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4,529 results for “drosophila”
Formatting hemiclone Drosophila melanogaster genotype data for GWAS
<p>Data and code for generating filtering and formatting of Drosophila melanogaster genotype data, from the Sussex LHM hemiclone population sample.</p>
Population genomics of Sussex LHM Drosophila melanogaster
<p>Input data, code, output data, summary plots, and run logs for investigation of the population genetics of the Drosophila melanogaster Sussex LHM sample.</p> <p>For output graphs, see popgen_plots.png</p> <p>Input data are 'plink binary' format.</p> <p>Code is a unix/linux shell script containing commands for Plink to perform population genetic tests.</p> <p>The two R scripts contain i. a short command for making a subpopulation file, ii. commands for plotting the output data. Both are initated in the shell script.</p> <p>Platform and version information are available in the log files. Other information available in the shell and R scripts.</p> <p>Broad observations are that the allele frequency disibribution is normal except a few humps around MAF 0.2-0.3 in the autosomes.</p> <p>Linkage disequilbrium, on average, levels-out after ~200bp but there can still be some at distances of 300Kb.</p> <p>The population appears to be divided into four genetically distinct groups (on the IBD-PCA scatter plot), with Fst analysis indicating that this is caused by genetic variation around the centromeres. This is possibly caused by historic admixture, and low centromeric recombination.</p>
Multiplexed DNA-FISH imaging dataset, drosophila embryos, nuclear cycles 11-14
<p>Multiplexed DNA-FISH imaging dataset from Drosophila embryos at nuclear cycles 11-14.</p> <p>Examples on how to load and use this dataset can be found at this <a href="https://github.com/NollmannLab/Goetz_etal">GitHub repository</a>.</p> <p><strong>Data processing details</strong></p> <p>Barcodes were segmented using a neural network (<a href="https://github.com/stardist/stardist"><em>stardist</em></a>) specifically trained for the detection of 3D diffraction limited spots produced by our microscope. To extract the position of the barcode with sub-pixel accuracy, a subsequent 3D Gaussian fit of the regions segmented by <em>stardist</em> was performed with Big-FISH (<a href="https://github.com/fish-quant/big-fish">https://github.com/fish-quant/big-fish</a>). Barcode localizations with intensities lower than 1.5 times that of the background were filtered out.</p> <p>Nuclei were segmented from projected DAPI images using <em><a href="https://github.com/stardist/stardist">stardist</a> </em>with a neural network trained for detection of nuclei from <em>Drosophila</em> embryos under our imaging conditions. Barcodes were then attributed to single nuclei by using the XY coordinates of the barcodes and the DAPI masks of the nuclei. Finally, pairwise distance matrices were calculated for each single nucleus.</p> <p><strong>Processed data in Figures</strong></p> <p>This new version of the dataset contains the raw data for each of the figures in the manuscript:</p> <p><strong>Associated publication</strong></p> <p><strong>Multiple parameters shape the 3D chromatin structure of single nuclei at the doc locus in </strong><em>Drosophila</em>.</p> <p>Markus Götz, Olivier Messina, Sergio Espinola, Jean-Bernard Fiche, Marcelo Nollmann</p> <p>Nature Communications (2022).</p>
Fluorescent Macrophages in Drosophila Embryo
<p>This is a data set that contains a time sequence of<strong> fluorescently labelled macrophages</strong> that migrated in a<strong> drosophila embryo</strong>.</p> <p>The macrophages were visualised in the embryo by using the UAS/GAL4 system.We used the srpHemo-Gal4driver,which mediate the expression of genes downstream of a UASsequence specifically in macrophages to express the following UAS fluorescent probes: UAS-RedStinger for the nuclei and UAS-Clip-GFP for the microtubules.</p> <p>Details of the imaging and preparation have been published in:</p> <p> </p> <ul> <li>Evans, I.R.; Zanet, J.; Wood, W.; Stramer, B.M.<em> Live imaging of Drosophila melanogaster embryonic339hemocyte migrations.Journal of visualized experiments:</em> JoVE2010,36.</li> </ul> <p> </p> <p>Details on the segmentation, tracking and analysis of the macrophage migration have been published in:</p> <ul> <li>José Alonso Solís-Lemus, Besaiz J Sánchez-Sánchez, Stefania Marcotti, Mubarik Burki, Brian Stramer, Constantino Carlos Reyes-Aldasoro, <em>Comparative study of contact repulsion in control andmutant macrophages using a novel interaction detection</em>, Journal of Imaging, BioRxiv, https://doi.org/10.1101/2020.03.31.018267</li> </ul> <p>and</p> <ul> <li>Solís-Lemus, J.A.; Stramer, B.; Slabaugh, G.; Reyes-Aldasoro, C.C. <em>Macrosight: A Novel Framework to Analyze the Shape and Movement of Interacting Macrophages Using Matlab</em>.Journal of Imaging 2019,5</li> </ul> <p> </p>
Data from: "Rapid molecular evolution of Spiroplasma symbionts of Drosophila"
<p>This repository contains data and information to reproduce the findings reported in the paper.</p> <p>File descriptions:</p> <ul> <li>OTU_sequences.fasta – all <em>Spiroplasma</em> sequences that contained an <a href="https://pfam.xfam.org/family/OTU">OTU domain</a> as predicted by <a href="https://www.ebi.ac.uk/Tools/pfa/pfamscan/">PfamScan</a></li> <li>OTU_alignments.fasta – alignment of OTU domains performed using <a href="https://mafft.cbrc.jp/alignment/software/">Mafft</a></li> <li>RIP_sequences.fasta – all <em>Spiroplasma</em> sequences that contained an <a href="https://pfam.xfam.org/family/RIP">RIP domain</a> as predicted by <a href="https://www.ebi.ac.uk/Tools/pfa/pfamscan/">PfamScan</a></li> <li>RIP_alignments.fasta – alignment of RIP domains performed using the <a href="http://hmmer.org/">HMMER package</a></li> <li>Spiroplasma_supermatrix.fasta – Fasta alignment of concatenated single copy <em>Spiroplasma</em> loci conserved across the investigated strains. Loci that showed signs of recombination were not included</li> <li>Spiroplasma_partitions.txt – Lists the loci that make up the <em>Spiroplasma</em> supermatrix</li> <li>Spiroplasma_partitioning.scheme.txt – Partitioning scheme employed in our Maximum Likelihood analysis of the supermatrix. This was the best fitting partitioning scheme as determined with <a href="http://www.iqtree.org/">IQ-TREE</a></li> <li>Protocol_1.pdf – Chloroform–Ethanol protocol used for extracting <em>Spiroplasma</em> DNA for <em>s</em>Hy-Tx</li> </ul>
Phenotype data for Sussex LHM Drosophila melanogaster reproductive fitness GWAS
<p>Input data, code, logs, graphs and output data for the Sussex LHM Drosophila melanogaster hemiclones.</p> <p>Aim is to generate single, standardised values of female and male reproductive fitness for each hemiclone genome, for using in genome-wide association test using Plink software.</p> <p>Notes on how to run are provided in the code.</p>
Gene co-ordinates, expression levels; SNP identifiers and functions for Drosophila melanogaster (Sussex LHM population)
<p>Data for SNP context information to add to GWAS results. Specifically, SNP functions, sex-bias in gene expression, official SNP idenfiers from NCBI dbSNP, and gene positions and names (from UCSC Genome Browswer). Most of the input files are on-line and their URLs are stated in the code (make_dmel_accessory_data.sh). Also includes code, logs, and exploratory graphs.</p>
Bivariate GWAS for female and male fitness in Drosophila melanogaster (Sussex, LHm)
<p>Code, logs, results and graphs for genome-wide association study of reproductive fitness in D.melanogaster hemiclone lines, using the R package 'Mulitphen'.</p>
Highly parallel genomic selection response in replicated Drosophila melanogaster populations with reduced genetic variation
<p>Many adaptive traits are polygenic and frequently more loci contributing to the phenotype are segregating than needed to express the phenotypic optimum. Experimental evolution with replicated populations adapting to a new controlled environment provides a powerful approach to study polygenic adaptation. Since genetic redundancy often results in non-parallel selection responses among replicates, we propose a modified Evolve and Resequence (E&R) design that maximizes the similarity among replicates. Rather than starting from many founders, we only use two inbred <em>Drosophila melanogaster</em>strains and expose them to a very extreme, hot temperature environment (29°C). After 20 generations, we detect many genomic regions with a strong, highly parallel selection response in 10 evolved replicates. The X chromosome has a more pronounced selection response than the autosomes, which may be attributed to dominance effects. Furthermore, we find that the median selection coefficient for all chromosomes is higher in our two-genotype experiment than in classic E&R studies. Since two random genomes harbor sufficient variation for adaptive responses, we propose that this approach is particularly well-suited for the analysis of polygenic adaptation.</p> <p>See the README.txt file to get a description of the uploaded files. Scripts.zip contains annotated command lines and scripts for the project (see internal README.txt file).</p>
Factors determining distributions of rainforest Drosophila shift from interspecific competition to high temperature with decreasing elevation (original datasets)
<p>This repository provides the data for the manuscript "Factors determining distributions of rainforest Drosophila shift from interspecific competition to high temperature with decreasing elevation"</p> <p>We investigated thermal tolerances and interspecific competition as causes of species turnover in the nine most abundant species of <em>Drosophila</em> along elevational gradients in the Australian Wet Tropics. Specifically, we 1) analyzed the distribution patterns of the studies <em>Drosophila</em> species; 2) fitted thermal performance curves; 3) tested the correlation between multiple thermal traits and distribution patterns; 4) fitted the Beverton-Holt model to describe the single-generation intra- and inter-specific competition effect; 5) examined the long-term effect of competition and temperature on the population size of a pair of Drosophila species.</p> <p>More details are provided in the README file.</p>
Zellige example dataset: Drosophila pupal wing and abdomen
<p><strong>Drosophila pupa imaged at around 24h after puparium formation. </strong></p> <p>The z-stack image encompasses a distal portion of the wing and a portion of the abdomen. The four distinct surfaces are the abdomen cuticle, the abdomen epithelium, the wing cuticle and the wing epithelium. The z-stack was acquired with a spinning disk confocal microscope (Yokogawa W1) equipped with a Nikon Plan-Apochromat 60x lens (NA=1.4). Pixel size 0.183 µm, z step <1 µm. This dataset contains both the ground-truth height maps and the height maps generated with Zellige.The Zellige parameters used are:</p> <p><span class="math-tex">\(T_{A}=6, T_{otsu}=1, S_{min}=5, \sigma_{xy}=5, \sigma_{z}=1, T_{OSE1}=0.7, R_{1}=10, C_{1}=0.8, T_{OSE2}=0.1, R_{2}=5, C_{2}=0.9.\)</span></p> <p>Nota: to compare the ground truth height map with the Zellige height map, one first needs to substrat 1 to all values of the Zellige height map.</p> <p>See the accompanying paper: Extracting multiple surfaces from 3D microscopy images in complex biological tissues with the Zellige software tool. Trébeau <em>et al.</em> 2022: <a href="https://doi.org/10.1101/2022.04.05.485876">https://doi.org/10.1101/2022.04.05.485876</a></p> <p> </p>
Drosophila willistoni genome annotation
<p>Genome annotation of Drosophila willistoni de novo assembly using long reads. Protein coding genes were predicted with Funannotate. This software aligned proteins and transcripts from the Drosophila willistoni Flybase annotation against the assembly using minimap2, diamond and exonerate. It processed these hints to be included by augustus when predicting protein coding genes.</p> <p>LncRNAs were identified by FEELnc using stranded ribodepleted RNA-seq libraries from ovaries, testes, male accessory glands and whole body samples. Additional lncRNAs were identified by mapping lncRNAs sequences downloaded from RNA central identified for Drosophila willistoni.</p> <p>Ribosomal RNAs were predicted with RNAmmer; tRNAs, with tRNAscan2; and other miscellaneous ncRNA, with cmsearch and Rfam models.</p>
Infection increases activity via Toll dependent and independent mechanisms in Drosophila melanogaster - ethoscope dataset
<p>Ethoscope dataset for Vicent et al 2022, PLoS Pathogens</p> <p>Original preprint available at: https://www.biorxiv.org/content/10.1101/2021.08.24.457493v1</p> <p> </p>
Linkage-independent SNPs in the Drosophila melanogaster Sussex LHM sample
<p>Unix code for running Plink program for generating a list of SNPs (single-nucleotide polymorphisms) which are independent of linkage diseqiulibrium. Used for later statistical analyses incorporating the number of independent tests made across the genome.</p>
Separate-sex GWAS for reproductive fitness in Drosophila melanogaster (Sussex LHM sample)
<p>Code, data, logs, and graphs for GWAS on seperate-sex reproductive fitness in Drosophila melanogaster, Sussex LHM population sample.</p> <p>The shell script, code_drive_basic_gwas.sh, downloads input data files from the internet, drives Plink to select LD-independent SNPs, and then perform a genome-wide association test against female and male fitness, separately. Plink is also used to assign functions and gene names to SNPs. Bash/Unix code is used for formatting/compatibility adjustments, and also to add NCBI-dbSNP IDs to results. The shell script starts an R script that generates basic diagnostic graphs. This updated version differs from the first in that three large unconfirmed snRNA genes have been omitted to improve assignment of SNPs to genes.</p> <p>See https://f1000research.com/articles/5-2644/v3 and http://www.sussex.ac.uk/lifesci/morrowlab/</p>
False discovery rate calculations for genome-wide association study of reproductive fitness in Drosophila melanogaster (Sussex LHM sample)
<p>R code and results of applying false discovery (FDR) rate calculations to establish statistical signficance in a genome-wide association study of reproductive fitness in Drosophila melanogaster. Phenotype values were generated on hemiclone female and male lines from an outbred, laboratory adapted population. Thus, GWAS were previously performed seperately on the phenotype values for each sex, and also using a bivariate GWAS implemented in the R package multiPhen.</p> <p>FDR calculations were performed using the R package 'fdrtool' on all SNPs, and on LD-independent SNPs, the latter of which was used to determine p-value thresholds for genome-wide significance when all SNPs were considered.</p> <p>This version differs from the original in that: i) Some gene positions/names have been reassigned for accuaracy in the input data. ii) A file containing the p-value thresholds corresponding to an FDR of 0.1 has been added. The 95% credible intervals for each SNP association have been added to the results data files.</p>
Drosophila Larvae Tracking: movies of drosophila larvae communities
<h2>33 movies of drosophila larvae communities</h2> <p>The task associated to this dataset is tracking multiple drosophila larvae. Such a tracking is required in the quest to elucidate the genetic basis of Drosophila's behaviour. This dataset was used in the article "<a href="https://hci.iwr.uni-heidelberg.de/sites/default/files/publications/files/219478572/fiaschi_14_tracking.pdf" target="_blank" rel="noopener">Tracking indistinguishable translucent objects over time using weakly supervised structured learning</a>". We provide the raw data, an intermediate segmentation of the foreground and the gold standard used in the <a href="https://hci.iwr.uni-heidelberg.de/sites/default/files/publications/files/219478572/fiaschi_14_tracking.pdf">evaluation of that tracking algorithm</a>. </p>
Centripetal migration in Drosophila ovary I: wild type timelapse & milestones pt1
<p>Timelapse imaging data tracking inward migration of follicle cells during centripetal migration in Drosophila ovary. </p> <p>Part of data supporting Figs 2, S1 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”</p> <p>DOI: 10.1242/dev.200492</p> <p> •Timelapse imaging data of wild type samples</p> <p> •Quantitative analysis of specific milestone morphologies</p> <p> •Analysis of distances between leader FC tips from opposite sides of egg chamber prior to Milestone VII in relevant samples</p>
Centripetal migration in Drosophila ovary IX: E-cadherin null clones pt2 & E-Cadherin germ cell RNAi pt 2
<p>Part of data supporting Figs 6, 7, S3, S6, S16 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”<br> DOI: 10.1242/dev.200492</p> <p><strong>Data file descriptions:</strong></p> <ul> <li><strong>“FRT G13 mitotic clones” 14.6 GB</strong></li> </ul> <p> Fixed sample image data for clones of cells with E-Cadherin mutant or control mitotic clones</p> <ul> <li><strong>“GC RNAi flipout timelapse data pt2” 28.92GB</strong></li> </ul> <p> Timelapse image data for clones of germ cells with E-Cadherin knockdown</p> <ul> <li><strong> “Image analysis of ring canals-fixed G13 control” 6 KB</strong></li> </ul> <p> Evaluation of fixed samples for ring canal position just prior to stage 11, nurse cell dumping, using</p> <ul> <li><strong>“Immuno Shg LOF clonal analysis” 98 KB</strong></li> </ul> <p> Preliminary evaluation of sample image with clones of cells with E-Cadherin mutant or control mitotic clones</p> <ul> <li><strong>“Live GC RNAi clonal data Prelim Eval” 25.2 MB</strong></li> </ul> <p> Preliminary evaluation of germ cell E-Cadherin knockdown samples</p> <p> </p>
Centripetal migration in Drosophila ovary X: E-Cadherin germ cell RNAi pt 1
<p>Part of data supporting Fig S16 of “Two phases for centripetal migration of Drosophila melanogaster follicle cells: initial ingression followed by epithelial migration”</p> <p>DOI: 10.1242/dev.200492</p> <p>Data description:</p> <ul> <li><strong>“GC RNAi flipout timelapse data pt1” 38 GB</strong></li> </ul> <p> Timelapse image data for clones of germ cells with E-Cadherin knockdown</p> <ul> <li><strong>“Live GC RNAi clonal data Prelim Eval” 25.2 MB</strong></li> </ul> <p> Preliminary evaluation of all germ cell E-Cadherin knockdown samples</p>
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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.