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472 results for “Whole genome sequence”
Amino acid sequences of the proteins predicted from the whole genome of hilsa shad (Tenualosa ilisha) of the Bay of Bengal
<p>Gene prediction was performed by AUGUSTUS (Stanke et al., 2006) from the whole genome sequence of <em>T. ilisha</em> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/400122">PRJNA400122</a>). The data contain amino acid sequences of 37,450 predicted protein coding genes.</p>
MAPNET Population Genomics Workshop Content: Whole genome sequencing of Bactericera cockerelli
<p>Materials for the Workshop "Getting Started with Low Coverage Population Genomics" , Otago University, 22 March 2019. Alignment files for whole-genome sequence of N=143 Tomato and Potato Psyllids (<em>Bactericera cockerelli)</em> from 4 New Zealand , 1 Californian and 1 Honduran populations. Data files represent 250 kbp of one scaffold of a draft assembly.</p> <p>This data was generated by the Plant and Food Research in research programme funded by the Ministry of Business, Innovation and Employment (MBIE) . </p> <p> </p> <p><a href="https://github.com/MapNetNZ/Pop-Genomics-Workshop2019">Wokshop GitHub Repo</a></p> <p> </p> <p> </p>
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>
Whole-genome sequencing reveals contribution of rare and common variation to structural kidney and urinary tract malformations
<p>Supplementary tables detailing analysis of whole-genome sequencing data from 992 patients with congenital anomalies of the kidneys and urinary tract (CAKUT). </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>
Raw data for whole plasmid and whole genome sequencing
<p>Original data for plasmid and genomic DNA sequencing in the paper: Tailoring Microbial Fitness Through Computational Steering and CRISPRi-Driven Robustness Regulation</p>
Supplementary dataset to publication: Whole-genome sequencing of Streptococcus uberis isolated from cows with mastitis in Thuringia
<p><span><strong>Introduction</strong>.</span> <em><span>Streptococcus uberis</span></em> is a common cause of mastitis in cattle, leading to significant economic losses. The widespread use of antimicrobials has contributed to the emergence of resistance, which poses a severe challenge in controlling <em><span>S. uberis</span></em> infection.</p> <p><span><strong>Aim</strong>.</span> The objective of this study was to gain insights into the antimicrobial resistance (AMR) and epidemiological typing of <em><span>S. uberis</span></em> isolated from milk collected from bovine mastitis on dairy farms in Thuringia.</p> <p><span><strong>Methodology</strong>.</span> In this study, 84 <em><span>S. uberis</span></em> isolates were obtained from cattle with clinical mastitis in Thuringia, their phenotypic and genotypic AMR were analyzed and their phylogenetic relationship was explored using whole-genome sequencing.</p> <p><span><strong>Results</strong>.</span> Genetically heterogeneous strains were found on the farms, but clusters of highly similar strains also circulated within the same farms. All isolates were sensitive to ampicillin, penicillin, ceftiofur, and vancomycin. However, 42.9%, 42.9%, 22.6%, 19.0%, and 13.0% were resistant to tetracycline, doxycycline, clindamycin, pirlimycin, and erythromycin, respectively. Thirty-nine strains were phenotypically resistant to two or more tested antibiotics. We identified a plasmid associated with macrolide and lincosamide resistance in 12% of the strains.</p> <p><span><strong>Conclusion</strong>.</span> The emergence of <em><span>S. uberis</span></em> strains resistant to multiple antibiotics highlights the importance of <em><span>S. uberis</span></em> surveillance and the prudent use of antimicrobials.</p>
Supplementary Data for: Whole genome sequencing elucidates the species-wide diversity and evolution of fungicide resistance in the early blight pathogen Alternaria solani
<p>Supplementary Data for: Whole genome sequencing elucidates the species-wide diversity and evolution of fungicide resistance in the early blight pathogen Alternaria solani</p> <p>This repository contains:</p> <p>SNP call data / VCF file</p> <p>Scripts for all processing steps from mapping up to PCA and phylogenetic analyses (script.ts)<br> Scripts for population genomic analyses with LEA and PopGenome (scripts.SE)<br> All script names are self explanatory.</p>
Assessing reproduciblity of Inherited Variants Detected with Short-read Whole Genome Sequencing
<p>This dataset is part of the following study:</p> <p><a href="https://www.fda.gov/science-research/bioinformatics-tools/microarraysequencing-quality-control-maqcseqc">https://www.fda.gov/science-research/bioinformatics-tools/microarraysequencing-quality-control-maqcseqc</a></p> <p>The raw sequencing data can be downloaded from SRA:</p> <p><a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA723125">https://www.ncbi.nlm.nih.gov/bioproject/PRJNA723125</a></p> <p>and NODE:</p> <p><a href="https://www.biosino.org/node/project/detail/OEP0018966">https://www.biosino.org/node/project/detail/OEP0018966</a></p>
List of known SNP positions (based on SNP chip data) for base quality score recalibration of alignments for whole-genome resequencing and whole-genome bisulfite sequencing data from great tits (Parus major)
<p>The profiling of epigenetic marks like DNA methylation has become a central aspect of studies in evolution and ecology. Bisulfite sequencing is commonly used for assessing genome-wide DNA methylation at single nucleotide resolution but these data can also provide information on genetic variants like single nucleotide polymorphisms (SNPs). However, bisulfite conversion causes unmethylated cytosines to appear as thymines, complicating the alignment and subsequent SNP calling. Several tools have been developed to overcome this challenge, but there is no independent evaluation of such tools for non-model species, which often lack genomic references. Here, we used whole-genome bisulfite sequencing (WGBS) data from four female great tits (<i>Parus major</i>) to evaluate the performance of seven tools for SNP calling from bisulfite sequencing data. We used SNPs from whole-genome resequencing data of the same samples as baseline SNPs to assess common performance metrics like sensitivity, precision, and the number of true positive, false positive, and false negative SNPs for the full range of variant and genotype quality values. We found clear differences between the tools in either optimizing precision (Bis-SNP), sensitivity (biscuit), or a compromise between both (all other tools). Overall, the choice of SNP caller strongly depends on which performance parameter should be maximized and whether ascertainment bias should be minimized to optimize downstream analysis, highlighting the need for studies that assess such differences.</p>
Primers for whole genome sequencing of the Sars-Cov-2 virus
<p>Here is the primer sequence for amplification and sequencing of the whole genome of the Sars-Cov-2 virus.</p>
Appendix of the thesis "Acquisition of new genetic knowledge on strains of Mycobacterium bovis, circulating in France, by the whole genome sequencing approach." Ciriac CHARLES
<p>Appendix 1 Table showing the <em>Mycobacterium bovis </em>genome information used in this study in panel 1 The 87 genomes are from previous work (Hauer et al., 2019). The names of the genomes are highlighted with color to distinguish them within a previously defined M. bovis cluster. In Yellow Cluster I/Clonal Complex Eu3. In orange Cluster G/Family F9. In brown Cluster C/Family SB0134. In purple Cluster D/Clonal Complex Eu1. In pink the Cluster A/Family F4. In blue the Cluster F/Clonal Complex Eu2. In grey, the others.</p> <p>Appendix 2 Table showing the <em>Mycobacterium bovis </em>genome information used in this study in panel 3. The 187 genomes are of genotypes F7 and F15 (SB0821 and SB0832 respectively) which are two closely related genotypes. These genomes had already been sequenced before the start of the thesis work. Some were published with the work of Duault and collaborators and others have not yet been published (noted NA) (Duault et al., 2022).</p> <p>Appendix 3 Table showing the <em>Mycobacterium bovis </em>genome information used in this study in panel 4. The 227 genomes are of genotype SB0120-DHV. These genomes had already been sequenced before the start of the thesis work but are currently unpublished (noted NA in the columns "Date of deposit" and "Genbank biosample").</p> <p>Appendix 4 Position of IS<em>6110</em> insertion sites in the panel of <em>Mycobacterium bovis </em>strains from Pyrénées-Atlantiques (SB0821 and SB0832). The position of the start and end of IS<em>6110</em> are determined with the ISMapper tool and the reference genome AF2122/97.</p> <p>Appendix 5 Position of IS<em>6110</em> insertion sites in the <em>Mycobacterium bovis </em>strain panel of SB0120-DHV. Position of the start and end of IS<em>6110</em> are determined with the ISMapper tool and the Mb3601 reference genome.</p> <p>Appendix 6 This figure from the Modenesi internship report represents a circular consensus phylogenetic tree of 300 strains of SB0120-DHV (Modenesi 2019). The strains in panel 3 are part of these 300 strains and were selected according to their sequencing quality, which explains the smaller number of strains retained (227). This tree is divided into 11 different colored clades. The posterior probability values (which correspond to the probability that these clades are true) determined with Beast (Drummond and Rambaut, 2007) are represented inside the tree.</p>
Appendix of the thesis "Acquisition of new genetic knowledge on Mycobacterium bovis strains, circulating in France, by the whole genome sequencing approach", part "4. Sequencing of new complete genomes", Ciriac CHARLES
<p>Annex S1: Sequencing metric of the 10 new genomes and obtained with fastqc. A: Metric provide to Illumina metric. B: metric provide to MinION metric.</p> <p>Annex S2: Pan-genomic study performed on 12 <em>M. bovis</em> complete genomes. The table indicates the genes accessory. “1” shows the presence of CDS and “0” his absence.</p> <p>Annex S3: Indels between the ten new complete genomes and Mb3601 using progressiveMauve. Annotation of these indels was performed with reference genome comparison for gap or with the annotation (with Prokka) of the new complete genome studied for insertion. IS<em>6110</em> is marked in green. "Indel distribution" sheet shows the indel distribution on the <em>M. bovis</em> genome for the ten new complete genomes. Black arrows show the genomic region with the most of indel found.</p> <p>Annex S4: WgSNP analysis performed on 98 <em>M. bovis</em>. SNPs were annotated and selected according to their specificity to an <em>M. bovis</em> group described in Fig 5. The last common give information on the genetic impact of the SNP. The last sheet presents a graph of SNP number in genomic position.</p> <p>Annex S5: Alignments of the 12 <em>M. bovis </em>complete genomes.</p>
Serratia fonticola EBS19 Whole genome sequence data fasta file annotated
<p>Whole genome sequence data of <em>Serratia fonticola</em> <strong>EBS19 </strong>strain.</p>
Whole-genome capture and sequencing of Francisella tularensis directly from clinical samples
<p>This dataset comprises:</p> <p><strong>1. The design of RNA oligonucleotide baits for Agilent Technologies’ SureSelect target enrichment - <strong>54756 RNA oligonucleotide "baits" (120 bp each) </strong></strong>designed to perform <strong>whole-genome capture and sequencing of </strong><strong>Francisella tularensis<strong> directly from clinical samples</strong></strong> (DNA) using Agilent Technologies’ SureSelect target enrichment system following the Illumina paired-end multiplexed sequencing library protocol.</p> <p>RNA oligonucleotide “baits” were designed to span the <em>Francisella tularensis </em>chromosome and plasmid, accounting for the genetic variability among publicly available genome sequences. All resulting sequences were BLASTn searched against the Human Genomic + Transcript database to excluded homologous sequences to the human genome. Overall, a total of 54756 RNA probes were generated and this custom bait library was then uploaded to the SureDesign software (https://earray.chem.agilent.com/suredesign) and synthesized by Agilent Technologies.</p> <p><strong>2. Genome assemblies of 17 Francisella tularensis samples generated in the context of validation and application of SureSelect target enrichment for Whole-genome capture and sequencing of Francisella tularensis directly from clinical samples </strong></p> <p>File “<strong>Ft_assembly_metadata.xlsx</strong>” contains the genome assembly statistics for each isolate, including European Nucleotide Archive accession numbers.</p> <p>The archive “<strong>Ft_assemblies.zip</strong>” contains all the genome assemblies (.fasta format) of each isolate presented in the metadata file.</p> <p>More details can be found in the following publication: (available soon)</p>
Low-coverage whole genome sequencing for highly accurate population assignment: Mapping migratory connectivity in the American Redstart (Setophaga ruticilla)
<p>Understanding the geographic linkages among populations across the annual cycle is an essential component for understanding the ecology and evolution of migratory species and for facilitating their effective conservation. While genetic markers have been widely applied to describe migratory connections, the rapid development of new sequencing methods, such as low-coverage whole genome sequencing (lcWGS), provides new opportunities for improved estimates of migratory connectivity. Here, we use lcWGS to identify fine-scale population structure in a widespread songbird, the American Redstart (<em>Setophaga</em> <em>ruticilla</em>), and accurately assign individuals to genetically distinct breeding populations. Assignment of individuals from the nonbreeding range reveals population-specific patterns of varying migratory connectivity. By combining migratory connectivity results with demographic analysis of population abundance and trends, we consider full annual cycle conservation strategies for preserving numbers of individuals and genetic diversity. Notably, we highlight the importance of the Northern Temperate-Greater Antilles migratory population as containing the largest proportion of individuals in the species. Finally, we highlight valuable considerations for other population assignment studies aimed at using lcWGS. Our results have broad implications for improving our understanding of the ecology and evolution of migratory species through conservation genomics approaches.</p>
ScienceDex guides
Understand access before you commit
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.