29 datasets found
  1. f

    Additional file 2: Table S1. of ChiLin: a comprehensive ChIP-seq and...

    • springernature.figshare.com
    xlsx
    Updated Jun 1, 2023
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    Qian Qin; Shenglin Mei; Qiu Wu; Hanfei Sun; Lewyn Li; Len Taing; Sujun Chen; Fugen Li; Tao Liu; Chongzhi Zang; Han Xu; Yiwen Chen; Clifford Meyer; Yong Zhang; Myles Brown; Henry Long; X. Liu (2023). Additional file 2: Table S1. of ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline [Dataset]. http://doi.org/10.6084/m9.figshare.c.3636644_D9.v1
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    xlsxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    figshare
    Authors
    Qian Qin; Shenglin Mei; Qiu Wu; Hanfei Sun; Lewyn Li; Len Taing; Sujun Chen; Fugen Li; Tao Liu; Chongzhi Zang; Han Xu; Yiwen Chen; Clifford Meyer; Yong Zhang; Myles Brown; Henry Long; X. Liu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Sheet1 ToolsComparison: ChIP-seq pipeline software comparison. Sheet2 Examples of ChiLin report. A summary of example data annotation of transcription factor, chromatin regulatory factor and histone modification ChIP-seq data. Sheet3 Protein classification standard for the 8 categories. Sheet4 Protein classification results. Sheet5 BWA QC Database. ChiLin samples and datasets quality metrics across three layers. A clean up table of cistrome samples and datasets quality metrics for ChiLin users’ reference. The QC results is based on the reference of hg38 and mm10 assembly. (XLSX 10363 kb)

  2. Data from: Top300 genes for HIF1A ranked by the average score of MACS2

    • figshare.com
    txt
    Updated Oct 9, 2019
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    Hidemasa Bono (2019). Top300 genes for HIF1A ranked by the average score of MACS2 [Dataset]. http://doi.org/10.6084/m9.figshare.9958235.v1
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    txtAvailable download formats
    Dataset updated
    Oct 9, 2019
    Dataset provided by
    figshare
    Authors
    Hidemasa Bono
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Publicly available ChIP-seq experiments were processed by MACS2 program and the average values of those scores were calculated for all genes.Original calculated data were from ChIP-Atlas database.Top300 genes for HIF1A ChIP-seq experiments are listed for the comparison.

  3. Top300 genes for EPAS1 ranked by the average score of MACS2

    • figshare.com
    txt
    Updated Oct 9, 2019
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    Hidemasa Bono (2019). Top300 genes for EPAS1 ranked by the average score of MACS2 [Dataset]. http://doi.org/10.6084/m9.figshare.9958250.v1
    Explore at:
    txtAvailable download formats
    Dataset updated
    Oct 9, 2019
    Dataset provided by
    figshare
    Authors
    Hidemasa Bono
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Publicly available ChIP-seq experiments were processed by MACS2 program and the average values of those scores were calculated for all genes.Original calculated data were from ChIP-Atlas database.Top300 genes for EPAS1(HIF2A) ChIP-seq experiments are listed for the comparison.

  4. Human list of RNA-seq data counts and average of ChIP-seq MACS2 value (HIF1A...

    • figshare.com
    txt
    Updated Oct 9, 2019
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    Hidemasa Bono (2019). Human list of RNA-seq data counts and average of ChIP-seq MACS2 value (HIF1A and EPAS1) from meta-analysis of the public NGS database [Dataset]. http://doi.org/10.6084/m9.figshare.9958181.v2
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    txtAvailable download formats
    Dataset updated
    Oct 9, 2019
    Dataset provided by
    Figsharehttp://figshare.com/
    figshare
    Authors
    Hidemasa Bono
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The number of experiments in which gene was up/down regulated in RNA-seq data and the average of ChIP-seq MACS2 values of HIF1A and EPAS1(HIF2A) in ChIP-Atlas database.Both were calculated from public NGS database (SRA).For up/donw regulated gene selection, 2 fold threshold was adopted.

  5. f

    Additional file 6 of xcore: an R package for inference of gene expression...

    • springernature.figshare.com
    xlsx
    Updated Aug 13, 2024
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    Maciej Migdał; Takahiro Arakawa; Satoshi Takizawa; Masaaki Furuno; Harukazu Suzuki; Erik Arner; Cecilia Lanny Winata; Bogumił Kaczkowski (2024). Additional file 6 of xcore: an R package for inference of gene expression regulators [Dataset]. http://doi.org/10.6084/m9.figshare.26560718.v1
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    xlsxAvailable download formats
    Dataset updated
    Aug 13, 2024
    Dataset provided by
    figshare
    Authors
    Maciej Migdał; Takahiro Arakawa; Satoshi Takizawa; Masaaki Furuno; Harukazu Suzuki; Erik Arner; Cecilia Lanny Winata; Bogumił Kaczkowski
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Additional file 6: Table S3. Table provides the activities of ReMap2020 and ChIP-Atlas molecular signatures estimated using TGFβ induced EMT in A-549 cell line dataset (GSE17708).

  6. Data from: ReMap 2022: a database of Human, Mouse, Drosophila and...

    • zenodo.org
    • data.niaid.nih.gov
    application/gzip, bin
    Updated Jan 19, 2024
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    Benoit Ballester; Benoit Ballester (2024). ReMap 2022: a database of Human, Mouse, Drosophila and Arabidopsis regulatory regions from an integrative analysis of DNA-binding sequencing experiments [Dataset]. http://doi.org/10.5281/zenodo.10527088
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    application/gzip, binAvailable download formats
    Dataset updated
    Jan 19, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Benoit Ballester; Benoit Ballester
    License

    Attribution-NonCommercial 4.0 (CC BY-NC 4.0)https://creativecommons.org/licenses/by-nc/4.0/
    License information was derived automatically

    Description

    ReMap is a large scale integrative analysis of DNA-binding experiments for Homo sapiens, Mus musculus, Drosophila melanogaster and Arabidopsis thaliana transcriptional regulators. The catalogues are the results of the manual curation of ChIP-seq, ChIP-exo, DAP-seq from public sources (GEO, ENCODE, ENA).

    ReMap (https://remap.univ-amu.fr) aims to provide manually curated, high-quality catalogs of regulatory regions resulting from a large-scale integrative anlysis of DNA-binding experiments in Human, Mouse, Fly and Arabidopsis thaliana for hundreds of transcription factors and regulators. In this 2022 update, we have uniformly processed >11 000 DNA-binding sequencing datasets from public sources across four species. The updated Human regulatory atlas includes 8103 datasets covering a total of 1210 transcriptional regulators (TRs) with a catalog of 182 million (M) peaks, while the updated Arabidopsis atlas reaches 4.8M peaks, 423 TRs across 694 datasets. Also, this ReMap release is enriched by two new regulatory catalogs for Mus musculus and Drosophila melanogaster. First, the Mouse regulatory catalog consists of 123M peaks across 648 TRs as a result of the integration and validation of 5503 ChIP-seq datasets. Second, the Drosophila melanogaster catalog contains 16.6M peaks across 550 TRs from the integration of 1205 datasets. The four regulatory catalogs are browsable through track hubs at UCSC, Ensembl and NCBI genome browsers. Finally, ReMap 2022 comes with a new Cis Regulatory Module identification method, improved quality controls, faster search results, and better user experience with an interactive tour and video tutorials on browsing and filtering ReMap catalogs.

    We thank our users for past and future feedback to make ReMap useful for the community. The ReMap team welcomes your feedback on the catalogs, use of the website and use of the downloadable files. Please contact benoit.ballester@inserm.fr for development requests.

    Reference:

    ReMap 2022: a database of Human, Mouse, Drosophila and Arabidopsis regulatory regions from an integrative analysis of DNA-binding sequencing experiments
    Fayrouz Hammal, Pierre de Langen, Aurélie Bergon, Fabrice Lopez, Benoit Ballester
    Nucleic Acids Research, Volume 50, Issue D1, 7 January 2022, Pages D316–D325,
    https://doi.org/10.1093/nar/gkab996

  7. Pregnancy Outcomes for Medicaid and CHIP Beneficiaries ages 15 to 44

    • catalog.data.gov
    • healthdata.gov
    • +1more
    Updated Jan 19, 2024
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    Pregnancy Outcomes for Medicaid and CHIP Beneficiaries ages 15 to 44 [Dataset]. https://catalog.data.gov/dataset/pregnancy-outcomes-for-medicaid-and-chip-beneficiaries-ages-15-to-44-e0154
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    Dataset updated
    Jan 19, 2024
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set includes monthly counts and rates (per 1,000 beneficiaries) of pregnancy outcomes, including (1) live births and (2) miscarriages, stillbirths, and terminations, for female Medicaid and CHIP beneficiaries ages 15 to 44 (as of the first day of the month), by state. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating pregnancy measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Procedure Codes - OT Professional, Claims Volume - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  8. Data from: A multiomic atlas of the aging hippocampus reveals molecular...

    • zenodo.org
    • portalinvestigacion.uniovi.es
    • +2more
    bin, txt, zip
    Updated Sep 23, 2024
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    Raúl F. Pérez; Raúl F. Pérez; Patricia Tezanos; Patricia Tezanos; Alfonso Peñarroya; Alfonso Peñarroya; Alejandro González-Ramón; Rocío G. Urdinguio; Rocío G. Urdinguio; Javier Gancedo-Verdejo; Javier Gancedo-Verdejo; Juan Ramón Tejedor; Juan Ramón Tejedor; Pablo Santamarina-Ojeda; Pablo Santamarina-Ojeda; Juan José Alba-Linares; Juan José Alba-Linares; Lidia Sainz-Ledo; Lidia Sainz-Ledo; Annalisa Roberti; Annalisa Roberti; Virginia López; Virginia López; Cristina Mangas; María Moro; Elisa Cintado; Elisa Cintado; Ignacio Ortea; Ignacio Ortea; Mar Rodriguez-Santamaria; Ramón Iglesias-Rey; Ramón Iglesias-Rey; Juan Castilla-Silgado; Cristina Tomás-Zapico; Cristina Tomás-Zapico; Eduardo Iglesias-Gutiérrez; Eduardo Iglesias-Gutiérrez; Benjamín Fernández-García; Benjamín Fernández-García; Jose Vicente Sanchez-Mut; Jose Vicente Sanchez-Mut; Jose Luis Trejo; Jose Luis Trejo; Agustín F. Fernández; Agustín F. Fernández; Mario F. Fraga; Mario F. Fraga; Alejandro González-Ramón; Cristina Mangas; María Moro; Mar Rodriguez-Santamaria; Juan Castilla-Silgado (2024). A multiomic atlas of the aging hippocampus reveals molecular rejuvenation in response to environmental stimulation (datasets and additional files) [Dataset]. http://doi.org/10.5281/zenodo.8372432
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    txt, zip, binAvailable download formats
    Dataset updated
    Sep 23, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Raúl F. Pérez; Raúl F. Pérez; Patricia Tezanos; Patricia Tezanos; Alfonso Peñarroya; Alfonso Peñarroya; Alejandro González-Ramón; Rocío G. Urdinguio; Rocío G. Urdinguio; Javier Gancedo-Verdejo; Javier Gancedo-Verdejo; Juan Ramón Tejedor; Juan Ramón Tejedor; Pablo Santamarina-Ojeda; Pablo Santamarina-Ojeda; Juan José Alba-Linares; Juan José Alba-Linares; Lidia Sainz-Ledo; Lidia Sainz-Ledo; Annalisa Roberti; Annalisa Roberti; Virginia López; Virginia López; Cristina Mangas; María Moro; Elisa Cintado; Elisa Cintado; Ignacio Ortea; Ignacio Ortea; Mar Rodriguez-Santamaria; Ramón Iglesias-Rey; Ramón Iglesias-Rey; Juan Castilla-Silgado; Cristina Tomás-Zapico; Cristina Tomás-Zapico; Eduardo Iglesias-Gutiérrez; Eduardo Iglesias-Gutiérrez; Benjamín Fernández-García; Benjamín Fernández-García; Jose Vicente Sanchez-Mut; Jose Vicente Sanchez-Mut; Jose Luis Trejo; Jose Luis Trejo; Agustín F. Fernández; Agustín F. Fernández; Mario F. Fraga; Mario F. Fraga; Alejandro González-Ramón; Cristina Mangas; María Moro; Mar Rodriguez-Santamaria; Juan Castilla-Silgado
    Description

    Aging is a universal biological phenomenon linked to many diseases, such as cancer or neurodegeneration. However, the molecular mechanisms underlying aging, or how lifestyle interventions such as cognitive stimulation can ameliorate this process, are yet to be clarified. Here, we performed a multi-omic profiling, including RNA-seq, ATAC-seq, ChIP-seq, EM-seq, SWATH-MS and single cell Multiome scRNA and scATAC-seq, in the dorsal hippocampus of young and old mouse subjects which were subject to cognitive stimulation using the paradigm of environmental enrichment. In this study we were able to describe the epigenomic landscape of aging and cognitive stimulation.

    This dataset contains information related to preprocessed datasets and additional files mentioned in the original manuscript.

  9. Program Information for Medicaid and CHIP Beneficiaries by Year

    • catalog.data.gov
    • data.virginia.gov
    • +1more
    Updated Feb 3, 2025
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    Centers for Medicare & Medicaid Services (2025). Program Information for Medicaid and CHIP Beneficiaries by Year [Dataset]. https://catalog.data.gov/dataset/program-information-for-medicaid-and-chip-beneficiaries-by-year-02cbe
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by program type (Medicaid or CHIP). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each program type over the year (duplicated count); (2) the number of beneficiaries enrolled in each program type as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly enrollment in each program type. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues, making the data unusable for calculating these measures. To assess data quality, analysts used measures featured in the DQ Atlas. Data for a state and year are considered unusable or of high concern based on DQ Atlas thresholds for the topics Medicaid-only enrollment and M-CHIP and S-CHIP Enrollment. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  10. Managed Care Information for Medicaid and CHIP Beneficiaries by Year

    • catalog.data.gov
    • healthdata.gov
    • +3more
    Updated Feb 3, 2025
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    Centers for Medicare & Medicaid Services (2025). Managed Care Information for Medicaid and CHIP Beneficiaries by Year [Dataset]. https://catalog.data.gov/dataset/managed-care-information-for-medicaid-and-chip-beneficiaries-by-year-dc72d
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by managed care participation (comprehensive managed care, primary care case management, MLTSS, including PACE, behavioral health organizations, nonmedical prepaid health plans, medical-only prepaid health plans, and other). There are three metrics presented: (1) the number of beneficiaries ever enrolled in each managed care plan type over the year (duplicated count); (2) the number of beneficiaries enrolled in each managed care plan type as of an individual’s last month of enrollment (duplicated count); and (3) average monthly enrollment in each managed care plan type. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some cells have a value of “DS”. Some states have serious data quality issues, making the data unusable for calculating these measures. To assess data quality, analysts used measures featured in the DQ Atlas. Data for a state and year are considered unusable or of high concern based on DQ Atlas thresholds for the topics Enrollment in CMC, Enrollment in PCCM Programs, and Enrollment in BHO Plans. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  11. COVID Testing and Testing-Related Services Provided to Medicaid and CHIP...

    • datasets.ai
    • data.virginia.gov
    • +2more
    8
    Updated Aug 8, 2024
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    U.S. Department of Health & Human Services (2024). COVID Testing and Testing-Related Services Provided to Medicaid and CHIP Beneficiaries [Dataset]. https://datasets.ai/datasets/covid-testing-and-testing-related-services-provided-to-medicaid-and-chip-beneficiaries
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    8Available download formats
    Dataset updated
    Aug 8, 2024
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Authors
    U.S. Department of Health & Human Services
    Description

    This data set includes monthly counts and rates (per 1,000 beneficiaries) of COVID-19 testing services provided to Medicaid and CHIP beneficiaries, by state.

    These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating COVID-19 testing services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Procedure Codes - OT Professional, Claims Volume - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data.

    Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  12. Program Information for Medicaid and CHIP Beneficiaries by Month

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Mar 28, 2023
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    data.medicaid.gov (2023). Program Information for Medicaid and CHIP Beneficiaries by Month [Dataset]. https://healthdata.gov/dataset/Program-Information-for-Medicaid-and-CHIP-Benefici/97m5-2uks
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    tsv, csv, json, application/rdfxml, xml, application/rssxmlAvailable download formats
    Dataset updated
    Mar 28, 2023
    Dataset provided by
    data.medicaid.gov
    Description

    This data set includes monthly enrollment counts of Medicaid and CHIP beneficiaries by program type (Medicaid or CHIP).

    These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topics Medicaid-only Enrollment and M-CHIP and S-CHIP Enrollment. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods.

    Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  13. Benefit Package for Medicaid and CHIP Beneficiaries by Year

    • data.virginia.gov
    • healthdata.gov
    • +2more
    csv
    Updated Jan 5, 2024
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    Centers for Medicare & Medicaid Services (2024). Benefit Package for Medicaid and CHIP Beneficiaries by Year [Dataset]. https://data.virginia.gov/dataset/benefit-package-for-medicaid-and-chip-beneficiaries-by-year
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    csvAvailable download formats
    Dataset updated
    Jan 5, 2024
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by benefit package (full-scope, comprehensive, limited, or unknown). There are three metrics presented: (1) the number of beneficiaries ever enrolled with each benefit package over the year (duplicated count); (2) the number of beneficiaries enrolled with each benefit package as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly enrollment with each benefit package.

    These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topic Restricted Benefits Code. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

    Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  14. Dual Status Information for Medicaid and CHIP Beneficiaries by Year

    • catalog.data.gov
    • healthdata.gov
    • +1more
    Updated Feb 3, 2025
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    Centers for Medicare & Medicaid Services (2025). Dual Status Information for Medicaid and CHIP Beneficiaries by Year [Dataset]. https://catalog.data.gov/dataset/dual-status-information-for-medicaid-and-chip-beneficiaries-by-year-405b3
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set presents annual enrollment counts of Medicaid and CHIP beneficiaries by dual eligibility status for Medicaid and Medicare (full dual eligibility, partial dual eligibility, or not dually eligible). There are three metrics presented: (1) the number of beneficiaries ever dually eligible for Medicaid and Medicare over the year (duplicated count); (2) the number of beneficiaries dually eligible for Medicaid and Medicare as of an individual’s last month of enrollment (unduplicated count); and (3) average monthly eligibility for Medicaid and Medicare. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topic Dually Enrolled in Medicare. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  15. Dental Services Provided to Medicaid and CHIP Beneficiaries Under Age 19

    • data.virginia.gov
    • healthdata.gov
    • +1more
    csv
    Updated Jan 5, 2024
    + more versions
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    Centers for Medicare & Medicaid Services (2024). Dental Services Provided to Medicaid and CHIP Beneficiaries Under Age 19 [Dataset]. https://data.virginia.gov/dataset/dental-services-provided-to-medicaid-and-chip-beneficiaries-under-age-19
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    csvAvailable download formats
    Dataset updated
    Jan 5, 2024
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set includes monthly counts and rates (per 1,000 beneficiaries) of dental services provided to Medicaid and CHIP beneficiaries under the age of 19 (as of the first day of the month), by state.

    These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating dental services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Procedure Codes - OT Professional, Claims Volume - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data.

    Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  16. Behavioral Health Services Provided to the Medicaid and CHIP Population

    • catalog.data.gov
    • healthdata.gov
    • +1more
    Updated Feb 3, 2025
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    Centers for Medicare & Medicaid Services (2025). Behavioral Health Services Provided to the Medicaid and CHIP Population [Dataset]. https://catalog.data.gov/dataset/behavioral-health-servicesprovided-to-the-medicaid-and-chip-population-b6f90
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    Dataset updated
    Feb 3, 2025
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set includes monthly counts and rates (per 1,000 beneficiaries) of behavioral health services, including emergency department services, inpatient services, intensive outpatient/partial hospitalizations, outpatient services, or services delivered through telehealth, provided to Medicaid and CHIP beneficiaries, by state. Users can filter by either mental health disorder or substance use disorder. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating behavioral health services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Diagnosis Code - IP, Diagnosis Code - OT. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  17. Acute Care Services Provided to the Medicaid and CHIP Population

    • data.virginia.gov
    • healthdata.gov
    • +2more
    csv
    Updated Jan 5, 2024
    + more versions
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    Centers for Medicare & Medicaid Services (2024). Acute Care Services Provided to the Medicaid and CHIP Population [Dataset]. https://data.virginia.gov/dataset/acute-care-services-provided-to-the-medicaid-and-chip-population
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    csvAvailable download formats
    Dataset updated
    Jan 5, 2024
    Dataset provided by
    Centers for Medicare & Medicaid Services
    Description

    This data set includes monthly counts and rates (per 1,000 beneficiaries) of acute care services, including emergency department (ED) visits, inpatient stays, intensive care unit (ICU) stays, and ICU stays that include ventilator use, provided to Medicaid and CHIP beneficiaries, by state. Users can filter to acute care services for any reason, or acute care services for COVID-19.

    These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating acute care services measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data.

    Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  18. Dual Status Information for Medicaid and CHIP Beneficiaries by Month

    • healthdata.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Mar 28, 2023
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    data.medicaid.gov (2023). Dual Status Information for Medicaid and CHIP Beneficiaries by Month [Dataset]. https://healthdata.gov/w/5npy-pruv/default?cur=FTpXQOspsNw&from=Ku3KPiKqP6H
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    csv, xml, json, application/rdfxml, application/rssxml, tsvAvailable download formats
    Dataset updated
    Mar 28, 2023
    Dataset provided by
    data.medicaid.gov
    Description

    This data set includes monthly enrollment counts of Medicaid and CHIP beneficiaries by dual eligibility status for Medicaid and Medicare (full dual eligibility, partial dual eligibility, or not dually eligible).

    These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating these measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable or of high concern based on DQ Atlas thresholds for the topic Dually Enrolled in Medicare. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods.

    Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  19. g

    Respiratory Conditions in the Medicaid and CHIP Population

    • gimi9.com
    • healthdata.gov
    • +3more
    Updated Dec 4, 2024
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    (2024). Respiratory Conditions in the Medicaid and CHIP Population [Dataset]. https://www.gimi9.com/dataset/data-gov_respiratory-conditions-in-the-medicaid-and-chip-population/
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    Dataset updated
    Dec 4, 2024
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This data set includes monthly counts and percentages of Medicaid and CHIP beneficiaries, by state, who received at least one service for each of the following conditions: acute bronchitis, acute respiratory distress, bronchitis not other specified (NOS), COVID-19 (based on the presence of diagnosis code U07.1), influenza, lower or acute respiratory infection, pneumonia, respiratory infection NOS, and suspected COVID-19 (based on the presence of diagnosis code B97.29). These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues for one or more months, making the data unusable for calculating COVID-related conditions measures. To assess data quality, analysts adapted measures featured in the DQ Atlas. Data for a state and month are considered unusable if at least one of the following topics meets the DQ Atlas threshold for unusable: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Claims Volume - IP, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

  20. g

    Number of pregnant and postpartum Medicaid and CHIP beneficiaries, 2017-2021...

    • gimi9.com
    Updated Jan 4, 2022
    + more versions
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    (2022). Number of pregnant and postpartum Medicaid and CHIP beneficiaries, 2017-2021 | gimi9.com [Dataset]. https://www.gimi9.com/dataset/data-gov_number-of-pregnant-and-postpartum-medicaid-and-chip-beneficiaries-2017-2020/
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    Dataset updated
    Jan 4, 2022
    License

    U.S. Government Workshttps://www.usa.gov/government-works
    License information was derived automatically

    Description

    This table presents the number of pregnant and postpartum Medicaid and CHIP beneficiaries, 2017-2021. It includes (1) the number and percentage of beneficiaries ever pregnant in the year; (2) the number and percentage of live births in the year; (3) the number and percentage of miscarriages, stillbirths, or terminations in the year; and (4) the number and percentage of births with an unknown delivery outcome in the year. These metrics are based on data in the T-MSIS Analytic Files (TAF). Some states have serious data quality issues, making the data unusable for identifying this population. Data for a state are considered unusable based on DQ Atlas thresholds for the following topics: Total Medicaid and CHIP Enrollment, Claims Volume - IP, Claims Volume - OT, Claims Volume - IP, Diagnosis Code - IP, Diagnosis Code - OT, Procedure Codes - OT Professional. Cells with a value of “DQ” indicate that data were suppressed due to unusable data. Data from Maryland, Tennessee, and Utah are omitted from the tables due to data quality concerns. Maryland was excluded in 2017 due to unusable diagnosis codes in the IP file and the OT file. Tennessee was excluded due to unusable diagnosis codes in the IP file in 2017 - 2019. Utah was excluded due to unusable procedure codes on OT professional claims in 2017 - 2020. In addition, states with a high data quality concern on one or more measures are noted in the table in the "Data Quality" column. Please refer to the DQ Atlas at http://medicaid.gov/dq-atlas for more information about data quality assessment methods. Some cells have a value of “DS”. This indicates that data were suppressed for confidentiality reasons because the group included fewer than 11 beneficiaries.

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Email
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Close
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Qian Qin; Shenglin Mei; Qiu Wu; Hanfei Sun; Lewyn Li; Len Taing; Sujun Chen; Fugen Li; Tao Liu; Chongzhi Zang; Han Xu; Yiwen Chen; Clifford Meyer; Yong Zhang; Myles Brown; Henry Long; X. Liu (2023). Additional file 2: Table S1. of ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline [Dataset]. http://doi.org/10.6084/m9.figshare.c.3636644_D9.v1

Additional file 2: Table S1. of ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline

Related Article
Explore at:
xlsxAvailable download formats
Dataset updated
Jun 1, 2023
Dataset provided by
figshare
Authors
Qian Qin; Shenglin Mei; Qiu Wu; Hanfei Sun; Lewyn Li; Len Taing; Sujun Chen; Fugen Li; Tao Liu; Chongzhi Zang; Han Xu; Yiwen Chen; Clifford Meyer; Yong Zhang; Myles Brown; Henry Long; X. Liu
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

Sheet1 ToolsComparison: ChIP-seq pipeline software comparison. Sheet2 Examples of ChiLin report. A summary of example data annotation of transcription factor, chromatin regulatory factor and histone modification ChIP-seq data. Sheet3 Protein classification standard for the 8 categories. Sheet4 Protein classification results. Sheet5 BWA QC Database. ChiLin samples and datasets quality metrics across three layers. A clean up table of cistrome samples and datasets quality metrics for ChiLin users’ reference. The QC results is based on the reference of hg38 and mm10 assembly. (XLSX 10363 kb)

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