cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.3886/icpsr09288.v1
title: Three-Generation National Survey of Black American Families, 1979-1981
title: Version 1

description: This dataset was created by merging information collected from three questionnaires that form part of the NATIONAL SURVEY OF BLACK AMERICANS, 1979-1980 (ICPSR 8512) (NSBA). The three questionnaires were (1) the original cross-sectional survey questionnaire, (2) the reinterview questionnaire, and (3) the family members questionnaire. All three were administered from 1979-1981. The unit of analysis in this dataset is three generations of a family, or a "triad." Each unit or record has identical variables for the three individuals making up a triad (i.e., a grandparent, parent, and child). There are 510 triads in this dataset. The study explores feelings and attitudes across the three generations regarding neighborhood-community integration, services, crime and community contact, the role of religion and the church, physical and mental health, and self-esteem. Employment, the effects of chronic unemployment, the effects of race on the job, and interaction with family and friends are also examined. In addition, the survey provides information on racial attitudes, race identity, group stereotypes, and race ideology. Demographic variables include age, education, income, occupation, and political behavior and affiliation.
description: Datasets: 
 
 DS1: Dataset
description: Black United States citizens 18 years of age or older.
description: National multistage probability sample. The sample is self-weighting. Every Black American household in the continental United States had an equal probability of being selected.
DOI: 10.3886/icpsr09288.v2
title: Three-Generation National Survey of Black American Families, 1979-1981
title: Version 2

description: This dataset was created by merging information collected from three questionnaires that form part of the NATIONAL SURVEY OF BLACK AMERICANS, 1979-1980 (ICPSR 8512) (NSBA). The three questionnaires were (1) the original cross-sectional survey questionnaire, (2) the reinterview questionnaire, and (3) the family members questionnaire. All three were administered from 1979-1981. The unit of analysis in this dataset is three generations of a family, or a "triad." Each unit or record has identical variables for the three individuals making up a triad (i.e., a grandparent, parent, and child). There are 510 triads in this dataset. The study explores feelings and attitudes across the three generations regarding neighborhood-community integration, services, crime and community contact, the role of religion and the church, physical and mental health, and self-esteem. Employment, the effects of chronic unemployment, the effects of race on the job, and interaction with family and friends are also examined. In addition, the survey provides information on racial attitudes, race identity, group stereotypes, and race ideology. Demographic variables include age, education, income, occupation, and political behavior and affiliation.
description: Response Rates: The number of cross-sectional respondents who were eligible for the three generation study was 1,122. Of these, 865 agreed to participate. There was further attrition due to non-response of some family members, therefore, information for all three generations was collected on 510 families (complete triads). If only one family member agreed to be interviewed, they form part of the family dyads dataset which also contains the complete triads as part of the dataset.
description: National multistage probability sample. The sample is self-weighting. Every Black American household in the continental United States had an equal probability of being selected.
description: Datasets: DS1: Three-Generation National Survey of Black American Families, 1979-1981
description: Black United States citizens 18 years of age or older.
DOI: 10.15454/brbk8x/dxdo5t
title: FOS_HYD_LCIA.tab

description: Life Cycle Impact Assessment of FOS produced by hydrolysis
DOI: 10.15454/brbk8x/frlypg
title: FOS_SYNT_LCIA.tab

description: Life Cycle Impact Assessment of FOS produced by synthesis
DOI: 10.15454/brbk8x/snbddn
title: FOS_HYD_LCI.tab

description: Life Cycle Inventory of FOS produced by hydrolysis
DOI: 10.15454/brbk8x/6djdl8
title: GOS_SYNT_LCI.tab

description: Life Cycle Inventory of GOS produced by synthesis
DOI: 10.15454/brbk8x/etcdwf
title: FOS_SYNT_LCI.tab

description: Life Cycle Inventory of FOS produced by synthesis
DOI: 10.15454/brbk8x/vtsymh
title: GOS_HYD_LCIA.tab

description: Life Cycle Impact Assessment of GOS produced by hydrolysis
DOI: 10.15454/brbk8x/xyaljh
title: GOS_SYNT_LCIA.tab

description: Life Cycle Impact Assessment of GOS produced by synthesis
DOI: 10.15454/brbk8x/xs8sbm
title: GOS_HYD_LCI.tab

description: Life Cycle Inventory of GOS produced by hydrolysis
DOI: 10.57745/zwwkf5
title: Equipment_data.tab

description: Data related to the equipment used, including power of the equipment, composition of the equipment (materials used and mass of each material)
DOI: 10.57745/buptg8
title: Supp.mat2.xlsx

description: :unav
DOI: 10.57745/eiposc
title: Data_cameraria.tab

description: :unav
DOI: 10.57745/ijnee9
title: Supp.mat1.xlsx

description: :unav
DOI: 10.57745/www6pv
title: RM_Cameraria_Bordeaux.Rmd

description: RMarkdown of the code used in the paper
DOI: 10.57745/mp6aot
title: Supp.mat3.xlsx

description: :unav
DOI: 10.57745/67aley
title: Culturability of L. salivarius CECT5713.txt

description: Culturability of L. salivarius CECT5713 protected cell concentrates at different steps of the production process: before and after freezing, after freeze-drying and 4 weeks of freeze-dried storage at 37°C.
DOI: 10.57745/1gwbde
title: Physical properties of L. salivarius CECT5713.txt

description: Glass transition of the liquid bacterial concentrates (Tg'), glass transition (Tg) and water activity (aw) of freeze-dried powders, after freeze-drying and after 1 and 4 weeks of freeze-dried storage at 37°C.
DOI: 10.57745/bmlpng
title: Membrane fatty acid composition of L.salivarius CECT5713.txt

description: Membrane fatty acid composition of L. salivarius CECT5713 protected cell concentrates after freeze-drying and 4 weeks of storage at 37°C
DOI: 10.57745/mjqybg
title: FTIR-microspectroscopy of L.salivarius CECT5713.txt

description: FTIR-microspectroscopy of L.salivarius CECT5713 cells in aqueous environment (4000-675cm-1) after freezing, after freeze-drying and 4 weeks of freeze-dried storage at 37°C.
DOI: 10.57745/jefti6
title: sheep_44321variants_47individuals.map

description: :unav
DOI: 10.57745/yab5ac
title: sheep_44321variants_47individuals.ped

description: :unav
DOI: 10.15454/ipmiox/7mj46y
title: Intensity_asexual_multiplication_rawdata.tab

description: We assessed the intensity of asexual multiplication by scoring disease severity on wheat leaves, expressed as the percentage of the leaf area covered by pycnidia
DOI: 10.15454/ipmiox/mpvciv
title: Intensity_sexual_reproduction_rawdata.tab

description: We assessed the intensity of sexual reproduction by evaluating ascospore discharge events in wheat residues samples
DOI: 10.57745/3ph3lj
title: Genotyping dataset.tab

description: Genetic profiles obtained with 12 SSR markers for parental and offspring strains
DOI: 10.6084/m9.figshare.21201472.v1
title: Hammond_et-al_2019_Microglia_SCE_Objects

description: Single cell SCE objects for data in: Hammond TR, Dufort C, Dissing-Olesen L, Giera S, Young A, Wysoker A, Walker AJ, Gergits F, Segel M, Nemesh J, Marsh SE, Saunders A, Macosko E, Ginhoux F, Chen J, Franklin RJM, Piao X, McCarroll SA, Stevens B (2019). Single-Cell RNA Sequencing of Microglia throughout the Mouse Lifespan and in the Injured Brain Reveals Complex Cell-State Changes. <em><strong>Immunity</strong></em><strong>,</strong> 50(1):253–271.e6. doi.org/10.1016/j.immuni.2018.11.004. PMID: 30471926.
DOI: 10.57745/2n2itx
title: Detail des donnees.pdf

description: :unav
DOI: 10.5281/zenodo.4434749
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 11,000+ patients, divided into 38 cancer types. This includes copy number variation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information.
DOI: 10.5281/zenodo.4460242
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 11,000+ patients, divided into 38 cancer types. This includes copy number variation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information. <br> Version notes: 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization to RPPA data.
description: Removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization to RPPA data.
DOI: 10.5281/zenodo.4490232
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 11,000+ patients, divided into 38 cancer types. This includes copy number variation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information. <br> Version notes: 2021-02-01: added mutation annotation scores. removed GRSN from RPPA pipeline. 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization (GRSN) to RPPA data.
description: Added mutation annotation scores. removed GRSN from RPPA pipeline.
DOI: 10.5281/zenodo.4568944
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 11,000+ patients, divided into 38 cancer types. This includes copy number variation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information. <br> Version notes: 2021-02-28: improved HDF file format. We provide one big matrix of data, rather than one matrix per cancer type. Cancer type is indicated by a vector (key="cancer_types"). Updated the Omic and Clinical HDFs accordingly. 2021-02-01: added mutation annotation scores. removed GRSN from RPPA pipeline. 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization (GRSN) to RPPA data.
description: Improved HDF file format. We provide one big matrix of data, rather than one matrix per cancer type. Cancer type is indicated by a vector (key="cancer_types"). Updated the Omic and Clinical HDFs accordingly.
DOI: 10.5281/zenodo.4434748
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 10,000+ patients. This includes copy number variation, somatic mutation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information about the data and its layout in the HDF5 files. <br> Version notes: 2022-08-09: Fixed some bugs in string formatting. (Pipeline updated on this date; data uploaded on 2022-09-26 due to Zenodo technical issues.) 2021-12-06: **Significant changes**. `tcga_omic.hdf` is organized very differently. It also includes more kinds of data (a) somatic mutation data and (b) full TCGA barcodes for each patient and omic type (useful for extracting batch information). 2021-03-17: improved the naming convention for RPPA data features: {GENE}_{ANTIBODY}_rppa 2021-02-28: improved HDF file format. We provide one big matrix of data, rather than one matrix per cancer type. Cancer type is indicated by a vector (key="cancer_types"). Updated the Omic and Clinical HDFs accordingly. 2021-02-01: added mutation annotation scores. removed GRSN from RPPA pipeline. 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization (GRSN) to RPPA data.
description: Fixed some bugs in string formatting.
DOI: 10.5281/zenodo.4614389
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 11,000+ patients, divided into 38 cancer types. This includes copy number variation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information. <br> Version notes: 2021-03-17: improved the naming convention for RPPA data features: {GENE}_{ANTIBODY}_rppa 2021-02-28: improved HDF file format. We provide one big matrix of data, rather than one matrix per cancer type. Cancer type is indicated by a vector (key="cancer_types"). Updated the Omic and Clinical HDFs accordingly. 2021-02-01: added mutation annotation scores. removed GRSN from RPPA pipeline. 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization (GRSN) to RPPA data.
description: Improved the naming convention for RPPA data features: {GENE}_{ANTIBODY}_rppa
DOI: 10.5281/zenodo.5762416
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 10,000+ patients. This includes copy number variation, somatic mutation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information. <br> Version notes: 2021-12-06: Significant changes. `tcga_omic.hdf` is organized very differently. It also includes more kinds of data (a) somatic mutation data and (b) full TCGA barcodes for each patient and omic type (useful for extracting batch information). 2021-03-17: improved the naming convention for RPPA data features: {GENE}_{ANTIBODY}_rppa 2021-02-28: improved HDF file format. We provide one big matrix of data, rather than one matrix per cancer type. Cancer type is indicated by a vector (key="cancer_types"). Updated the Omic and Clinical HDFs accordingly. 2021-02-01: added mutation annotation scores. removed GRSN from RPPA pipeline. 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization (GRSN) to RPPA data.
description: Significant changes. `tcga_omic.hdf` is organized very differently. It also includes more kinds of data (a) somatic mutation data and (b) full TCGA barcodes for each patient and omic type (useful for extracting batch information).
DOI: 10.5281/zenodo.6977490
title: TCGA HDF file pipeline

description: HDF files containing data from The Cancer Genome Atlas (TCGA).<br> <br> https://www.cancer.gov/about-nci/organization/ccg/research/structural-genomics/tcga Please see the Broad Institute's TCGA data usage policy: https://broadinstitute.atlassian.net/wiki/spaces/GDAC/pages/844333156/Data+Usage+Policy The HDF files were generated by the code in this repository: https://github.com/dpmerrell/tcga-pipeline * tcga_omic.tar.gz contains multi-omic data for 10,000+ patients. This includes copy number variation, somatic mutation, methylation, gene expression, and RPPA data. * tcga_clinical.tar.gz contains clinical annotations for those same patients. E.g., age, sex, survival, smoking. See https://github.com/dpmerrell/tcga-pipeline/blob/main/README.md for more information about the data and its layout in the HDF5 files. <br> Version notes: 2022-08-09: Fixed some bugs in string formatting. (Pipeline updated on this date; data uploaded on 2022-09-26 due to Zenodo technical issues.) 2021-12-06: **Significant changes**. `tcga_omic.hdf` is organized very differently. It also includes more kinds of data (a) somatic mutation data and (b) full TCGA barcodes for each patient and omic type (useful for extracting batch information). 2021-03-17: improved the naming convention for RPPA data features: {GENE}_{ANTIBODY}_rppa 2021-02-28: improved HDF file format. We provide one big matrix of data, rather than one matrix per cancer type. Cancer type is indicated by a vector (key="cancer_types"). Updated the Omic and Clinical HDFs accordingly. 2021-02-01: added mutation annotation scores. removed GRSN from RPPA pipeline. 2021-01-24: removed redundant/combination datasets (COADREAD, STES, GBMLGG, KIPAN). Applied Global Rank-Invariant Set normalization (GRSN) to RPPA data.
description: Fixed some bugs in string formatting.
DOI: 10.57745/kfufpc
title: FigS1.pdf

description: The estimated log probability of our data Pr(X|K) (equation 12 in Pritchard et al. 2000) and its standard deviation for each value of K between 1 to 20 estimated from STRUCTURE. Values of ∆K (Evanno et al., 2005) plotted against values of K estimated from STRUCTURE.
DOI: 10.57745/risvvv
title: FigS2.pdf

description: Proportion of membership of each “population” in each of the 15 clusters calculated in STRUCTURE (for the run with the smallest lnPr(X|K) at K=15). Each stacked plot represents a “population” whose label is indicated at the bottom of the plot together with its sample size. “Populations” here refers as the baseline samples at the end of the first filtering step, i.e. close relatives being discarded and migrants still included. Information relative to the three reporting groups (RG1-3) thereafter used for baseline performance tests and sea trout assignment are also shown in the middle of each plot.
DOI: 10.57745/bnkvje
title: FigS3.pdf

description: Neighbour joining genetic tree based on the net nucleotide distance between the 15 genetic clusters found by STRUCTURE (same run as Figure S2).
DOI: 10.57745/m4unlf
title: FigS5.pdf

description: Genetic assignment of sea trout (N=546) caught in Gaves, Nive and Nivelle. Only those exhibiting an assignment probability above 80% were here considered (N=546). The upper part of each figure illustrated the genetic cluster composition (STRUCTURE outputs) of sea trout considered as local and the lower part those considered as immigrant (local/immigrant status from ONCOR outputs).
DOI: 10.57745/ofydgk
title: FigS4.pdf

description: Bayesian STRUCTURE results showing the distribution of the 15 genetic clusters detected among the close relative filtered baseline (not considering sampling location as a prior). Each individual is represented by a vertical bar divided into 15 coloured segments whose height is proportional to the estimated membership coefficients of the individual in each cluster, the so-called Q parameter output by STRUCTURE. The plot subdivided each predefined “populations” into two groups according to the individual status attributed by ONCOR (local origin on the left side / immigrant origin on the right side, and for the latter, the population of origin inferred by ONCOR). (A) Rivers located north of the focal area. (B) Main tributaries of the River Adour. (C) Remaining wild populations. (D) Domestic strains.
DOI: 10.57745/qbqrhi
title: Dataset_SeaTrout_619ind.tab

description: SSR genetic datamatrix of sea trout
DOI: 10.57745/v8abmk
title: Dataset_Baseline_1017ind.tab

description: "SSR genetic datamatrix of the baseline used to assign sea trout to their source populations. Label population codes : 1 (Scorff), 2 (Loire, Sèvre Niortaise and Charente), 3 (Dordogne and Garonne), 4 (Upper Adour - Adour), 5 (Gave de Pau - Adour), 6 (Gave d'Oloron - Adour), 7 (Lower Adour - Adour), 8 (Nive - Adour), 9 (Nivelle), 10 (Spanish Coastal Streams), 11-17 (hatcheries), 18 (Upper Ebro - Mediterranean lineage), 19 (Atlantic salmon)."
DOI: 10.57745/9jxsln
title: Supplementary Information no1.pdf

description: Individual genetic assignment procedure of sea trout caught in Nivelle and Adour rivers.
DOI: 10.57745/apgjrn
title: DATA1_glm.tab

description: Sea trout individual genetic assignment and their deduced behaviour (Adour and Nivelle)
DOI: 10.57745/boqzzq
title: Supplementary Information no2.pdf

description: Baseline tests. (a) Estimated mean stock composition of baseline data sets using self-assignment of the baseline. Samples were assigned to river or, when appropriate, to reporting group of origin using the "leave-one-out" procedure in ONCOR. Only complete genotypes were assigned (N=956 out of 1017). (b) Estimated mean stock composition of resident trout of known origin collected in the wild (N=97). Samples were assigned to river or, when appropriate, to reporting group of origin using ONCOR. (c) Estimated mean stock composition of 100 data sets of 200 simulated genotypes for each population. Genotypes were simulated and assigned to river or, when appropriate, to reporting group of origin using ONCOR
DOI: 10.57745/ipu5zi
title: Supplementary Information no3.pdf

description: Statistical modelling (glm) of straying in sea trout using R.
DOI: 10.57745/qosflq
title: DATA2_glm.tab

description: Sea trout behaviour (Tamar), counts deduced from proportion given in Appendices of the paper from King et al (2016)