Source Data Underlying Manuscript Figures
Douglas V. Arneson · Figshare · 2020
Fig1aSupplementaryDataMixture.xlsx Source data underlying Figure 1a of the manuscript. In Silico mixtures which are deconvolved. Row names:CellType - Cell type spiked in at a particular fraction SpikePercentage - Percentage cell type is spiked in at TumorContent - Percentage of tumor content added to methylation mixture CancerType - Cancer cell line used as the tumor content Replicate - Replicate number Cell type names ending in "_GT" are the ground truth percentages of those cell types Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns Fig1aSupplementaryDataDeconvolution.xlsx Source data underlying Figure 1a of the manuscript. Results of deconvolution of in silico mixtures. Column names:Method - Method used for deconvolution CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at TumorContent - Percentage of tumor content added to methylation mixture CancerType - Cancer cell line used as the tumor content Replicate - Replicate number Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method. Fig1bSupplementaryDataMixture.xlsx Source data underlying Figure 1b of the manuscript. In Vitro mixtures which are deconvolved. Row names:Mixture - In Vitro mixture name -- this corresponds to the cell type fractions in the mixtureTumorContent - Percentage of tumor content added to methylation mixture CancerType - Cancer cell line used as the tumor content NoiseCoefficient - Amount of noise added to the mixture Replicate - Replicate number Cell type names ending in "_GT" are the ground truth percentages of those cell types Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns Fig1bSupplementaryDataDeconvolution.xlsx Source data underlying Figure 1b of the manuscript. Results of deconvolution of in vitro mixtures. Column names:Method - Method used for deconvolution Mixture - In Vitro mixture name -- this corresponds to the cell type fractions in the mixtureTumorContent - Percentage of tumor content added to methylation mixture CancerType - Cancer cell line used as the tumor content NoiseCoefficient - Amount of noise added to the mixture Replicate - Replicate number Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method. Fig1cSupplementaryDataDeconvolution.xlsx Source data underlying Figure 1c of the manuscript. Results of deconvolution of whole blood and engineered mixtures using LTS regression and the new signature matrix. Column names:Mixture - Mixture name -- this corresponds to the cell type fractions in the mixture Cell type names ending in "_GT" are the ground truth percentages of those cell types; cell type names not ending in "_GT" are the predicted cell type fractions using the specified method. RMSE1,RMSE2,R1,R2 -- these correspond to the goodness-of-fit metrics Fig2a2bSupplementaryDataDeconvolution.xlsx Source data underlying Figures 2a and 2b of the manuscript. Results of deconvolution of true positive and true negative samples using LTS regression and the new signature matrix. Column names: Sample - Sample GEO accession RMSE1, R1, RMSE2, R2 - goodness of fit metrics which are plotted in Figures 2a and 2bCell type names - the predicted cell type fractions using LTS and the new signature Tissue - the annotated tissue (or tissue of origin) Fig2c2dSupplementaryDataMixture.txt Source data underlying Figures 2c and 2d of the manuscript. Mixtures generated from pairwise combinations of true positive and true negative samples with varying fractions of true negative content. Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns. Columns are the mixture name with the amount of true negative. Fig2c2dSupplementaryDataDeconvolution.xlsx Source data underlying Figures 2c and 2d of the manuscript. Results of deconvolution of mixtures generated from pairwise combinations of true positive and true negative samples with varying fractions of true negative content using LTS regression and the new signature matrix. Column names: Mixture - The mixture name with the amount of true negative fraction in the mixture indicated in the name RMSE1, R1, RMSE2, R2 - goodness of fit metrics which are plotted in Figures 2c and 2dCell type names - the predicted cell type fractions using LTS and the new signature Fig2eSupplementaryDataCorrelations.xlsx Source data underlying Figure 2e of the manuscript. Results of deconvolution of TCGA samples which were used to find correlations between cell types fractions or goodness-of-fit metrics and the consensus purity estimate (CPE). Column names: Sample - TCGA sample IDRMSE1, R1, RMSE2, R2 - goodness of fit metricsCell type names - the predicted cell type fractions using LTS and the new signatureCPE - consensus purity estimate for the TCGA sample