cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh1229234.08fu
title: SH1229234.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh1229235.08fu
title: SH1229235.08FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/th028929
title: TH028929
title: Philometridae

description: Here we present the novel 'taxon hypothesis' (TH) concept to accommodate fungal 'species hypothesis' (SH) into existing classification frameworks for taxonomic communication. As supplied with Digital Object Identifiers (DOIs), THs are flexible in time and enable direct cross-communication of higher level taxa along with evolving classification schemes. Every TH includes given number of SHs and consequently fixed number of fungal rDNA ITS sequences. DNA sequences generated by High-throughput or Sanger sequencing studies and identified against UNITE SHs will be automatically assigned to THs as well.
DOI: 10.15156/bio/th028930
title: TH028930
title: Pratylenchidae

description: Here we present the novel 'taxon hypothesis' (TH) concept to accommodate fungal 'species hypothesis' (SH) into existing classification frameworks for taxonomic communication. As supplied with Digital Object Identifiers (DOIs), THs are flexible in time and enable direct cross-communication of higher level taxa along with evolving classification schemes. Every TH includes given number of SHs and consequently fixed number of fungal rDNA ITS sequences. DNA sequences generated by High-throughput or Sanger sequencing studies and identified against UNITE SHs will be automatically assigned to THs as well.
DOI: 10.35092/yhjc.10026887
title: Raw and Associated Data for “Dual hemispheric transcranial direct current stimulation (tDCS) over the primary motor cortex does not affect movement selection”

description: The dataset contains all the raw and analyzed data that are associated with manuscript titled "Dual hemispheric transcranial direct current stimulation (tDCS) over the primary motor cortex does not affect movement selection"<br><br>Supports PLoS ONE publication: Thirugnanasambandam N, Contreras-Castro FG, Hallett M (2019) Dual-hemispheric transcranial direct current stimulation (tDCS) over primary motor cortex does not affect movement selection. PLoS ONE 14(12): e0226103. https://doi.org/10.1371/journal.pone.0226103<br>
DOI: 10.35092/yhjc.10026887.v1
title: Raw and Associated Data for “Dual hemispheric transcranial direct current stimulation (tDCS) over the primary motor cortex does not affect movement selection”

description: The dataset contains all the raw and analyzed data that are associated with manuscript titled "Dual hemispheric transcranial direct current stimulation (tDCS) over the primary motor cortex does not affect movement selection"<br><br>Supports PLoS ONE publication: Thirugnanasambandam N, Contreras-Castro FG, Hallett M (2019) Dual-hemispheric transcranial direct current stimulation (tDCS) over primary motor cortex does not affect movement selection. PLoS ONE 14(12): e0226103. https://doi.org/10.1371/journal.pone.0226103<br>
DOI: 10.35092/yhjc.10248833
title: GFP-Rab11A intracellular movement in DMSO treated A549 cells.

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 GFP-Rab11A cells treated with DMSO (control). Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. The data from these cells correspond to Supplementary Movie 3 and analysis of these movies provided data presented in Figure 3 and Supplementary Figure 4.<br>Supplementary Movie 3: A549 GFP-Rab11A cells under control treatment (DMSO). <br>Figure 3: Motion Dynamics of Rab11A under the effect of cytoskeletal depolymerizing drugs.<br>Supplementary Figure 4: Impact of skeletal depolymerizing drugs on the transport of Rab11A.
DOI: 10.35092/yhjc.10248833.v1
title: GFP-Rab11A intracellular movement in DMSO treated A549 cells.

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 GFP-Rab11A cells treated with DMSO (control). Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. The data from these cells correspond to Supplementary Movie 3 and analysis of these movies provided data presented in Figure 3 and Supplementary Figure 4.<br>Supplementary Movie 3: A549 GFP-Rab11A cells under control treatment (DMSO). <br>Figure 3: Motion Dynamics of Rab11A under the effect of cytoskeletal depolymerizing drugs.<br>Supplementary Figure 4: Impact of skeletal depolymerizing drugs on the transport of Rab11A.
DOI: 10.35092/yhjc.10248833.v2
title: GFP-Rab11A intracellular movement in DMSO treated A549 cells.

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 GFP-Rab11A cells treated with DMSO (control). Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. The data from these cells correspond to Supplementary Movie 3 and analysis of these movies provided data presented in Figure 3 and Supplementary Figure 4.<br>Supplementary Movie 3: A549 GFP-Rab11A cells under control treatment (DMSO). <br>Figure 3: Motion Dynamics of Rab11A under the effect of cytoskeletal depolymerizing drugs.<br>Supplementary Figure 4: Impact of skeletal depolymerizing drugs on the transport of Rab11A.
DOI: 10.35092/yhjc.10250273
title: GFP-Rab11A intracellular movement in Nocodazole (16 µm) treated A549 cells

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 GFP-Rab11A cells treated with Nocodazole (16 µm). Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. These data correspond to Supplementary Movie 4 and analysis of these movies provided data presented in Figure 3 and Supplementary Figure 4. <br>Supplementary Movie 4: A549 GFP-Rab11A cells under nocodazole treatment. <br>Figure 3: Motion Dynamics of Rab11A under the effect of cytoskeletal depolymerizing drugs.<br>Supplementary Figure 4: Impact of skeletal depolymerizing drugs on the transport of Rab11A.
DOI: 10.35092/yhjc.10250273.v1
title: GFP-Rab11A intracellular movement in Nocodazole (16 µm) treated A549 cells

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 GFP-Rab11A cells treated with Nocodazole (16 µm). Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. These data correspond to Supplementary Movie 4 and analysis of these movies provided data presented in Figure 3 and Supplementary Figure 4. <br>Supplementary Movie 4: A549 GFP-Rab11A cells under nocodazole treatment. <br>Figure 3: Motion Dynamics of Rab11A under the effect of cytoskeletal depolymerizing drugs.<br>Supplementary Figure 4: Impact of skeletal depolymerizing drugs on the transport of Rab11A.
DOI: 10.35092/yhjc.10250342
title: GFP-Rab11A intracellular movement in Latrunculin A (1 µm) treated A549 cells

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 GFP-Rab11A cells treated with Latrunculin A (1 µm). Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. These data correspond to Supplementary Movie 5 and analysis of these movies provided data presented in Figure 3 and Supplementary Figure 4.<br>Supplementary Movie 5: A549 GFP-Rab11A cells under latrunculin A treatment. <br>Figure 3: Motion Dynamics of Rab11A under the effect of cytoskeletal depolymerizing drugs.<br>Supplementary Figure 4: Impact of skeletal depolymerizing drugs on the transport of Rab11A.
DOI: 10.35092/yhjc.10250438
title: H1N1 pdm PA::GFP intracellular movement in DMSO treated A549 cells during infection

description: TIFF series of diSPIM datasets, fused and deconvolved, from A549 cells infected with H1N1 pdm PA::GFP and treated with DMSO. Each TIFF file is a full cell volume of 50 planes, with isotropic resolution of 330nm, each .zip file is an independent replicate with at least 1 or 2 cells analyzed for 3D tracking of cytoplasmic foci with 500 time stamps. These data correspond to Supplementary Movie 6 and analysis of these movies provided data presented in Figure 4 and Supplementary Figure 8.<br>Supplementary Movie 6: A549 cells infected with H1N1 pandemic influenza expressing GFP-tagged PA protein (control treatment). <br>Figure 4: Effect of cytoskeleton depolymerization on motion dynamics of influenza vRNP in A549 cells. <br>Supplementary Figure 8: Impact of cytoskeletal depolymerizing drugs on the transport of PA::GFP.
DOI: 10.35092/yhjc.9177143
title: X-ray scattering curves (SAXS/WAXS) used for the analysis described in ‘Temperature-Jump Solution X-ray Scattering Reveals Distinct Motions in a Dynamic Enzyme’

description: Data provided here are the integrated X-ray scattering curves (SAXS/WAXS) used for the analysis described in:<br>Thompson, et al. (2019) Nature Chemistry."Temperature-Jump Solution X-ray Scattering Reveals Distinct Motions in a Dynamic Enzyme"<br><br>The data are provided as azimuthally averaged I(q) vs. q scattering curves. Prior to averaging the pixel measurements, we applied polarization, geometry, and detector non-uniformity corrections to the 2D X-ray images. <br>Columns in the .dat file format correspond to q, intensity, and the standard deviation of the intensity.<br><br>Data are organized by CypA variant, by whether the data are time-resolved or static, and by final temperature (after T-jump) for time-resolved experiments. Sample and experiment metadata is provided in each subdirectory.<br>
DOI: 10.35092/yhjc.9202247
title: Decomposed matrices used for the analysis described in 'Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology'

description: The dataset deposited here contains decomposed matrices of GWAS summary statistics across 2,138 phenotypes described in the following publication:<b><br></b>Y. Tanigawa*, J. Li*, et al., Components of genetic associations across 2,138 phenotypes in the UK Biobankhighlight adipocyte biology. Nature Communications (2019). doi:10.1038/s41467-019-11953-9.<b><br></b>The data are provided as three Python Numpy data (npz) files, each of which corresponds to the three datasets used in computational analysis described in our manuscript.<b><br></b>- "all" dataset: dev_allNonMHC_z_center_p0001_100PCs_20180129.npz- "Coding only" dataset: dev_codingNonMHC_z_center_p0001_100PCs_20180129.npz- "PTVs only" dataset: dev_PTVsNonMHC_z_center_p0001_100PCs_20180129.npz<b><br></b>Those files can be loaded with Python numpy package and were used in our analysis scripts and notebook (https://github.com/rivas-lab/public-resources/tree/master/uk_biobank/DeGAs).<b><br></b>Please read our publication for more information regarding this dataset.<b><br></b>Abstract<br>Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we applied truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identified key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits, and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.<br>
DOI: 10.35092/yhjc.9202247.v1
title: Decomposed matrices used for the analysis described in 'Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology'

description: The dataset deposited here contains decomposed matrices of GWAS summary statistics across 2,138 phenotypes described in the following publication:<b><br></b>Y. Tanigawa*, J. Li*, et al., Components of genetic associations across 2,138 phenotypes in the UK Biobankhighlight adipocyte biology. Nature Communications (2019). doi:10.1038/s41467-019-11953-9.<b><br></b>The data are provided as three Python Numpy data (npz) files, each of which corresponds to the three datasets used in computational analysis described in our manuscript.<b><br></b>- "all" dataset: dev_allNonMHC_z_center_p0001_100PCs_20180129.npz- "Coding only" dataset: dev_codingNonMHC_z_center_p0001_100PCs_20180129.npz- "PTVs only" dataset: dev_PTVsNonMHC_z_center_p0001_100PCs_20180129.npz<b><br></b>Those files can be loaded with Python numpy package and were used in our analysis scripts and notebook (https://github.com/rivas-lab/public-resources/tree/master/uk_biobank/DeGAs).<b><br></b>Please read our publication for more information regarding this dataset.<b><br></b>Abstract<br>Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we applied truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identified key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits, and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.<br>
DOI: 10.35092/yhjc.9693302
title: FCS files to support 4-84 TG6 F3 females tetramer panel (Figs 2, 4, 5) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: These are FCS files that correspond to data in figures 2, 4, and 5. FCS files to support 4-84 TG6 F3 females tetramer panel (Figs 2, 4, 5) <br>Figure 2: F0 exposure to TCDD has transgenerational effects on the CD8+ T response to IAV in the lung of female offspring. <br>Figure 4: In the MLN, F0 AHR activation alters the CD8+ T cell response of female and male F1 but not F3 generation offspring. <br>Figure 5: Transgenerational effects on the CD8+ T cell response to IAV in the lung are transmitted through both parental lineages. <br>
DOI: 10.35092/yhjc.9693380
title: FCS files to support 4-46 F1 males tetramer panel (Figs 3 & 4) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: These are FCS files that correspond to data in Figures 3 and 4. FCS files to support 4-46 F1 males tetramer panel (Figs 3 & 4)<br>Figure 3: F0 exposure to TCDD has developmental, but not transgenerational effects on the CD8+ T response to IAV in the lung of male TCDD lineage offspring. <br>Figure 4: In the MLN, F0 AHR activation alters the CD8+ T cell response of female and male F1 but not F3 generation offspring. <br>
DOI: 10.35092/yhjc.9693380.v1
title: FCS files to support 4-46 F1 males tetramer panel (Figs 3 & 4) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: These are FCS files that correspond to data in Figures 3 and 4. FCS files to support 4-46 F1 males tetramer panel (Figs 3 & 4)<br>Figure 3: F0 exposure to TCDD has developmental, but not transgenerational effects on the CD8+ T response to IAV in the lung of male TCDD lineage offspring. <br>Figure 4: In the MLN, F0 AHR activation alters the CD8+ T cell response of female and male F1 but not F3 generation offspring. <br>
DOI: 10.35092/yhjc.9693491
title: FCS files to support 4-99 F1 tetramer panel (Figs 2 & 3) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: FCS files to support 4-99 F1 tetramer panel (Figs 2 & 3)<br>Figure 2: F0 exposure to TCDD has transgenerational effects on the CD8+ T response to IAV in the lung of female offspring. <br>Figure 3: F0 exposure to TCDD has developmental, but not transgenerational effects on the CD8+ T response to IAV in the lung of male TCDD lineage offspring. <br>
DOI: 10.35092/yhjc.9693491.v1
title: FCS files to support 4-99 F1 tetramer panel (Figs 2 & 3) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: FCS files to support 4-99 F1 tetramer panel (Figs 2 & 3)<br>Figure 2: F0 exposure to TCDD has transgenerational effects on the CD8+ T response to IAV in the lung of female offspring. <br>Figure 3: F0 exposure to TCDD has developmental, but not transgenerational effects on the CD8+ T response to IAV in the lung of male TCDD lineage offspring. <br>
DOI: 10.35092/yhjc.9693512
title: Figure Keys for "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: Each Excel file corresponds to a different figure in the paper. <br><br>"TG paper Figure Key" shows which FCS folder goes with each panel for every figure.<br><br>The individually numbered sample key Excel documents correspond to a figure in the paper and for each experiment ID, the treatment group and/or genotype associated with each sample is indicated in the table.<br><br>The information in these files is necessary for interpreting any analysis performed <br><br>
DOI: 10.35092/yhjc.9693512.v1
title: Figure Keys for "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: Each Excel file corresponds to a different figure in the paper. <br><br>"TG paper Figure Key" shows which FCS folder goes with each panel for every figure.<br><br>The individually numbered sample key Excel documents correspond to a figure in the paper and for each experiment ID, the treatment group and/or genotype associated with each sample is indicated in the table.<br><br>The information in these files is necessary for interpreting any analysis performed <br><br>
DOI: 10.35092/yhjc.9695951
title: FCS files to support LB 8-127 males (Figure 6) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: These FCS files correspond to the male data shown in Figure 6.<br>Figure 6: Lack of AHR in hematopoietic cells has differential effects on CD8+ T cell expansion in female and male offspring during IAV infection. <br>At maturity, 9-11 male or female developmentally exposed Vav1creAhrfx/fx and Ahrfx/fx offspring were infected with IAV. MLN cells were harvested and stained as described in the Methods section.
DOI: 10.35092/yhjc.9695951.v1
title: FCS files to support LB 8-127 males (Figure 6) in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: These FCS files correspond to the male data shown in Figure 6.<br>Figure 6: Lack of AHR in hematopoietic cells has differential effects on CD8+ T cell expansion in female and male offspring during IAV infection. <br>At maturity, 9-11 male or female developmentally exposed Vav1creAhrfx/fx and Ahrfx/fx offspring were infected with IAV. MLN cells were harvested and stained as described in the Methods section.
DOI: 10.35092/yhjc.9696257
title: FCS files to support F1 females IFNg panel Figs 4 in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: This data set corresponds to F1 female data shown in Figure 4 <br>Figure 4: In the MLN, F0 AHR activation alters the CD8+ T cell response of female and male F1 but not F3 generation offspring. F1 and F3 generation offspring were generated as shown in Fig 1A. 7-9 adult F1 and F3 generation offspring from each treatment group were infected with IAV and MLN cells were harvested on day 8 (males) or 9 (females) post infection. <br>This is FCS data for (C) The number of IFNg+CD8+ T cells in female F1 (left) and F3 (right) offspring.<br>
DOI: 10.35092/yhjc.9696257.v1
title: FCS files to support F1 females IFNg panel Figs 4 in "The ancestral environment shapes antiviral CD8+ T cell responses across generations"

description: This data set corresponds to F1 female data shown in Figure 4 <br>Figure 4: In the MLN, F0 AHR activation alters the CD8+ T cell response of female and male F1 but not F3 generation offspring. F1 and F3 generation offspring were generated as shown in Fig 1A. 7-9 adult F1 and F3 generation offspring from each treatment group were infected with IAV and MLN cells were harvested on day 8 (males) or 9 (females) post infection. <br>This is FCS data for (C) The number of IFNg+CD8+ T cells in female F1 (left) and F3 (right) offspring.<br>