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105 results for “Omicron”
Risk and symptoms of COVID-19 in health professionals according to baseline immune status and booster vaccination during the Delta and Omicron waves in Switzerland – a multicentre cohort study
<p>For details, see publication</p>
Supplementary Data: OpenCOVID model output underlaying Figures 1 and 2 of "Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden"
<p>Supplementary data files <strong>Figure_1.xlsx</strong> and <strong>Figure_2.xlsx</strong> contain the model simulation outcomes for Figures 1 and 2 of <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al</em></a> "<strong>Modelling the impact of Omicron and emerging variants on SARS-CoV-2 transmission and public health burden</strong>" (2022)</p> <ul> <li><strong>Figure 1</strong>: Peak daily hospital occupancy (number of beds per 100,000 population over the six-month simulation period) for three variant properties; infectivity (relative to Delta), immune evading capacity (%), and severity (relative to Delta)<br> </li> <li><strong>Figure 2</strong>: Percentage of COVID-19 infections and deaths averted by third-dose vaccines for adults and vaccinating 5-11-year-olds with doses one and two.<br> </li> <li>Open access source-codes of the associated plotting functions are published <a href="http://zenodo.org/record/6532404#.Yqw7cezMKdb">here</a> on Zenodo.<br> </li> <li>Open access source-codes for the OpenCOVID model of all analyses as presented in <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al.</em> (2022)</a> are publicly available at <a href="https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src">https://github.com/SwissTPH/OpenCOVID/tree/manuscript_december_2021/src</a>.<br> </li> <li>Detailed model descriptions and model equations of individual-based transmission model <strong>OpenCOVID</strong> are described in <a href="https://pubmed.ncbi.nlm.nih.gov/34923396/">Shattock <em>et al</em>. (2022)</a> and <a href="https://www.medrxiv.org/content/10.1101/2021.12.12.21267673v2">Le Rutte, Shattock <em>et al.</em> (2022).</a></li> </ul>
Results: Modeling the impact of the Omicron infection wave in Germany
<p># Modeling the impact of the Omicron infection wave in Germany</p> <p>This repository contains results of a modelling study regarding the spread of SARS-CoV-2 VOC "Omicron" in Germany.</p> <p>## Columns and values</p> <p>| column name | type | description EN | description DE |<br> | -- | -- | -- | -- |<br> | `infectious_period_both` | int | Mean infectious period (in days) for both variants | Mittlere Infektiositaetsperiode fuer beide Varianten (in Tagen) |<br> | `omicron_latent_period` | int | Mean latent period of VOC Omicron (in days) | Mittlere Latenzzeit der VOC Omikron (in Tagen) |<br> | `booster_reach` | str | Reach of the booster campaign | Reichweite der Auffrischkampagne |<br> | `booster_VE` | str | Vaccine efficacy of the booster vaccination | Impfeffektivitaet der Auffrischimpfung |<br> | `contact_reduction_scenario_id` | int | ID of the contact reduction scenario | ID des Kontaktreduktionsszenarios |<br> | `contact_reduction_strength` | float | prefactor with which the contact modulation f(t) is multiplied | Vorfaktor, mit der die Kontaktmodulation f(t) waehrend der Kontaktreduktionsperiode skaliert wird |<br> | `contact_reduction_start` | date (ISO 8601) | Date when contact reduction begins | Beginn der Kontaktreduktion |<br> | `contact_reduction_end` | date (ISO 8601) | Date when contact reduction ends | Ende der Kontaktreduktion |<br> | `relative_risk_hospitalization` | float | Relative risk (RR) of hospitalization after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Hospitalisierung nach Infektion mit Omicron gegenueber Infektion mit Delta |<br> | `relative_risk_icu` | float | Relative risk (RR) of ICU admission after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Intensivpflichtigkeit nach Infektion mit Omicron gegenueber Infektion mit Delta |<br> | `value_type` | str | Wich value is shown in the `value` column | Art des Wertes in der Spalte `value` |<br> | `date` | date (ISO 8601) | Date associated with the modeling result given in column `value` | Datum assoziiert mit dem Modellergebnis des Wertes in der Spalte `value` |<br> | `value` | int | Model result (rounded to nearest integer) | Modellergebnis (gerundet auf ganze Zahl) |</p> <p>Additional columns regarding combinations of plausible scenarios (rounded to nearest integer) and 180 stochastic simulations per parameter combination:</p> <p>| column name | type | description EN | description DE |<br> | -- | -- | -- | -- |<br> | `95_PI_lower` | int | 95% PI lower bound (rounded to nearest integer) | Untere Schranke des 95% PIs (gerundet auf ganze Zahl) |<br> | `50_PI_lower` | int | 50% PI lower bound (rounded to nearest integer) | Untere Schranke des 50% PIs (gerundet auf ganze Zahl) |<br> | `median` | int | median (rounded to nearest integer) | Median (gerundet auf ganze Zahl) |<br> | `50_PI_upper` | int | 50% PI upper bound (rounded to nearest integer) | Obere Schranke des 50% PIs (gerundet auf ganze Zahl) |<br> | `95_PI_upper` | int | 95% PI upper bound (rounded to nearest integer) | Obere Schranke des 95% PIs (gerundet auf ganze Zahl) |</p> <p>### Values: `booster_reach`</p> <p>| value | description EN | description DE |<br> | -- | -- | -- |<br> | `md` | medium booster campaign reach (80% of those that received full vaccination in 2021 receive booster vaccination) | Medium, 80% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung |<br> | `hi` | high booster campaign reach (100% of those that received full vaccination in 2021 receive booster vaccination) | Hoch, 100% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung |<br> | `hi-and-90perc-2dose` | 100% receive booster vaccination and vaccine uptake of first immunization suddenly increases to 90% in Jan 2022 | 100% erhalten Auffrischimpfung und Impfquote der Erstimmunisierung erreicht schnell 90% im Januar 2022 | </p> <p><br> ### Values: `booster_VE`</p> <p>| value | description EN | description DE |<br> | -- | -- | -- |<br> | `lo` | low booster vaccine efficacy (assumption: booster protects as well against infection as 2nd dose) | Niedrige Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie 2 Dosen) |<br> | `hi` | high booster vaccine efficacy (assumption: booster protects as well against infection as against symptomatic disease) | Hohe Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie vor symptomatischer Erkrankung) |</p> <p>### Values: `value_type`</p> <p>| value | description EN | description DE |<br> | -- | -- | -- |<br> | `inc` | incidence (absolute number of new reported cases per day) | Inzidenz (Zahl der gemeldeten Neuinfektion an diesem Tag, absolut) |<br> | `hsp` | hospitalization incidence (absolute number of new hospital admissions per day) | Hospitalisierungsinzidenz (Zahl der gemeldeten Neuhospitalisierungen an diesem Tag, absolut) |<br> | `icu` | total number of patients in ICUs | Gesamtzahl der intensivpflichtigen Patient:innen |</p> <p>## License</p> <p>Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).<br> </p>
WT, Delta and Omicron RBDs Adsorption onto Hydrophobic, Hydrophilic Surfaces and Biological Interfaces
<p>Simulations (trajectories) and analysis of the 3 VoCs RBDs of the SARS-CoV-2.</p> <p>For more information go to this article: https://doi.org/10.1021/acs.jcim.4c00460</p>
Electron microscopy images and morphometric data of SARS-CoV-2 variants in ultrathin plastic sections - Dataset 06 (SARS-CoV-2 Omicron B.1.1.529; BA.2)
<p>Dataset 06 comprises 164 transmission electron microscopy images of extracellular SARS-CoV-2 (isolate Omicron B.1.1.529; BA.2) particles in ultrathin plastic sections (45 nm) through Vero cell cultures. The images were recorded with dimensions of 4112 x 3008 pixels at a pixel size of 0.1641 nm and stored in 16-bit TIF format. It is recommended that an image viewer capable of reading 16-bit images, such as IrfanView, be used to visualize the images. The image files have been size calibrated and can be opened with the correct size calibration using ImageJ or Fiji with the Bioformats importer. A PDF document is provided with the image files, which describes the methods used for the generation of the images. Additionally, an XLSX file is included, offering morphometric particle measurements and the calculated statistical values for their distribution. The dataset was produced as dataset 06 for a comparative morphometric analysis of evolving SARS-CoV-2 variants. Further datasets used for the analysis are available in this repository (see dataset description document).</p>
Figures 44. Omicron aridum new species. A-B in Vespidae (Insecta: Hymenoptera) of Puerto Rico, West Indies
Figures 44. Omicron aridum new species. A-B) habitat in Guayanilla. C) female inspecting an old nest. D) female transporting a moth larva for provisioning the nest. Nests attached to: E) cactus, Pilosocereus royenii; F) a plant stem; G) screen of a greenhouse; H) PVC tube.
Adsorption of the WT, delta and omicron variants onto hydrophobic and hydrophilic surfaces
<p>Adsorption of the WT, delta and omicron variants onto hydrophobic and hydrophilic surfaces. This contains 3 replicas of each.</p>
Results: Modeling the impact of the Omicron infection wave in Germany
<pre>Results: Modeling the impact of the Omicron infection wave in Germany This repository contains results of a modeling study regarding the spread of SARS-CoV-2 VOC "Omicron" in Germany. ## Columns and values | column name | type | description EN | description DE | | -- | -- | -- | -- | | `infectious_period_both` | int | Mean infectious period (in days) for both variants | Mittlere Infektiositaetsperiode fuer beide Varianten (in Tagen) | | `omicron_latent_period` | int | Mean latent period of VOC Omicron (in days) | Mittlere Latenzzeit der VOC Omikron (in Tagen) | | `booster_reach` | str | Reach of the booster campaign | Reichweite der Auffrischkampagne | | `booster_VE` | str | Vaccine efficacy of the booster vaccination | Impfeffektivitaet der Auffrischimpfung | | `contact_reduction_scenario_id` | int | ID of the contact reduction scenario | ID des Kontaktreduktionsszenarios | | `contact_reduction_strength` | float | prefactor with which the contact modulation f(t) is multiplied | Vorfaktor, mit der die Kontaktmodulation f(t) waehrend der Kontaktreduktionsperiode skaliert wird | | `contact_reduction_start` | date (ISO 8601) | Date when contact reduction begins | Beginn der Kontaktreduktion | | `contact_reduction_end` | date (ISO 8601) | Date when contact reduction ends | Ende der Kontaktreduktion | | `relative_risk_hospitalization` | float | Relative risk (RR) of hospitalization after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Hospitalisierung nach Infektion mit Omicron gegenueber Infektion mit Delta | | `relative_risk_icu` | float | Relative risk (RR) of ICU admission after infection with Omicron as compared to infection with Delta | Relatives Risiko (RR) der Intensivpflichtigkeit nach Infektion mit Omicron gegenueber Infektion mit Delta | | `value_type` | str | Wich value is shown in the `value` column | Art des Wertes in der Spalte `value` | | `date` | date (ISO 8601) | Date associated with the modeling result given in column `value` | Datum assoziiert mit dem Modellergebnis des Wertes in der Spalte `value` | | `value` | int | Model result (rounded to nearest integer) | Modellergebnis (gerundet auf ganze Zahl) | Additional columns regarding combinations of plausible scenarios (rounded to nearest integer) and 180 stochastic simulations per parameter combination: | column name | type | description EN | description DE | | -- | -- | -- | -- | | `95_PI_lower` | int | 95% PI lower bound (rounded to nearest integer) | Untere Schranke des 95% PIs (gerundet auf ganze Zahl) | | `50_PI_lower` | int | 50% PI lower bound (rounded to nearest integer) | Untere Schranke des 50% PIs (gerundet auf ganze Zahl) | | `median` | int | median (rounded to nearest integer) | Median (gerundet auf ganze Zahl) | | `50_PI_upper` | int | 50% PI upper bound (rounded to nearest integer) | Obere Schranke des 50% PIs (gerundet auf ganze Zahl) | | `95_PI_upper` | int | 95% PI upper bound (rounded to nearest integer) | Obere Schranke des 95% PIs (gerundet auf ganze Zahl) | ### Values: `booster_reach` | value | description EN | description DE | | -- | -- | -- | | `md` | medium booster campaign reach (80% of those that received full vaccination in 2021 receive booster vaccination) | Medium, 80% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung | | `hi` | high booster campaign reach (100% of those that received full vaccination in 2021 receive booster vaccination) | Hoch, 100% derjenigen, die in 2021 vollstaendig geimpft wurden, erhalten eine Auffrischimpfung | | `hi-and-90perc-2dose` | 100% receive booster vaccination and vaccine uptake of first immunization suddenly increases to 90% in Jan 2022 | 100% erhalten Auffrischimpfung und Impfquote der Erstimmunisierung erreicht schnell 90% im Januar 2022 | ### Values: `booster_VE` | value | description EN | description DE | | -- | -- | -- | | `lo` | low booster vaccine efficacy (assumption: booster protects as well against infection as 2nd dose) | Niedrige Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie 2 Dosen) | | `hi` | high booster vaccine efficacy (assumption: booster protects as well against infection as against symptomatic disease) | Hohe Impfeffektivitaet (Auffr. schuetzt genauso gut vor Infektion wie vor symptomatischer Erkrankung) | ### Values: `value_type` | value | description EN | description DE | | -- | -- | -- | | `inc` | incidence (absolute number of new reported cases per day) | Inzidenz (Zahl der gemeldeten Neuinfektion an diesem Tag, absolut) | | `hsp` | hospitalization incidence (absolute number of new hospital admissions per day) | Hospitalisierungsinzidenz (Zahl der gemeldeten Neuhospitalisierungen an diesem Tag, absolut) | | `icu` | total number of patients in ICUs | Gesamtzahl der intensivpflichtigen Patient:innen | ## License Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/).</pre>
Adsorption patterns of the WT, delta and omicron variants onto hydrophobic and hydrophilic surfaces
<p>Adsorption of the WT, delta and omicron variants onto hydrophobic and hydrophilic surfaces. This contains 3 replicas of each.</p>
SARS-CoV-2 Omicron Boosting Induces De Novo B Cell Response in Humans
<p>These are the<strong> processed</strong> BCR repertoire and transcriptomics data described in <a href="https://doi.org/10.1038/s41586-023-06025-4">Alsoussi & Malladi et al., <em>Nature</em>, 2023</a>. The <strong>raw</strong> sequencing data new to this study are available on SRA under BioProject <a href="https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA800176">PRJNA800176</a>. This study also used BCR repertoire data from <a href="https://doi.org/10.1038/s41586-021-03738-2">Turner & O'Halloran et al., <em>Nature</em>, 2021</a> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA731610">PRJNA731610</a>), <a href="https://doi.org/10.1016/j.immuni.2021.08.013">Schmitz, Turner & Liu et al., <em>Immunity</em>, 2021</a> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA741267">PRJNA741267</a>), and <a href="https://doi.org/10.1038/s41586-022-04527-1">Kim & Zhou et al., <em>Nature</em>, 2022</a> (<a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA777934/">PRJNA777934</a>).</p> <p> </p> <p><strong>Code</strong></p> <p>Code along with Docker containers for reproducing the NGS data-based figures and analyses in the published paper can be <a href="https://github.com/julianqz/wustl_published/tree/main/nature_2023">found on GitHub</a>.</p> <p> </p> <p><strong>Metadata</strong></p> <p>File: WU382_alsoussi_et_al_nature_2023_meta.tsv.gz</p> <p>Notes:</p> <ul> <li>181 samples in total, including: <ul> <li>78 new</li> <li>90 from <a href="https://doi.org/10.1038/s41586-022-04527-1">Kim & Zhou et al., <em>Nature</em>, 2022</a></li> <li>8 from <a href="https://doi.org/10.1016/j.immuni.2021.08.013">Schmitz, Turner & Liu et al., <em>Immunity</em>, 2021</a></li> <li>5 from <a href="https://doi.org/10.1038/s41586-021-03738-2">Turner & O'Halloran et al., <em>Nature</em>, 2021</a></li> </ul> </li> <li>Participant IDs: 6 participants who were in previous studies and who continued in the new study were referenced by new participant IDs. Correspondence with previous participant IDs is as follows: <ul> <li>382-01 = 368-22</li> <li>382-02 = 368-20</li> <li>382-07 = 368-02a</li> <li>382-08 = 368-04</li> <li>382-13 = 368-01a</li> <li>382-15 = 368-10</li> </ul> </li> <li>Sample collection time was originally recorded in days in the `timepoint` column. Values in parentheses indicate variations in which the BCR data was coded. Timepoints were mainly referenced in weeks in the manuscript, as shown in the `timepoint_ms` column. </li> <li>Pre-3rd dose ("pre-boost") samples were coded `b0` in the `booster_num` column; post-3rd dose ("post-boost") samples were coded `b1`.</li> <li>The `booster_type` column records the 3rd dose ("booster") variant. <ul> <li>`regular` = mRNA-1273 (WA1/2020)</li> <li>`beta_delta` = mRNA-1273.213 (Beta & Delta)</li> <li>`v1.1.529` = mRNA-1273.529 (Omicron)</li> </ul> </li> <li>382-02/07/08 received mRNA-1273; 382-01/13/15 received mRNA-1273.213; 382-53/54/55 received mRNA-1273.529.</li> <li>The `seq_type` column indicates the platform from which sequences originated. <ul> <li>`bulk` = bulk BCR sequencing</li> <li>`tgx` = 10x Genomics single-cell VDJ + 5' gene expression</li> <li>`mab`, `mab_1`, `mab_2`: single-cell sorted mAb synthesis. The suffixes were purely for the convenience of distinguishing originating studies.</li> </ul> </li> </ul> <p>Abbreviations:</p> <ul> <li>LN = lymph node</li> <li>BM = bone marrow</li> <li>PB = plasmablast</li> <li>GC = germinal centre</li> <li>LLPC = long-lived plasma cell</li> <li>NS = no sorting</li> <li>mAb = monoclonal antibody</li> </ul> <p> </p> <p><strong>[Beta & Delta booster] Processed BCR data - heavy chains</strong></p> <p>File: WU382_alsoussi_et_al_nature_2023_betaDelta_bcr_heavy.tsv.gz</p> <p><em>Analysis was based on heavy chain-based clonal inference.</em></p> <p>Notes on columns:</p> <p>The columns largely follow the <a href="https://changeo.readthedocs.io/en/stable/standard.html">AIRR-C Rearrangement format</a>. The main deviation is that CDR3s were used, as opposed to IMGT-defined "junctions". Nonetheless, junction-related columns are included here as some repositories such as <a href="https://gateway.ireceptor.org/login"><em>iReceptor</em></a> use these. Non-standard columns are noted below.</p> <ul> <li>`cell_id`: Only sequences from single-cell samples and synthesized mAbs have cell IDs. 10x sequences follow the format `[donor]_[sample]@[id]`. `NA` for bulk sequences.</li> <li>`sequence_id`: Sequence IDs follow the format `[donor]_[sample]@[id]`.</li> <li>`v_call_genotyped`: V gene annotation reassigned after individualized genotyping by <a href="https://tigger.readthedocs.io/en/stable/">TIgGER</a>.</li> <li>`germline_[vdj]_call`: Clonal consensus germline calls after corresponding clonal consensus sequences were reconstructed via <a href="https://changeo.readthedocs.io/en/stable/methods/germlines.html">`CreateGermlines.py --cloned` from Change-O</a>.</li> <li>`collapse_count`: Number of duplicate IMGT-aligned V(D)J sequences that were collapsed by <a href="https://alakazam.readthedocs.io/en/stable/topics/collapseDuplicates/">`alakazam::collapseDuplicates`</a>.</li> <li>`timepoint`: Timepoints follow the format `b[01]_d*`, where `b0` and `b1` correspond to pre-3rd dose ("pre-boost") and post-3rd dose ("post-boost") respectively, and `d*` indicates the timepoint in days. There's one exception: `b0_m6or9` for pre-3rd dose d201 or d280 (m6or9 = 6 or 9 months).</li> <li>`gex_anno`: Cell type identity annotation based on transcriptomic profiles. Mapped from `anno_leiden_0.35` from WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cells.h5ad.</li> <li>`compartment`: B cell compartment</li> <li>`clone_id`: B cell clonal lineage IDs follow the format `[donor]@[id]`.</li> <li>`s_pos_clone`: `TRUE` if a sequence belonged to a B cell clone that was designated as S-binding by virtue of containing one of the recombinant mAbs that tested positive via ELISA.</li> <li>`expressed_id`: mAb IDs of mAbs from <a href="https://doi.org/10.1038/s41586-021-03738-2">Turner & O'Halloran et al., <em>Nature</em>, 2021</a> and the current study; and of recombinant mAbs generated based on 10x BCRs from <a href="https://doi.org/10.1038/s41586-022-04527-1">Kim & Zhou et al., <em>Nature</em>, 2022</a>. `NA` for everything else.</li> <li>`elisa`: ELISA results for binding of recombinant mAbs to SARS-CoV-2 S. `TRUE` if positive (WA1+); `FALSE` if negaive; `NA` if not tested or test failed.</li> <li>`nuc_RS_19_312`: number of replacement and silent mutations between IMGT-numbered nucleotide positions 19-312 along IGHV sequences, calculated by <a href="https://shazam.readthedocs.io/en/stable/topics/calcObservedMutations/">`shazam::calcObservedMutations`</a>.</li> <li>`nuc_denom_19_312`: number of informative nucleotide positions for counting mutations, excluding non-A/T/G/C positions (such as "N", "-", ".").</li> <li>`nuc_RS_freq_19_312`: nucleotide-level mutation frequency (= nuc_RS_19_312 / nuc_denom_19_312).</li> </ul> <p> </p> <p><strong>[Beta & Delta booster] Processed BCR data - light chains</strong></p> <p>File: WU382_alsoussi_et_al_nature_2023_betaDelta_bcr_light.tsv.gz</p> <p><em>Light chains were not used for heavy chain-based clonal inference or analysis.</em></p> <p> </p> <p><strong>[Beta & Delta booster] Processed transcriptomics data</strong></p> <p>Files: </p> <ul> <li>WU382_alsoussi_et_al_nature_2023_betaDelta_gex_all_cells.h5ad</li> <li>WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cells.h5ad</li> <li>WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cell_umap.tsv.gz</li> </ul> <p>Notes on the `h5ad` files:</p> <ul> <li>These files can be imported into <a href="https://scanpy.readthedocs.io/en/stable/index.html">Scanpy</a> as an <a href="https://scanpy.readthedocs.io/en/stable/usage-principles.html#anndata">AnnData object</a>.</li> <li>Each `AnnData` object has 3 `.layers`, each representing a version of the count matrix. <ul> <li>`raw_counts`: Imported from `<a href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/6.0/using/aggregate">cellranger aggr</a>` output by `scanpy.read_10x_mtx`.</li> <li>`log_norm`: Log-noramlized expression values outputted by `scanpy.pp.normalize_total` followed by `scanpy.pp.log1p`.</li> <li>`scaled`: The `log_norm` layer scaled to unit variance and zero mean by `scanpy.pp.scale`. </li> </ul> </li> <li>The `gene_name` and `biotype` columns in `.var` were extracted from GENCODE v32 GTF.</li> <li>Columns in `.obs` (each row corresponds to a cell) <ul> <li>`n_feature`: The `n_genes_by_counts` column produced by `scanpy.pp.calculate_qc_metrics`, renamed. The number of genes expressed. This is before subsetting the genes.</li> <li>`n_umi`: The `total_counts` column produced by `scanpy.pp.calculate_qc_metrics`, renamed. The total UMI counts in a cell.</li> <li>`pct_mt`: The `pct_counts_mt` column produced by `scanpy.pp.calculate_qc_metrics`, renamed. The percentage of counts in mitochondrial genes.</li> <li>`n_hkg`: The number of housekeeping genes for which expression was detected.</li> <li>`n_gene_expressed`: The total number of genes for which expression was detected. This is after subsetting the genes.</li> <li>`pre_qc_bcr`: `TRUE` if a cell also had paired BCR data available. Produced by cross-referencing the cellular barcodes in `cell_barcodes.json` outputted by `cellranger vdj`. At this point the BCR data had not gone through the QC process in the BCR processing pipeline (hence `pre_qc`). </li> <li>`leiden_[resolution]`: Cluster assignment by `scanpy.tl.leiden`.</li> <li>`anno_leiden_[resolution]`: Cell type identity annotations based on transcriptomic profiles. This was mapped onto the `gex_anno` column in the processed heavy chain BCR data.</li> </ul> </li> <li>UMAP coordinates can be found in `.obsm["X_umap"]`.</li> <li>`.X` has been set to `None` in order to reduce file size.</li> </ul> <p>Note on the `tsv.gz` file: This file was derived from WU382_alsoussi_et_al_nature_2023_betaDelta_gex_b_cells.h5ad. It contains UMAP coordinates and select attributes of the cells, including their log-normalized expression values of XBP1 (`ln_XBP1`). For analysis and visualization in conjunction with BCR data.</p> <p>In addition, the preprocessed count matrix outputted by `<a href="https://support.10xgenomics.com/single-cell-gene-expression/software/pipelines/6.0/using/aggregate">cellranger aggr</a>` is available from <a href="https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE227562">GEO under BioProject PRJNA800176</a>.</p> <p> </p> <p><strong>[Omicron booster] Processed BCR data - heavy chains</strong></p> <p>File: WU382_alsoussi_et_al_nature_2023_omicron_bcr_heavy.tsv.gz</p> <p>Notes on columns:</p> <ul> <li>`elisa`: ELISA results for mAbs, with values being one of `WA1+`, `BA1+WA1-`, or `negative`. `NA` for bulk sequences.</li> <li>`clone_type`: If a sequence was in an S-binding B cell clone (`TRUE` for `s_pos_clone`), its `clone_type` was based on the `elisa` value of the S-binding mAb in that clone -- either `WA1+` or `BA1+WA1-`; otherwise `NA`.</li> </ul>
Molecular Dynamics of Omicron-RBD and hACE2 performed with NAMD at 37 degrees Celsius
<p>Molecular Dynamics of Omicron-RBD and hACE2 performed with NAMD at 37 degrees Celsius. The PDB used is 7T9K for an MD of 9 nanoseconds. Amino acids side chains are in yellow which are the 11 amino acids specific to the Omicron variant mapped to the interface with hACE2 receptor. The mutations in Omicron make this variant to bind better to the hACE2 receptor and to evade most previous immunity including vaccines. Visualization in UCSF Chimera.</p>
Molecular Dynamics of hACE2 Receptor and SARS-CoV-2 Omicron-RBD (Receptor Binding Domain) in Electrostatics View
<p>Molecular Dynamics of hACE2 Receptor and SARS-CoV-2 Omicron-RBD (Receptor Binding Domain) in Electrostatics View.</p> <p>Molecular Dynamics performed with NAMD in Frontera supercomputer for 8 nanoseconds at 37 degrees Celsius. Electrostatics is visualized with ChimeraX (red is negative and blue is positive). By Victor Padilla-Sanchez, PhD; Texas Advanced Computing Center.</p>
Neutralizing immunity induced against the Omicron BA.2 variant in vaccinated and unvaccinated individuals infected by Omicron BA.1
<p>This repository contains the pertinent data files used in the manuscript, <em>Neutralizing immunity induced against the Omicron BA.2 variant in vaccinated and unvaccinated individuals infected by Omicron BA.1</em>.</p>
Supplementary data to Analyzing and Modeling the Spread of SARS-CoV-2 Omicron Lineages BA.1 and BA.2, France, September 2021–February 2022
<p>ZIP folder containing supplementary files to the article entitled <em>Analyzing and Modeling the Spread of SARS-CoV-2 Omicron Lineages BA.1 and BA.2, France, September 2021–February 2022</em> and published in Emerging Infectious Diseases with doi <a href="https://dx.doi.org/10.3201/eid2807.220033">10.3201/eid2807.220033</a></p> <ul> <li>Script_EID_1.R is the R script analysing the data_EID1.csv screening test data file (Figure 1 and Suppl Figure F1, and Tables 1 and 3).</li> <li>Script_EID_2.R is the R script analysing the data_EID2.csv screening test data file (Figures 2, 3, 5, and Suppl Figure F2, and Table 2).</li> <li>Script_EID_sequencing_raw.R is the R script analysing the data_EID_sequencing.csv sequencing data file (Figures 4, 5, and Suppl Figure F3).</li> </ul>
Supplementary data for article "Reduced B-cell antigenicity of Omicron lowers host serologic response"
<p>This repository contains five supplementary data files for the research article "<strong>Reduced B-cell antigenicity of Omicron lowers host serologic response</strong>". For more information, please refer to the article preprint https://doi.org/10.1101/2022.02.15.480546 and upcoming article at Cell Reports.</p> <p> </p> <ol> <li><strong>Table_hCoV229E.xlsx:</strong> list of hCoV229E RBD sequences, with associated isolate and collection date identifiers, and ScanNet antigenicity score for reproducing <strong>Figure 3A</strong>. Aligned sequences and templates are also provided.</li> <li><strong>table_artificial_variants.csv</strong>: List of artificial RBD sequences generated by an evolutionary-based sequence generative model for reproducing <strong>Figure 3B</strong>, <strong>Supplementary Figure S6H</strong>.</li> <li><strong>MSA_RBD.fasta:</strong> Multiple Sequence Alignment of RBD sequences and sample weights used for training the sequence generative model used in <strong>Figure 3B</strong>, <strong>Supplementary Figures S2C, S6</strong>.</li> <li><strong>table_antibody_hit_rate_RBD.csv</strong>: Empirical epitope distribution for the RBD, as determined from the Protein Data Bank and raw data for <strong>Supplementary Figure S1</strong>).</li> <li><strong>RBD_virtual_DMS.xlsx</strong>: virtual Deep Mutational Scan performed with ScanNet and the sequence generative model shown in <strong>Supplementary Figure S2</strong>.</li> </ol> <p> </p> <p> </p>
AMTraC-19 (v7.9) Dataset: Persistence of the Omicron variant of SARS-CoV-2 in Australia
<p>The paper describing scenarios which generated this dataset:</p> <p>S. L. Chang, Q. D. Nguyen, A. Martiniuk, V. Sintchenko, T. C. Sorrell, M. Prokopenko, Persistence of the Omicron variant of SARS-CoV-2 in Australia: The impact of fluctuating social distancing, <em>PLOS Global Public Health</em>, 3(4): e0001427, 2023.</p> <p>The AMTraC-19 source code (v7.9) is released on Zenodo: https://zenodo.org/record/7325675</p>
SARS-CoV-2 vaccine breakthrough infections by Omicron and Delta variants in healthcare workers
<p>An observational prospective cohort study was conducted in vaccinated employees with acute SARS-CoV-2 infection between October 2021 and February 2022. Serological and molecular testing was performed to determine SARS-CoV-2 viral load, lineage, antibody levels, and neutral-ising antibody titres. A total of 571 (9.7%) employees experienced SARS-CoV-2 breakthrough infections during the enrolment period, of which 81 were included. The majority (n=79, 97.5%) was symptomatic and most (n=75, 92.6%) showed Ct-values < 30 in RT-PCR assays. Twenty-four (30%) remained PCR-positive for > 15 days. Neutralizing antibody titres were strongest for the wildtype, intermediate for Delta and lowest for Omicron variants. Omicron infections occurred at higher anti-RBD-IgG serum levels (p= 0.00001) and showed a trend for higher viral loads (p=0.14, median Ct-difference 4.3, 95% CI [-2.5-10.5]). For both variants, viral loads were signifi-cantly higher in participants with lower anti-RBD-IgG serum levels (p=0.02). </p>
Supplementary Data for: "The principles of SARS-CoV-2 inter-variant competition are exemplified in the pre-Omicron era of the Colombian epidemic"
<p>Supplementary data files, including BEAST XMLs and logs from the study "The principles of SARS-CoV-2 inter-variant competition are exemplified in the pre-Omicron era of the Colombian epidemic".</p>
TRACE-Omicron Policy Counterfactuals Simulation Data
<p>This repository contains the simulation data for the Policy Counterfactuals in the study in "TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States" published in Advanced Theory and Simulations (doi:10.1002/adts.202300147)</p>
TRACE-Omicron: Epidemiological Counterfactuals; Tractable Strain
<p>This repository contains the simulation data corresponding to the Epidemiological Counterfactuals under the Tractable Strain baseline scenario in "TRACE-Omicron: Policy Counterfactuals to Inform Mitigation of COVID-19 Spread in the United States" published in Advanced Theory and Simulations (doi:10.1002/adts.202300147)</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.