-miRNAs
GEO Series GSE212229. Caenorhabditis elegans. 6 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Analysis of small RNA response to viral infection in C.elegans
GEO Series GSE41693. Caenorhabditis elegans. 24 samples. Type: Non-coding RNA profiling by high throughput sequencing.
RNA sequencing of wild type C.elegans exposed to Haptoglossa zoospora for 6 or 12 hours
GEO Series GSE175950. Caenorhabditis elegans. 11 samples. Type: Expression profiling by high throughput sequencing.
Gene expression profile of N2 and HPX-2 mutant C.elegans strains when exposed to E.coli and E.faecalis
GEO Series GSE124372. Caenorhabditis elegans. 16 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis of wild-type and lin-22 mutants in C.elegans
GEO Series GSE101645. Caenorhabditis elegans. 12 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
A microRNA microarray analysis of C.elegans Parkinsons disease models
GEO Series GSE14899. Caenorhabditis elegans. 12 samples. Type: Non-coding RNA profiling by array.
Identification of transcription factor EOR-1 binding sites in C.elegans
GEO Series GSE17456. Caenorhabditis elegans. 4 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Mitochondrial Metabolism Shifts Characterized by Quantitative Mass Spectrometry in Insulin Signaling-regulated Longevity of C.elegans
GEO Series GSE274456. Caenorhabditis elegans. 18 samples. Type: Expression profiling by high throughput sequencing.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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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.