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3,584 results for “genomic analysis”
EGP Mitochondrial Genome Analysis on Human Genome Diversity Project Whole-Genome Sequencing Data
<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the HGDP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Simons Genome Diversity Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>2b388c1fa446ecec70e33ea0471e06f8</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>50b80ed32b1ae542c8967cc31986dd19</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>995f30b74c4bb094a674b1a994853246</td> </tr> <tr> <td>Human Genome Diversity Project</td> <td>Mitochondrial Genome Copy Number</td> <td>e79e61efab4c491fa2825b7d1853df58</td> </tr> </tbody> </table> </div> <div>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</div>
EGP Mitochondrial Genome Analysis on Simons Genome Diversity Project Whole-Genome Sequencing Data
<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the SGDP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Simons Genome Diversity Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <table> <tbody> <tr> <th>Public Dataset</th> <th>EGP Result File Type</th> <th>MD5</th> </tr> </tbody> <tbody> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>86b09553f80926c1c29c57000ec1a88f</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>010026d77bee81e7b8daf5836bd12da3</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>f1ea3edf4a82b42f2028467fb3544dc4</td> </tr> <tr> <td>Simons Genome Diversity Project</td> <td>Mitochondrial Genome Copy Number</td> <td>4872eeb792c214ad49662e98e4b14620</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p>
EGP Mitochondrial Genome Analysis on 1000 Genomes Project 2504 Whole-Genome Sequencing Data
<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the 1000 Genomes Project 2504 Dataset. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on 1000 Genomes Project 2504 Dataset</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://ftp.1000genomes.ebi.ac.uk/vol1/ftp/data_collections/1000G_2504_high_coverage/1000G_2504_high_coverage.sequence.index</code>. Please note that the index files are there as well. You just have to append a <code>.crai</code>. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>dbf39d6ff0e4389b900f9d985f2e6c64</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>4d53ef60ec16f3e4b566c45fdf0fb977</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Variant Tables</td> <td>16925b546051d37cce27df8ec57ccc5e</td> </tr> <tr> <td>1000 Genomes Project 2504</td> <td>Mitochondrial Genome Copy Number</td> <td>365c1b360ea327795d981356064658a6</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div>
EGP Mitochondrial Genome Analysis on 1000 Genomes Project 698 Related Whole-Genome Sequencing Data
<div> <p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the 1000 Genomes Project 698 Related Dataset. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on 1000 Genomes Project 698 Related Dataset</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://ftp-trace.ncbi.nlm.nih.gov/1000genomes/ftp/1000G_2504_high_coverage/additional_698_related/1000G_698_related_high_coverage.sequence.index</code>. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>322038d61b4da2e937b32410613c3532</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>36c782c12245100478903f7fa191a402</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Variant Tables</td> <td>68b2a51361ffae4e7ad9d420b8becd38</td> </tr> <tr> <td>1000 Genomes Project 698 Related</td> <td>Mitochondrial Genome Copy Number</td> <td>1e83c8ae132b0a7ef33b090757b29063</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div> <p> </p> </div> <h2> </h2>
EGP Mitochondrial Genome Analysis on Gambian Genome Variation Project Whole-Genome Sequencing Data
<p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the GGVP. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on Gambian Genome Variation Project</strong>: Short-read WGS CRAM files were downloaded from the EMBL-EBI Public Data Globus Endpoint from the <code>/1000g/ftp/data_collections</code> directory. Post-download, the data was run through EGP version 1.3. The results are shown below:</p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>d21e1e91e8b4c00627171fae79a1f54d</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>b359d1068d4f84f7746d1ebde82df29a</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Variant Tables</td> <td>ee2b93aa93d2177d92ec0f8f308b43ed</td> </tr> <tr> <td>Gambian Genome Variation Project</td> <td>Mitochondrial Genome Copy Number</td> <td>fda509ba1d2bf33fd2d6b77b92e76c03</td> </tr> </tbody> </table> <p>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</p> </div>
EGP Mitochondrial Genome Analysis on GIAB Whole-Genome Sequencing Data
<div> <p><strong>Summary: </strong>This dataset consists of running EGP version 1.3 on whole-genome sequencing data from the GIAB. The link to EGP is here https://github.com/tycheleturner/ElGenomaPequeno.</p> <p><strong>Author: </strong>Tychele N. Turner, Ph.D.</p> <p><strong>Short Writeup: EGP version 1.3 on GIAB</strong>: Short-read WGS CRAM files were downloaded through the paths present in this file <code>https://raw.githubusercontent.com/genome-in-a-bottle/giab_data_indexes/refs/heads/master/AshkenazimTrio/alignment.index.AJtrio_Illumina300X_wgs_novoalign_GRCh37_GRCh38_NHGRI_07282015</code></p> <div> <table> <tbody> <tr> <td>Public Dataset</td> <td>EGP Result File Type</td> <td>MD5</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome Fasta Files for MEGA</td> <td>5eac6ec7d36307aa401fd5441b38a506</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome MitoMaster Result File</td> <td>1151ae74c8e515f4f39bef816bb55d6a</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome Variant Tables</td> <td>b3e342fe9827df2e399f5685f84cd4dc</td> </tr> <tr> <td>GIAB</td> <td>Mitochondrial Genome Copy Number</td> <td>3c45c19f76f71b3ccaad155565ead5e4</td> </tr> </tbody> </table> </div> <div>Please note: I have found that with Zenodo you must use "Download All" for the copy number table to properly open.</div> <p> </p> <p> </p> </div> <h2> </h2>
Supplementary data for analysis of TEs in Atlantic salmon genome
<p>This dataset contains the data used to generate the figures in the manuscript "The role of transposon activity in shaping cis-regulatory element evolution after whole genome duplication".</p> <p>The scripts for the figures can be found at https://gitlab.com/sandve-lab/TE-CRE</p>
Genome-wide association analysis identifies naturally segregating genetic variation associated with the rapid evolution of diapause in Aedes albopictus, an invasive vector mosquito.
<p>The raw data for genotype calls, the output files from the genotype calls, the code to replicate the analysis, and the output of the analysis.</p>
Comparative genomics of Helotiales (Leotiomycetes) and in silico analysis of temperature adaptations of plant-associated genes
<p><span>Table S1: Genome assembly size and quality for every species in this study; </span></p> <p><span>Table S2: Genome annotation counts for P450, virulence factors, effectors, and CAZy genes and their temperature adaptation.</span></p>
Data from: Whole-genome analysis of Mustela erminea finds that pulsed hybridization impacts evolution at high-latitudes
At high-latitude, climatic shifts hypothetically drove episodes of divergence during isolation in glacial refugia, or ice-free pockets of land that enabled terrestrial species persistence. Upon glacial recession, populations can expand and often come into contact, resulting in admixture between previously isolated groups. To understand how recurrent periods of isolation and contact have impacted evolution at high latitudes, we investigated introgression in the stoat (Mustela erminea), a Holarctic mammalian carnivore, using whole-genome sequences. We identify two temporally isolated introgression events coincident with large-scale climatic shifts: contemporary introgression in a mainland contact zone and ancient contact ~ 200 km south along North America's North Pacific Coast. Repeated episodes of gene flow highlight the central role of cyclic climates in structuring high-latitude diversity, through refugial divergence and subsequent introgressive hybridization. Introgression followed by allopatry (e.g., insularization) may contribute to expedited divergence of island taxa experiencing substantial glacial flux.
Data from: Comparative genomic analysis of the pheromone receptor Class 1 family (V1R) reveals extreme complexity in mouse lemurs (genus, Microcebus) and a chromosomal hotspot across mammals
<p><span>Sensory gene families are of special interest, both for what they can tell us about molecular evolution, and for what they imply as mediators of social communication. The vomeronasal type-1 receptors (V1Rs) have often been hypothesized as playing a fundamental role in driving or maintaining species boundaries given their likely function as mediators of intraspecific mate choice, particularly in nocturnal mammals. Here, we employ a comparative genomic approach for revealing patterns of V1R evolution within primates, with a special focus on the small-bodied nocturnal mouse and dwarf lemurs of Madagascar (genera <i>Microcebus</i> and <i>Cheirogaleus</i>, respectively). By doubling the existing genomic resources for strepsirrhine primates (i.e., the lemurs and lorises), we find that the highly speciose and morphologically cryptic mouse lemurs have experienced an elaborate proliferation of V1Rs that we argue is functionally related to their capacity for rapid lineage diversification. Contrary to a previous study that found equivalent degrees of V1R diversity in diurnal and nocturnal lemurs, our study finds a strong correlation between nocturnality and V1R elaboration, with nocturnal lemurs showing elaborate V1R repertoires and diurnal lemurs showing less diverse repertoires. Recognized subfamilies among V1Rs show unique signatures of diversifying positive selection, </span>as might be expected if they have each evolved to respond to specific stimuli<span>. Further, a detailed syntenic comparison of mouse lemurs with mouse (genus <i>Mus</i>) and other mammalian outgroups shows that orthologous mammalian subfamilies, predicted to be of ancient origin, tend to cluster in a densely populated region across syntenic chromosomes that we refer to as a V1R "hotspot."</span></p>
Full-likelihood genomic analysis clarifies a complex history of species divergence and introgression: the example of the erato-sara group of Heliconius butterflies
<p>Introgressive hybridization plays a key role in adaptive evolution and species diversification in many groups of species. However, frequent hybridization and gene flow between species make estimation of the species phylogeny and key population parameters challenging. Here, we show that by accounting for phasing and using full-likelihood methods, introgression histories and population parameters can be estimated reliably from whole-genome sequence data. We employ the multispecies coalescent (MSC) model with and without gene flow to infer the species phylogeny and cross-species introgression events using genomic data from six members of the <i>erato</i>-<i>sara</i> clade of <i>Heliconius</i> butterflies. The methods naturally accommodate random fluctuations in genealogical history across the genome due to deep coalescence. To avoid heterozygote phasing errors in haploid sequences commonly produced by genome assembly methods, we process and compile unphased diploid sequence alignments and use analytical methods to average over uncertainties in heterozygote phase resolution. There is robust evidence for introgression across the genome, both among distantly related species deep in the phylogeny and between sister species in shallow parts of the tree. We obtain chromosome-specific estimates of key population parameters such as introgression directions, times and probabilities, as well as species divergence times and population sizes for modern and ancestral species. We confirm ancestral gene flow between the <i>sara</i> clade and an ancestral population of <i><span>H. telesiphe</span></i>, a likely hybrid speciation origin for <i>H. hecalesia</i>, and gene flow between the sister species <i><span>H. erato</span></i><span> and <i>H. himera</i></span>. Inferred introgression among ancestral species also explains the history of two chromosomal inversions deep in the phylogeny of the group. This study illustrates how a full-likelihood approach based on the multispecies coalescent makes it possible to extract rich historical information of species divergence and gene flow from genomic data.</p>
Gramtools enables multiscale variation analysis with genome graphs
<p>Singularity container and data files supporting the article.</p> <p>Instructions to use these data are at: https://github.com/iqbal-lab-org/paper_gramtools_nesting </p>
Genome-wide SNP analysis elucidates the evolution of Prunus takesimensis in Ulleung Island: Genetic consequences of anagenetic speciation
<p>Of two major speciation modes of endemic plants on oceanic islands, cladogenesis and anagenesis, the latter has been recently emphasized as an effective mechanism for increasing plant diversity in isolated, ecologically homogeneous insular setting. As a single flowering cherry occurring on Ulleung Island in East Sea, <i>Prunus takesimensis</i> Nakai has been presumed as derived through anagenetic speciation on the Island. Based on morphological similarities, <i>P. sargentii </i>distributed in adjacent continental areas and islands has been suggested as its purported continental progenitor.<i> </i>However, the overall genetic complexity and resultant non-monophylies of closely related flowering cherries have hindered determining their phylogenetic relationships as well as establishing concrete continental progenitor and insular derivative relationship. Based on extensive sampling of wild flowering cherries including <i>P. takesimensis</i> and<i> P. sargentii</i> from Ulleung Island and its adjacent areas, this study inferred the origin and evolution of <i>P. takesimensis</i> using multiple different molecular markers. As the result of phylogeny and population genetic structure analyses based on SNPs detected by MIG-Seq and complementary cpDNA haplotypes, we could provide the extensive and convincing evidence for (1) the monophyly of<i> P. takesimensis</i>,<i> </i>(2) clear genetic differentiation between <i>P. takesimensis</i> (insular derivative) and <i>P. sargentii</i> (continental progenitor), (3) the geographic origin of <i>P. takesimensis</i> via single introduction from source population of <i>P. sargentii</i> in Korean Peninsula, (4) no significant genetic reduction in anagenetically derived insular species <i>P. takesimsnsis</i> compared to continental progenitor <i>P. sargentii</i>, (5) no strong population genetic structuring or geographical patters in the insular derived species, and (6) Mig-seq method as an effective tool to unravel complex evolutionary history of plant groups.</p>
Figure 5 in The complete mitochondrial genome of Lemyra melli (Daniel) (Lepidoptera: Erebidae) and a comparative analysis within the Noctuoidea
Figure 5. The potential stem-loop structure with "GAAT" and "TATA" in the flanking region.
Data from: Genome-wide analysis reveals associations between climate and regional patterns of adaptive divergence and dispersal in American pikas
<p>Understanding the role of adaptation in species responses to climate change is important for evaluating the evolutionary potential of populations and informing conservation efforts. Population genomics provides a useful approach for identifying putative signatures of selection and the underlying environmental factors or biological processes that may be involved. Here, we employed a population genomic approach within a space-for-time study design to investigate the genetic basis of local adaptation and reconstruct patterns of movement across rapidly changing environments in a thermally-sensitive mammal, the American pika (<i>Ochotona princeps</i>). Using genotypic data at 49,074 single nucleotide polymorphisms (SNPs), we analyzed patterns of genome-wide diversity, structure, and migration along three independent elevational transects located at the northern extent (Tweedsmuir South Provincial Park, British Columbia, Canada) and core (North Cascades National Park, Washington, USA) of the Cascades lineage. We identified 899 robust outlier SNPs within- and among-transects. Of those annotated to genes with known function, many were linked with cellular processes related to climate stress including ATP-binding, ATP citrate synthase activity, ATPase activity, hormone activity, metal ion-binding, and protein-binding. Moreover, we detected evidence for contrasting patterns of directional migration along transects across geographic regions that suggest an increased propensity for American pikas to disperse among lower elevation populations at higher latitudes where environments are generally cooler. Ultimately, our data indicate that fine-scale demographic patterns and adaptive processes may vary among populations of American pikas, providing an important context for evaluating biotic responses to climate change in this species and other alpine-adapted mammals.</p>
Compare Analysis with a High-quality Genome of Weedy Rice Reveals the Evolutionary Game of De-domestication
<p>A02.SV.vcf is the SV information between the A02 genome and Nipponbare genome.</p> <p>All.population.SV.vcf is the data of the SV genotyping information based on the super pan-genome.</p>
Methodological challenges in the genomic analysis of an endangered mammal population with low genetic diversity
<p><span>Recently, populations of various species with very low genetic diversity have been discovered. Some of these persist in the long term, but others could face extinction due to accelerated loss of fitness. In this work, we characterize 45 individuals of one of these populations, belonging to the Iberian desman (<em>Galemys</em> <em>pyrenaicus</em>). For this, we used the ddRADseq technique, which generated 1,421 SNPs. The heterozygosity values of the analyzed individuals were among the lowest recorded for mammals, ranging from 26 to 91 SNPs/Mb. Furthermore, the individuals from one of the localities, highly isolated due to strong barriers, presented extremely high inbreeding coefficients, with values above 0.7. Under this scenario of low genetic diversity and elevated inbreeding levels, some individuals appeared to be almost genetically identical. We used different methods and simulations to determine if genetic identification and parentage analysis were possible in this population. Only one of the methods, which does not assume population homogeneity, was able to identify all individuals correctly. Therefore, genetically impoverished populations pose a great methodological challenge for their genetic study. However, these populations are of primary scientific and conservation interest, so it is essential to characterize them genetically and improve genomic methodologies for their research.</span></p>
Detection of SARS-CoV-2 variants by genomic analysis of wastewater ampliconic samples (Galaxy Training Material)
<p>The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater ampliconic samples. (https://training.galaxyproject.org/training-material/)</p>
Detection of SARS-CoV-2 variants by genomic analysis of wastewater metatranscriptomic samples (Galaxy Training Material)
<p>The tutorial aims to train how to run workflows to analyze lineages abundances in SAR-CoV-2 wastewater metatranscriptomic samples. (https://training.galaxyproject.org/training-material/)</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.