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87 results for “human assemblies”
Eigen scores for human genome assembly GRCh38 Part 4 (Chr1 - Chr2)
<p>Eigen is a spectral approach to the functional annotation of genetic variants in coding and noncoding regions. Eigen makes use of a variety of functional annotations in both coding and noncoding regions (such as protein function scores, evolutionary conservation scores, and epigenetic annotations from ENCODE and Roadmap Epigenomics projects), and combines them into one single measure of functional importance. Eigen is an unsupervised approach, and, unlike many existing methods, is not based on any labelled training data. Eigen produces estimates of predictive accuracy for each functional annotation score, and subsequently uses these estimates of accuracy to derive the aggregate functional score for variants of interest as a weighted linear combination of individual annotations.</p>
Eigen scores for human genome assembly GRCh38 Part 3 (Chr3 - Chr5)
<p>Eigen is a spectral approach to the functional annotation of genetic variants in coding and noncoding regions. Eigen makes use of a variety of functional annotations in both coding and noncoding regions (such as protein function scores, evolutionary conservation scores, and epigenetic annotations from ENCODE and Roadmap Epigenomics projects), and combines them into one single measure of functional importance. Eigen is an unsupervised approach, and, unlike many existing methods, is not based on any labelled training data. Eigen produces estimates of predictive accuracy for each functional annotation score, and subsequently uses these estimates of accuracy to derive the aggregate functional score for variants of interest as a weighted linear combination of individual annotations.</p>
Human assemblies evaluated in the hifiasm paper
<p>Human assemblies evaluated in the <a href="https://www.nature.com/articles/s41592-020-01056-5">Cheng et al (2021)</a>. Non-human assemblies are available at <a href="https://zenodo.org/record/4393750">doi:10.5281/zenodo.4393750</a>. File "*.ONT.*" were generated by <a href="https://www.nature.com/articles/s41587-020-0503-6">Shafin et al (2020)</a>, "*.DipAsm*" by <a href="https://www.nature.com/articles/s41587-020-0711-0">Garg et al (2020)</a> and "*.PAGS*" by <a href="https://www.nature.com/articles/s41587-020-0719-5">Porubsky et al (2020)</a>. The rest of the assemblies were generated by Cheng et al.</p>
GenoNet scores for human genome assembly GRCh38
<p>Predicting the functional consequences of genetic variants in non-coding regions is a challenging problem. We propose here a semi-supervised approach, GenoNet, to jointly utilize experimentally confirmed regulatory variants (labeled variants), millions of unlabeled variants genome-wide, and more than a thousand cell/tissue type-specific epigenetic annotations to predict functional consequences of non-coding variants.</p> <p><strong>Format</strong></p> <p>The GenoNet scores are stored in the tab-delimited text files. </p> <p>Each row represents a genomic region with 131 columns. Please find the header line in "genonet.header.txt". </p> <p>The first four columns are chromosome, start coordinate, end coordinate, and a region ID named by positions. Please note that the coordinates are counted in the 0-based UCSC Genome Browser BED format. For example, the following region with a start position 10000 and an end position 10025 includes 25 base pairs within chr1:10001-10025.</p> <p>chr1 10000 10025 chr1_10001_10025</p> <p>Columns 5-131 are the predicted tissue-specific functional effects (GenoNet scores) for the 127 Roadmap tissues. Each column is named by the corresponding epigenome ID. This <a href="https://docs.google.com/spreadsheet/ccc?key=0Am6FxqAtrFDwdHU1UC13ZUxKYy1XVEJPUzV6MEtQOXc&usp=sharing">online spreadsheet</a> includes the information about the 127 Roadmap tissues in detail.</p> <p><strong>Reference</strong><br> Zihuai He, Linxi Liu, Kai Wang, Iuliana Ionita-Laza. A semi-supervised approach for predicting cell type/tissue specific functional consequences of non-coding variation using massively parallel reporter assays. Nature Communications, 2018.</p> <p><strong>Release</strong></p> <p>GRCh37 <a href="https://zenodo.org/record/3336209">https://zenodo.org/record/3336209</a></p> <p>GRCh38 liftover <a href="https://zenodo.org/record/6484230">https://zenodo.org/record/6484230</a></p>
GenoNet scores for human genome assembly GRCh37
<p>Predicting the functional consequences of genetic variants in non-coding regions is a challenging problem. We propose here a semi-supervised approach, GenoNet, to jointly utilize experimentally confirmed regulatory variants (labeled variants), millions of unlabeled variants genome-wide, and more than a thousand cell/tissue type specific epigenetic annotations to predict functional consequences of non-coding variants.</p> <p><strong>Format</strong></p> <p>The GenoNet scores are stored in the tab-delimited text files. </p> <p>Each row represents a genomic region with 131 columns. Please find the header line in "genonet.header.txt". </p> <p>The first four columns are chromosome, start coordinate, end coordinate, and a region ID named by positions. Please note that the coordinates are counted in the 0-based UCSC Genome Browser BED format. For example, the following region with a start position 10000 and an end position 10025 includes 25 base pairs within chr1:10001-10025.</p> <p>chr1 10000 10025 chr1_10001_10025</p> <p>Columns 5-131 are the predicted tissue-specific functional effects (GenoNet scores) for the 127 Roadmap tissues. Each column is named by the corresponding epigenome ID. This <a href="https://docs.google.com/spreadsheet/ccc?key=0Am6FxqAtrFDwdHU1UC13ZUxKYy1XVEJPUzV6MEtQOXc&usp=sharing">online spreadsheet</a> includes the information about the 127 Roadmap tissues in detail.</p> <p><strong>Reference</strong><br> Zihuai He, Linxi Liu, Kai Wang, Iuliana Ionita-Laza. A semi-supervised approach for predicting cell type/tissue specific functional consequences of non-coding variation using massively parallel reporter assays. Nature Communications, 2018.</p> <p><strong>Release</strong></p> <p>GRCh37 <a href="https://zenodo.org/record/3336209">https://zenodo.org/record/3336209</a></p> <p>GRCh38 liftover <a href="https://zenodo.org/record/6484230">https://zenodo.org/record/6484230</a></p>
Metagenomic assembly and bin3C clustering result for a healthy human faecal microbiome transplant donor
<p>Metagenomic WGS assembly and Hi-C deconvolution of a healthy human faecal microbiome transplant donor.</p> <p>Metagenomic assembly was produced using Spades (v3.13.1).</p> <p>Extracted MAGs were produced using bin3C (v0.3.3) and QC'd using CheckM (v1.0.18).</p>
Non-human assemblies evaluated in the hifiasm paper
<p>Non-human assemblies evaluated in <a href="https://www.nature.com/articles/s41592-020-01056-5">Cheng et al (2021)</a>. Human assemblies are available via <a href="https://zenodo.org/record/4393631">doi:10.5281/zenodo.4393631</a>.</p>
Tandem repeat catalog of the human genome generated from long-read assemblies
<p>Allele sequences of polymorphic loci (VCF) and README for all version 2 (2.0 + 2.1) files</p>
A collection of high-quality human assemblies
<p>A collection of high-quality human assemblies, including:</p> <ul> <li><a href="https://github.com/marbl/CHM13">T2T-CHM13</a> v2.0 analysis set with HG002 chrY and rCRS chrM</li> <li>GRCh38 <a href="https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/000/001/405/GCA_000001405.15_GRCh38/seqs_for_alignment_pipelines.ucsc_ids/">no-alt analysis set</a> with rCRS chrM</li> <li><a href="https://www.nature.com/articles/s41422-023-00849-5">CN1</a> v1.0.1</li> <li><a href="https://www.sciencedirect.com/science/article/pii/S1672022923001006">YAO</a> v1.1</li> <li><a href="https://www.nature.com/articles/s41597-024-04121-2">KSA001</a> v1.1.0</li> <li>232 HPRC r2/v0.6 samples (464 assemblies; HG00272 has a ~50Mb inversion misassembly)</li> </ul> <p>Use <a href="https://github.com/refresh-bio/agc/releases">AGC</a> to extract indivual genomes and use <a href="https://github.com/lh3/ropebwt3">ropebwt3</a> to query the FM-index:</p> <blockquote> <p>agc listset human472.agc # list genomes<br>agc getset human472.agc 200149_HG02523.pat > HG02523.pat.fa # extract one genome<br>gzip -d human472.fmr.gz # decompress the incremental index<br>ropebwt3 build -i human472.fmr -do human472.fmd # convert to a faster query format<br>gzip -d human472.fmd.ssa.gz # decompress suffix array samples<br>echo CCAGGACCCCTGTCCAGTGTTAGACAGGAGCATGCAG | ropebwt3 sw -eN200 -Lm10 human472.fmd -</p> </blockquote> <p><strong>Note:</strong> The HPRC assemblies are already available from GenBank. This repository only provides a convenient way to download them. However, these assemblies are not formally published. You may use them for algorithm development or performance evaluation. If you want to use the genomes for biological discovery, please <a href="https://humanpangenome.org/contact/">contact HPRC</a>.</p>
Raw microscopy data from: Endoplasmic reticulum stress activates human IRE1α through reversible assembly of inactive dimers into small oligomers
<p>Protein folding homeostasis in the endoplasmic reticulum (ER) is regulated by a signaling network, termed the unfolded protein response (UPR). Inositol-requiring enzyme 1 (IRE1) is an ER membrane-resident kinase/RNase that mediates signal transmission in the most evolutionarily conserved branch of the UPR. Dimerization and/or higher-order oligomerization of IRE1 are thought to be important for its activation mechanism, yet the actual oligomeric states of inactive, active, and attenuated mammalian IRE1 complexes remained unknown. We developed an automated two-color single-molecule tracking approach to dissect the oligomerization of tagged endogenous human IRE1 in live cells. In contrast to previous models, our data indicate that IRE1 exists as a constitutive homodimer at baseline and assembles into small oligomers upon ER stress. We demonstrate that the formation of inactive dimers and stress-dependent oligomers is fully governed by IRE1's lumenal domain. Phosphorylation of IRE1's kinase domain occurs more slowly than oligomerization and is retained after oligomers disassemble back into dimers. Our findings suggest that assembly of IRE1 dimers into larger oligomers specifically enables trans- autophosphorylation, which in turn drives IRE1's RNase activity.</p> <p> </p>
ATAC-seq processing resources for the GRCh38 (hg38) assembly of the human genome
<p>A collection of publicly available, but preprocessed, reference data for the analysis of ATAC-seq samples using the GRCh38 (hg38) assembly of the human genome using the <a href="https://doi.org/10.5281/zenodo.6323634">Ultimate ATAC-seq Data Processing & Analysis Pipeline</a> (details in the documentation on GitHub).</p>
Mappability tracks for human assemblies (hg19 and GRCh38)
<p>They were created by using the GEM mapper aligner (Derrien et al., 2012) allowing up to two mismatches and considering sliding windows of 100-mer. They are exploited by the EXCAVATOR2 tool for reducing technical biases of Read Count measure in WES/TS experiments.</p>
Data for: Community assembly of the human piercing microbiome
<p>Predicting how biological communities respond to disturbance requires understanding the forces that govern their assembly. We propose using human skin piercings as a model system for studying community assembly after rapid environmental change. Local skin sterilization provides a 'clean slate' within the novel ecological niche created by the piercing. Stochastic assembly processes can dominate skin microbiomes due to the influence of environmental exposure on local dispersal, but deterministic processes might play a greater role within occluded skin piercings if piercing habitats impose strong selection pressures on colonizing species. Here we explore the human ear-piercing microbiome and demonstrate that community assembly is predominantly stochastic but becomes significantly more deterministic with time, producing increasingly diverse and ecologically complex communities. We also observed changes in two dominant and medically relevant antagonists (<em>Cutibacterium acnes </em>and <em>Staphylococcus epidermidis</em>), consistent with competitive exclusion induced by a transition from sebaceous to moist environments. By exploiting this common yet uniquely human practice, we show that skin piercings are not just culturally significant but also represent ecosystem engineering on the human body. The novel habitats and communities that skin piercing produce may provide general insights into biological responses to environmental disturbance with implications for both ecosystem and human health.</p>
Cryo-ET tilt series of human GBP1 coatomers assembled on SUVs
<p>Uncorrected frame stacks of cryo-tomographic tilt series acquired for human GBP1 coaotomers assembled on small unilamellar vesicles.</p>
Metagenome assembled genome database of a human cohort and fecal reactors
<p><strong>HumanCohort_annotations.tsv.zip:</strong> This is the custom MAG database (n=2447 MAGs) and corresponding annotations that were used in Borton 2022: "Targeted curation of the gut microbial gene content modulating human cardiovascular disease". The citation will be updated upon publication of the manuscript. Metagenome assembled genomes were generated from fecal metagenomes derived from a 54 person cohort and anoxic methylated amine enrichments. </p> <p><strong>HumanCohortmetabolism_summary.xlsx.zip: </strong> This is the annotation summary for 2447 MAGs in the cohort database. </p> <p><strong>Quality_Abundance_CohortMAGs.xlsx: </strong>This is a genome inventory of the 2447 MAGs in the cohort database including genome statistics and relative abundance. </p> <p><strong>orig_1D_NMR_fids.zip: </strong>NMR data derived from anoxic methylated amine enrichments. </p>
The human origin recognition complex (ORC) is essential for pre-RC assembly, mitosis and maintenance of nuclear structure
Open the record for dataset details and reuse information.
Data for: Community assembly of the human piercing microbiome
Open the record for dataset details and reuse information.
Raw microscopy data from: Endoplasmic reticulum stress activates human IRE1α through reversible assembly of inactive dimers into small oligomers
Open the record for dataset details and reuse information.
Training data for 'Unicycler assembly of SARS-CoV-2 genome with preprocessing to remove human genome reads' tutorial (Galaxy Training Material)
<p>The data here is a copy of the corresponding SRR records in the NCBI SRA. The duplication serves a dual purpose:</p> <ol> <li>as a backup should there be problems connecting to NCBI servers, e.g., during Galaxy user trainings.</li> <li>to illustrate how to obtain raw sequencing data from alternative sources, and to organize the data into the same collection structure in a Galaxy history that is generated by specialized Galaxy SRA download tools.</li> </ol>
Eigen scores for human genome assembly GRCh37 Part 1 (Chr1 - Chr3)
<p>Eigen is a spectral approach to the functional annotation of genetic variants in coding and noncoding regions. Eigen makes use of a variety of functional annotations in both coding and noncoding regions (such as protein function scores, evolutionary conservation scores, and epigenetic annotations from ENCODE and Roadmap Epigenomics projects), and combines them into one single measure of functional importance. Eigen is an unsupervised approach, and, unlike many existing methods, is not based on any labelled training data. Eigen produces estimates of predictive accuracy for each functional annotation score, and subsequently uses these estimates of accuracy to derive the aggregate functional score for variants of interest as a weighted linear combination of individual annotations.</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
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Annotated Behaviour and Observability Dataset (ABODe)
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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.