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3,584 results for “genomic analysis”
Pergola: boosting visualization and analysis of longitudinal data by unlocking genomic analysis tools - Mouse feeding behavior dataset
<p>Dataset contains feeding and drinking behavioral recordings of C57BL6/J male mice. Mice were distributed into 2 groups (9 control mice and 8 high-fat diet mice) and tracked individually on Phecomp cages for 9 weeks. During the first experimental week all animals were given <em>ad libitum</em> access to a standard chow (habituation phase). After this first week, control mice continued with the same diet regime while high-fat mice were exclusively given <em>ad libitum</em> access to a high-fat chow. Data was used originally in this publication <a href="http://onlinelibrary.wiley.com/doi/10.1111/adb.12595/abstract">10.1111/adb.12595.</a></p> <p>The data set consist in:</p> <p>- a "mouse_recordings" folder containing a CSV file containing mouse recordings and the files.</p> <p>- a "mappings" folder containing all the mappings used by the pergola in the pipeline to convert data.</p> <p>- a "phases" folder containing a CSV file containing experimental phases.</p> <p>- a "chromHMM_files" folder containing a cellmarkfiletable table used by chromHMM to learn a HMM model</p>
Pergola: boosting visualization and analysis of longitudinal data by unlocking genomic analysis tools - D. melanogaster behavior dataset obtained with JAABA
<p>Dataset contains <em>Drosophila melanogaster </em>behavioral annotations of chasing. The dataset is formed by 20 GAL4 line flies group from a TrpA activation screen with increased propensity to chasing and by 19 pBDPGAL4U line (control) flies group. Ctrax motor trajectories derived from the original video-recordings (1000 seconds) were downloaded from this <a href="https://sourceforge.net/projects/jaaba/files/Sample%20Data/sampledata_v0.1.zip/download">link</a> and used to obtain the chasing behavioral annotations using <a href="http://jaaba.sourceforge.net/">JAABA</a> <a href="https://www.nature.com/articles/nmeth.2281">10.1038/nmeth.2281</a>: </p> <p>The data set consist in:</p> <p>- a "mappings" folder containing all the mappings used by the pergola in the pipeline to convert data.</p> <p>- a "perframe_TrpA" folder containing mat files with three Ctrax derived variables (dnose2ell, dtheta and velmag) from the motor trajectories of the GAL4 line.</p> <p>- a "perframe_pBDPGAL4" folder containing mat files with three Ctrax derived variables (dnose2ell, dtheta and velmag) from the motor trajectories of the control line.</p> <p>- a "scores" folder including the JAABA chasing annotations in two mat file one for each fly line.</p>
Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits
<p><strong>Introduction</strong></p> <p>These are the <em>Summary Level-data</em> as presented in:</p> <p>"Genome-wide association meta-analysis of 30,000 samples identifies seven novel loci for quantitative ECG traits". Eur J Hum Genet. 2019 Jan 24. doi: 10.1038/s41431-018-0295-z.<em> [Epub ahead of print]</em></p> <p>If you use these data please cite the corresponding manuscript, which can be downloaded here: <a href="http://em.rdcu.be/wf/click?upn=lMZy1lernSJ7apc5DgYM8eFz0euOx0-2B13Abimi4Sb0A-3D_2NNavOiAD9A7CPFnsa04dGla3sU002fLfkDtL-2FhGlad0GuoM-2B3OlDb0C5GiEhwIvtH7ba4KKF45ipTOFodx6CqvVvoP2GQ992sPGoV9ZPWIe04tUd8-2BGWey0In0TXPII5zK-2Bfp8Wk9TpEqEcSd-2BEmywqZc8o5TW4xGPXZqmchfUH8chy3P4SEtpzHXMG1LwsIYrKfwegqTXG85RAJPr-2B21Tk9SobtpvFs0frMkJ4ekKsl33ryoZfFPk1byjQunJYn4-2BB0iqMgGs6cXv0AOgAxg-3D-3D">https://rdcu.be/bh8mu</a>. When you have any questions or comments regarding this study or these files, please contact me via:</p> <p>Jessica van Setten, PhD | <em>Department of Cardiology, University Medical Center Utrecht, Utrecht University</em> | j.vansetten [at] umcutrecht [dot] nl</p> <p> </p> <p><strong>Files and description</strong></p> <p>There are four files available:</p> <ol> <li>RR_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for RR interval</li> <li>PR_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for PR interval</li> <li>QT_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for QT interval</li> <li>QRS_summary_Sept2018.txt.gz - gzipped file containing all the (unfiltered) meta-analysis results for QRS duration</li> </ol> <p>All these files have the same lay-out and are gzipped. The reference used for meta-analysis of GWAS was Genome of the Netherlands v4. </p> <ul> <li><em>SNP</em> - variantID (rsID), please note that few hundred variants do not have an rsID, but are NA instead. These can still be identified by chromosome and position.</li> <li><em>CHR</em> - chromosome numbers [1-22 and X].</li> <li><em>POS</em> - base pair position, hg19 / build37.</li> <li><em>CODED_ALLELE</em> - coded allele, <em>i.e.</em> the effect allele, as represented (and harmonized) across cohorts. Note that this is not necessarily the minor allele.</li> <li><em>NON_CODED_ALLELE</em> - the other allele, <em>i.e.</em> the non-effect allele.</li> <li><em>CODED_ALLELE_FREQ</em> - coded allele frequency, <em>i.e.</em> the effect allele frequency. Note that this is not necessarily the minor allele frequency.</li> <li><em>BETA</em> - beta from the fixed-effects model.</li> <li><em>SE </em>- standard error from the fixed-effects model.</li> <li><em>P </em>- P-value from the fixed-effects model.</li> <li><em>NEAREST_GENE</em> - the gene closest to the respective variant.</li> </ul> <p> </p>
REPIN population analysis in 4 Dokdonia genomes
<p>This dataset is the output of RAREFAN (http://rarefan.evolbio.mpg.de/) a webserver to identify REPIN populations across an entire bacterial species. The data was created using the following command "java -jar -Xmx10g rarefan.jar dokdonia/in/ dokdonia/out/ 4h-3-7-5.fas 55 21 in/yafM_Ecoli.faa dokdonia.nwk 1e-10 true 1"</p> <p>All input files are located in the folder dokdonia/in/, all output data is located in dokdonia/out/.</p> <p>The input files include the 4 fasta formatted <em>Dokdonia</em> genome files (*.fas) and a RAYT protein sequence called yafM_Ecoli.faa.</p> <p>The output files include the following:</p> <p>A phylogenetic tree "dokdonia.nwk" of all genomes generated with andi (<a href="http://github.com/evolbioinf/andi/">http://github.com/evolbioinf/andi/</a>) and clustDist (http://guanine.evolbio.mpg.de/problemsBook/node1.html).</p> <p>A file containing the frequencies of all 21bp long sequences found in the 4h-3-7-5 genome: 4h-3-7-5.wfr</p> <p>A file containing all 21bp long sequences that occur more frequently than 55 times in the 4h-3-7-5 genome: 4h-3-7-5.overrep</p> <p>A file containing information on the RAYTs and their cooccurrence with different REPIN populations: prox.stats</p> <p>A file containing the nucleotide sequences of all yafM_Ecoli.faa relatives identified with BLAST+ in the <em>Dokdonia </em>species: yafM_relatives.fna</p> <p>maxREPIN_0.txt Contains the most frequent REPIN identified for each sequence type in each <em>Dokdonia</em> strain.</p> <p> presAbs_0.txt Contains for each strain information on the number of RAYTs, the number of REPINs, the master sequence, the number of master sequences, the entire REP/REPIN population size, the number of REPIN clusters that contain more than 10 sequences, all REPINs in the population as well as all REPINs that differ to the master sequences in at most three nucleotides.</p> <p>rayt_[strain name].tab contains location information for each identified RAYT relative for each strain. The files can be viewed with artemis.</p> <p>results.txt contains for each strain the frequency of the six identified 21bp long seeds.</p> <p>There is one folder called groupSeedSequences, which includes the data for identifying the most common 21 bp long sequences in <em>D. </em>sp. 4h-3-7-5. All 21bp long sequences in the genome that occur more frequently than 55 times are sorted into 6 sequence groups. These sequence groups are stored in the files Group_4h-3-7-5_*.out and .out.fas. There is also a 4h-3-7-5_words.tab file, which contains the locations of all overrepresented 21bp long sequences in the 4h-3-7-5 genome. This file can be viewed in artemis (https://www.sanger.ac.uk/tool/artemis/) together with the 4h-3-7-5 genome file. The most common sequence in each group is used as a seed sequence to determine REPIN populations across all 4 genomes.</p> <p> </p> <p>For each genome there is one output folder (ending in _0), for each sequence group one.</p> <p>Each folder contains the following files:</p> <p>*.dd: Degree distribution of the REPIN network, where each REPIN is a node. A REPIN is connected to another REPIN if they differ in exactly one position. The degree distribution is a histogram of the number of connections of all the nodes. </p> <p>*.hist For the largest sequence cluster determined by mcl that consists of REPINs (two REPs in inverted orientation) this file contains the number of REPINs in each sequence class. Sequence class 0 is the master sequence. By definition the most common REPIN in the sequence population. Sequence class 1 contains all REPINs differing in exactly one position to the master sequence. Sequence class 2 contains REPINs differing in 2 positions etc.</p> <p>*.mcl Contains the clustering output by mcl. Each line contains the member of a cluster. Lines are sorted by cluster size.</p> <p>*.mw Contains the most common 21bp long sequence and its frequency in the genome, which is the basis for identifying first all related REP sequences and from those the REPINs formed by these REP sequences.</p> <p>*.nodes The identity and frequency of all REPINs and REP sequences for either all sequences or only for the largest sequence cluster.</p> <p>*.ss Contains REPINs and REP sequences as well as their positions in fasta format. Position information starts with the location in genome fasta file (first sequence is 0...) followed by the start and end position of the entire REPIN/REP sequence. </p> <p>*.ss.REP REP sequence information in fasta format.</p> <p>*.tab Location in tab format. Can be used to display locations of REPs and REPINs in the genome via artemis.</p> <p>*_[0-9].ss Contains REPIN/REP sequence information for each subcluster separately.</p> <p>*_[0-9].tab Contains the location of REP/REPINs for each subcluster separately for viewing in artemis.</p> <p>*allSeed.nw Contains network connections between nodes of all sequences. Can be used to view network in for example R or cytoscape together with the nodes file.</p> <p>*largestCluster.nodes Information on nodes only from the largest REPIN cluster.</p> <p>*largestCluster.ss *.ss file for the largest REPIN cluster.</p> <p>*largestCluster.tab *.tab file for the largest REPIN cluster.</p> <p>*_rayt_repin_prox.txt shows which REPIN/REP cluster is in proximity to any of the RAYT genes identified in the genome (within 200bp).</p> <p>And a subfolder that contains the complete sequences (including the variable region) for all identified REPs and REPINs.</p> <p><strong>The dataset was generated using the following external tools:</strong></p> <p>andi for tree building:</p> <p>B Haubold, F Klötzl, and P Pfaffelhuber. <strong>andi: fast and accurate estimation of evolutionary distances between closely related genomes.</strong> Bioinformatics, 2015 vol. 31 (8) pp. 1169-1175.</p> <p>MCL for REPIN population clustering:</p> <p>A J Enright, S Van Dongen, and C A Ouzounis. <strong>An efficient algorithm for large-scale detection of protein families.</strong> Nucleic Acids Research, 2002 vol. 30 (7) pp. 1575-1584.</p> <p>BLAST+ for identifying RAYT relatives in the different genomes:</p> <p>C Camacho, G Coulouris, V Avagyan, N Ma, J Papadopoulos, K Bealer, and T L Madden. <strong>BLAST+: architecture and applications.</strong> BMC Bioinformatics, 2009 vol. 10 (1) pp. 421-9.</p>
Genome and transcriptome analysis of the beet armyworm Spodoptera exigua reveals targets for pest control
<p>The genus <i>Spodoptera</i> (Lepidoptera: Noctuidae) includes some of the most infamous insect pests of cultivated plants including <i>Spodoptera frugiperda</i>, <i>Spodoptera litura</i> and <i>Spodoptera exigua</i>. To effectively develop targeted pest control strategies for diverse <i>Spodoptera</i> species, genomic resources are highly desired. To this aim, we provide the genome assembly and developmental transcriptome comprising all major life stages of <i>S. exigua</i>, the beet armyworm. <i>Spodoptera exigua</i> is a polyphagous herbivore that can feed from > 130 host plants including several economically important crops.</p> <p>The 419 Mb beet armyworm genome was sequenced from a female <i>S. exigua</i> pupa. Using a hybrid genome sequencing approach (Nanopore long read data and Illumina short read), a high-quality genome assembly was achieved (N50=1.1 Mb). An official gene set (OGS, 18,477 transcripts) was generated by automatic annotation and by using transcriptomic RNA-seq data sets of 18 <i>S. exigua</i> samples as supporting evidence. In-depth analyses of developmental stage-specific expression in combination with gene tree analyses of identified homologous genes across Lepidoptera genomes revealed four potential genes of interest (three of them <i>Spodoptera</i>-specific) upregulated during 1<sup>st</sup> and 3<sup>rd</sup> instar larval stages for targeted pest-outbreak management.</p> <p>The beet armyworm genome sequence and developmental transcriptome covering all major developmental stages provides critical insights into the biology of this devastating polyphagous insect pest species with a worldwide distribution. In addition, comparative genomic analyses across Lepidoptera significantly advance our knowledge to further control other invasive <i>Spodoptera</i> species and reveals potential lineage-specific target genes for pest control strategies.</p>
Figure 3 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea
Figure 3. Putative secondary cloverleaf structures of the tRNA genes in the Lemyra melli mitogenome with mismatched bases. The blue dots, and red dots indicate Watson- Crick base pairing A-U and G-C, respectively, and the blanks indicate mismatched bases. Seven mismatches (five U-U, one A-A and one U-G) lie in five tRNA genes (three in the amino acid acceptor stems, three in the anticodon stems and one in pseudouridine (TΨC)).
Figure 1 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea
Figure 1. Map of the mitogenome of Lemyra melli. Genes lying outside and inside of the outer circle are transcribed in the counterclockwise and clockwise directions, respectively. The transfer RNA genes trnL1, trnL2, trnS1 and trnS2 are denoted trnL(UUR), trnL(CUN), trnS(AGN) and trnS(UCN), respectively. Area dashed darker gray in the inner circle denotes the GC content while the lighter gray denotes the AT content of the genome.
Figure 4 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea
Figure 4. The structure in the A+T-rich region of the Leymra melli mitogenome. The ATAGA + polyT, the duplicated 14-bp repeat element, the ATTTA + (AT)10 element, and the polyA structure are shown in the sequence.
Figure 1 in The complete mitochondrial genome of Parnassius actius (Lepidoptera: Papilionidae: Parnassinae) with the related phylogenetic analysis
Figure 1. Circular map of the mitochondrial genome of P. actius. The abbreviations for the genes are as follows: COI, COII and COIII refer to the cytochrome oxidase subunits; Cytb refers to cytochrome B; ATP6 and ATP8 refer to subunits 6 and 8 of ATPase; ND1–6 grefers to components of NADH dehydrogenase. The tRNAs are indicated by the IUPAC-IUB single letter amion acid codes, while L1, L2, S1, S2 denote tRNALeu(CUN), tRNALeu(UUR), tRNASer(AGN) and tRNASer(UCN), respectively. Gene names that are not underlined indicate the direction of transcription from left to right, and with underline indicates right to left. The P. actius mitogenome was sequenced by using 7 short fragments (SF1–SF7) and 7 long fragments (LF1–LF7) as templates, shown as single lines within a circle.
Figure 2 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea
Figure 2. Relative Synonyous Codon Usage (RSCU) in L. melli, H. cunea, and A. formosae mitogenomes. Codons are provided on the x-axis.
Figure 6 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea
Figure 6. Phylogenetic analysis inferred from the concatenated nucleotide sequences of 13 PCGs in the mitogenome. D. melanogaster and E. regina were used as outgroups. The numbers above the branches specify bootstrap percentages (1 000 replicates) from software RAXMAL and the ML method. A, B, C, D, and E indicated the superfamily of Noctuoidea, Bombycoidea, Geometroidea, Pyraloidea and Tortricidea, respectively.
Figure 7 in The complete mitochondrial genome of Parnassius actius (Lepidoptera: Papilionidae: Parnassinae) with the related phylogenetic analysis
Figure 7. Bayesian Inference and maximum likelihood phylograms of the 45 Parnassius species in this study (Numbers on each node correspond to the posterior probability values of the BI analysis (left) and the ML bootstrap percentage values for 1000 replicates (right), posterior probability values below 0.5 or bootstrap percentage values below 50% was not shown on the diagram).
Datasets of "Lipoxygenase (LOX) genes in angiosperms: a comparative genome-wide analysis"
<p>This dataset contain protein subcellular localization results and FASTA files containing coding sequences (CDS) and protein sequences used for all phylogenetic analyses of the study " Lipoxygenase (LOX) genes in angiosperms: a comparative genome-wide analysis" (submitted).</p>
Data and materials for "The Consequences of Data Dispersion in Genomics: A Comparative Analysis of Data Sources for Precision Medicine" manuscript"
<p>Data and sripts for the "The Consequences of Data Dispersion in Genomics: A Comparative Analysis of Data Sources for Precision Medicine" manuscript" manuscript, sent to BMC Bioinformatics</p>
Additional annotation, alignment, and results from Ka/Ks analysis for Chromosomal-level reference genome assembly of the African Spiny Mouse (Acomys cahirinus)
<p><strong>Annotation files, alignments, and results summaries from Chromosomal-level reference genome assembly of the African Spiny Mouse (Acomys cahirinus).</strong></p> <p>Pairwise genome alignments contain the .maf suffix</p> <p>FASTA alignments from stitched gene blocks contain the .fasta suffix</p> <p>CSV file containing the Ka/Ks results</p> <p>RepeatMasker .out file</p>
metaGOflow: a workflow for the analysis of marine Genomic Observatories shotgun metagenomics data - use case
<p>Data products returned by <a href="https://github.com/emo-bon/MetaGOflow">metaGOflow</a> (<a href="https://github.com/emo-bon/MetaGOflow/releases/tag/v1.0.0">v1.0.0</a>) and packed as a Research Object (RO) Crate, when performed with:</p> <ul> <li>a <strong>seawater metagenomic sample </strong>(TARA OCEAN, <a href="https://www.ebi.ac.uk/ena/browser/view/ERR599171">ERR599171</a>)</li> <li>a <strong>fish gut </strong>sample (<a href="https://www.ebi.ac.uk/ena/browser/view/ERR4765907">ERR4765907</a>)</li> <li>a<strong> human gut </strong>sample (<a href="https://www.ebi.ac.uk/ena/browser/view/SRR9654976">SRR9654976</a>)</li> </ul> <p>This Zenodo repo accompanies the metaGOflow paper and more about the analysis of this sample can be found there.</p> <p>You can also have a look at some visual components of the workflow at this <a href="https://data.emobon.embrc.eu/MetaGOflow/">GitHub page</a>. </p> <p>The source code of metaGOflow is available through <a href="http://github.com/emo-bon/MetaGOflow">GitHub</a>.</p>
Genome sequencing of three Orestias species and the analysis of their phylogenetic relationships within the Cyprinodontiformes order
<p>Relevant files and datasets for the paper: <em>"Genomes of the Orestias pupfish from the Andean Altiplano shed light on their evolutionary history and phylogenetic relationships within Cyprinodontiformes." </em>by Morales <em>et al</em>.</p>
Genome-wide analysis resolves the radiation of New Zealand’s freshwater Galaxias vulgaris complex and reveals a candidate species obscured by mitochondrial capture
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Reproducible data, example subsets, and analysis pipeline for the extended TAaCGH study of breast cancer genomic and transcriptomic profiles
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Genome and transcriptome analysis of the beet armyworm Spodoptera exigua reveals targets for pest control
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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
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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.