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Search.setIndex({"alltitles":{"API References":[[55,null]],"Additional Metadata Fields":[[33,"additional-metadata-fields"]],"Additional Visualization Examples":[[19,null],[25,"additional-visualization-examples"]],"Age":[[32,"age"]],"Basic Usage":[[30,"basic-usage"]],"Best Practices":[[30,"best-practices"]],"Biolearn":[[31,null],[59,"biolearn"]],"Biolearn and the Future of Biomarkers":[[60,null]],"Building a competition submission using an existing model":[[14,null]],"Calculate \u201cbiological age\u201d based on PhenotypicAge":[[9,"calculate-biological-age-based-on-phenotypicage"]],"Challenge Submission Examples":[[11,null],[25,"challenge-submission-examples"]],"Clock/model visualizations using GEO datasets":[[20,null]],"Clocks and Other Models":[[28,null]],"Common Errors":[[30,"common-errors"]],"Compare to known cell proportions measured with FACS (fluorescence-activated cell sorting)":[[17,"compare-to-known-cell-proportions-measured-with-facs-fluorescence-activated-cell-sorting"]],"Composite Biomarkers Examples":[[8,null],[25,"composite-biomarkers-examples"]],"Computation times":[[7,null],[10,null],[13,null],[18,null],[23,null],[26,null],[61,null]],"Contributing":[[59,"contributing"]],"Core Team":[[0,"core-team"]],"Create a dictionary of dataset display names to GeoData objects":[[22,"create-a-dictionary-of-dataset-display-names-to-geodata-objects"]],"DNA Methylation Array Data Standard V-2410":[[33,null]],"DNA methylation visualizations using GEO datasets":[[21,null]],"Data Requirements":[[30,"data-requirements"]],"Data Values":[[33,"data-values"]],"Deconvolution Examples":[[16,null],[25,"deconvolution-examples"]],"Detailed Setup":[[30,"detailed-setup"]],"Discord server":[[59,"discord-server"]],"Down Syndrome Epigenetic Plotting":[[3,null]],"Estimate cell proportions using EPIC deconvolution model":[[17,"estimate-cell-proportions-using-epic-deconvolution-model"]],"Example Files":[[33,"example-files"]],"Example Script":[[30,"example-script"]],"Examples":[[25,null]],"Examples using biolearn.data_library.DataLibrary":[[39,"examples-using-biolearn-data-library-datalibrary"]],"Examples using biolearn.data_library.DataSource":[[40,"examples-using-biolearn-data-library-datasource"]],"Examples using biolearn.data_library.GeoData":[[41,"examples-using-biolearn-data-library-geodata"]],"Examples using biolearn.imputation.impute_from_standard":[[44,"examples-using-biolearn-imputation-impute-from-standard"]],"Examples using biolearn.load.load_nhanes":[[46,"examples-using-biolearn-load-load-nhanes"]],"Examples using biolearn.model_gallery.ModelGallery":[[47,"examples-using-biolearn-model-gallery-modelgallery"]],"Examples using biolearn.mortality.run_predictions":[[53,"examples-using-biolearn-mortality-run-predictions"]],"Exploring the Challenge Data":[[12,null]],"Featured examples":[[31,"featured-examples"]],"File Format":[[33,"file-format"],[33,"id1"]],"Finally extract the age data from the metadata from GEO and plot the results using seaborn":[[4,"finally-extract-the-age-data-from-the-metadata-from-geo-and-plot-the-results-using-seaborn"]],"Finally generate a boxplot to show the predictive power":[[3,"finally-generate-a-boxplot-to-show-the-predictive-power"]],"First load up some methylation data from GEO using the data library":[[3,"first-load-up-some-methylation-data-from-geo-using-the-data-library"],[4,"first-load-up-some-methylation-data-from-geo-using-the-data-library"]],"First load up some transcriptomic data from GEO using the data library":[[6,"first-load-up-some-transcriptomic-data-from-geo-using-the-data-library"]],"GEO Data Sources":[[29,null]],"Generate a quality control report for each dataset":[[22,"generate-a-quality-control-report-for-each-dataset"]],"Getting Your API Key":[[30,"getting-your-api-key"]],"Hurdle InflammAge API 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a local data file":[[5,"load-up-a-local-data-file"]],"Load up a target dataset and run the imputation":[[2,"load-up-a-target-dataset-and-run-the-imputation"]],"Load up some training data":[[15,"load-up-some-training-data"]],"Loading NHANES 2010 data":[[9,"loading-nhanes-2010-data"]],"Loading up the data for the competition":[[12,"loading-up-the-data-for-the-competition"],[14,"loading-up-the-data-for-the-competition"],[15,"loading-up-the-data-for-the-competition"]],"Local Data Loading":[[5,null]],"Metadata File Standard":[[33,"metadata-file-standard"]],"Metadata Standard & Quick Search":[[32,null]],"Metadata is loaded if available":[[5,"metadata-is-loaded-if-available"]],"Methylation Matrix File Standard":[[33,"methylation-matrix-file-standard"]],"Missing Value Handling":[[30,"missing-value-handling"]],"Model IP and Usage":[[34,null]],"Non-Commercial Use Only":[[30,"non-commercial-use-only"]],"Now run clock predictions on the dataset before and after":[[2,"now-run-clock-predictions-on-the-dataset-before-and-after"]],"Now run the down syndrome model on the data to get a score":[[3,"now-run-the-down-syndrome-model-on-the-data-to-get-a-score"]],"Now run the transcriptomic clock to predict age":[[6,"now-run-the-transcriptomic-clock-to-predict-age"]],"Now run three different clocks on the dataset to produce epigenetic clock ages":[[4,"now-run-three-different-clocks-on-the-dataset-to-produce-epigenetic-clock-ages"]],"Omics Biomarker Examples":[[1,null],[25,"omics-biomarker-examples"]],"Other contributors":[[0,"other-contributors"]],"Partner Organizations":[[0,"partner-organizations"]],"Performing custom imputations":[[2,null]],"Plot survival curve for people with accelerated aging (older biological age) vs decelerated aging (younger biological age)":[[9,"plot-survival-curve-for-people-with-accelerated-aging-older-biological-age-vs-decelerated-aging-younger-biological-age"]],"Plot the results against the chronological age using seaborn":[[6,"plot-the-results-against-the-chronological-age-using-seaborn"]],"Plot the results to see how good our model is":[[15,"plot-the-results-to-see-how-good-our-model-is"]],"Preprocessing":[[33,"preprocessing"]],"Privacy Notice":[[30,"privacy-notice"]],"Python example":[[32,"python-example"]],"Quality control visualization using GEO datasets":[[22,null]],"Quick Start":[[30,"quick-start"]],"Quickstart":[[59,null]],"References":[[33,"references"]],"Requirements":[[59,"requirements"]],"Run the challenge data through the model":[[15,"run-the-challenge-data-through-the-model"]],"Save the results as an output file for submission":[[15,"save-the-results-as-an-output-file-for-submission"]],"Seperate data into training and test sets":[[15,"seperate-data-into-training-and-test-sets"]],"Setting Your API Key":[[30,"setting-your-api-key"]],"Sex codes":[[32,"sex-codes"]],"Show relation between biological age and chronological age":[[9,"show-relation-between-biological-age-and-chronological-age"]],"Some of the data overlaps while some does not but all the metadata is combined":[[12,"some-of-the-data-overlaps-while-some-does-not-but-all-the-metadata-is-combined"]],"Standard Metadata Fields":[[33,"standard-metadata-fields"]],"Support":[[30,"support"]],"Team":[[0,null]],"Technical Details":[[30,"technical-details"]],"The challenge data also has proteomic data":[[12,"the-challenge-data-also-has-proteomic-data"]],"The challenge data has methylation data":[[12,"the-challenge-data-has-methylation-data"]],"Train a model using elastic net":[[15,"train-a-model-using-elastic-net"]],"Training an ElasticNet model":[[15,null]],"Troubleshooting":[[30,"troubleshooting"]],"Usage Examples":[[30,"usage-examples"]],"Use the Lin model to predict the age":[[14,"use-the-lin-model-to-predict-the-age"]],"Using Hurdle\u2019s InflammAge Model in Biolearn":[[30,null]],"Visualize DNA methylation against age with linear and polynomial regression":[[21,"visualize-dna-methylation-against-age-with-linear-and-polynomial-regression"]],"Visualize DNA methylation levels by age and sex in a violin plot":[[21,"visualize-dna-methylation-levels-by-age-and-sex-in-a-violin-plot"]],"Visualize a correlation matrix across aging clocks/models":[[20,"visualize-a-correlation-matrix-across-aging-clocks-models"]],"Visualize aging clock/model predictions against chronological age":[[20,"visualize-aging-clock-model-predictions-against-chronological-age"]],"Visualize clock/model chronological age deviations across samples in a heatmap":[[20,"visualize-clock-model-chronological-age-deviations-across-samples-in-a-heatmap"]],"Visualize model predictions against its corresponding health outcome":[[20,"visualize-model-predictions-against-its-corresponding-health-outcome"]],"Visualize the comparison of age predictions":[[2,"visualize-the-comparison-of-age-predictions"]],"Visualize the distribution of sample deviations from the population 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