Source Data Underlying Manuscript Figures

<b>Fig1aSupplementaryDataMixture.xlsx</b><br>Source data underlying <b>Figure 1a</b> of the manuscript. In Silico mixtures which are deconvolved.<br>Row names:CellType - Cell type spiked in at a particular fraction<br>SpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br><b>Fig1aSupplementaryDataDeconvolution.xlsx<br></b><br>Source data underlying <b>Figure 1a</b> of the manuscript. Results of deconvolution of in silico mixtures.<br>Column names:Method - Method used for deconvolution<br>CellType - Cell type spiked in at a particular fractionSpikePercentage - Percentage cell type is spiked in at<br>TumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>Replicate - Replicate number<br><br>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.<br><b>Fig1bSupplementaryDataMixture.xlsx</b><br>Source data underlying <b>Figure 1b</b> of the manuscript. In Vitro mixtures which are deconvolved.<br>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<br>CancerType - Cancer cell line used as the tumor content<br>NoiseCoefficient - Amount of noise added to the mixture<br>Replicate - Replicate number<br>Cell type names ending in "_GT" are the ground truth percentages of those cell types<br><br>Rows with "cg" correspond to CpG site on 450k methylation array with the Beta values for each mixture in the columns<br><b>Fig1bSupplementaryDataDeconvolution.xlsx</b><br><b><br></b>Source data underlying <b>Figure 1b</b> of the manuscript. Results of deconvolution of in vitro mixtures.<br>Column names:Method - Method used for deconvolution<br>Mixture - In Vitro mixture name -- this corresponds to the cell type fractions in the mixtureTumorContent - Percentage of tumor content added to methylation mixture<br>CancerType - Cancer cell line used as the tumor content<br>NoiseCoefficient - Amount of noise added to the mixture<br>Replicate - Replicate number<br><br>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.<br><b>Fig1cSupplementaryDataDeconvolution.xlsx</b><br>Source data underlying <b>Figure 1c</b> of the manuscript. Results of deconvolution of whole blood and engineered mixtures using LTS regression and the new signature matrix.<b><br></b><br>Column names:Mixture - Mixture name -- this corresponds to the cell type fractions in the mixture<br>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.<br>RMSE1,RMSE2,R1,R2 -- these correspond to the goodness-of-fit metrics<br><b>Fig2a2bSupplementaryDataDeconvolution.xlsx</b><br>Source data underlying <b>Figures 2a</b> and <b>2b</b> of the manuscript. Results of deconvolution of true positive and true negative samples using LTS regression and the new signature matrix.<br><br>Column names:<br>Sample - Sample GEO accession<br>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<br>Tissue - the annotated tissue (or tissue of origin)<br><b>Fig2c2dSupplementaryDataDeconvolution.xlsx</b><br>Source data underlying <b>Figures 2c</b> and <b>2d</b> 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.<br><br>Column names:<br>Mixture - The mixture name with the amount of true negative fraction in the mixture indicated in the name<br>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

<b>Fig1aSupplementaryDataMixture.xlsx</b><br>本文件为论文图1a的源数据，包含待解卷积的计算机模拟（in silico）混合样本。<br>行名说明：<br>CellType：以特定比例掺入的细胞类型<br>SpikePercentage：该细胞类型的掺入比例<br>TumorContent：添加至甲基化混合样本中的肿瘤组分占比<br>CancerType：用作肿瘤组分的癌细胞系<br>Replicate：重复实验编号<br><br>以“_GT”结尾的细胞类型名称代表该细胞类型的真实百分比（ground truth）。<br><br>行名包含“cg”的行对应450k甲基化芯片上的CpG位点，列则为各混合样本对应的Beta值。<br><br><b>Fig1aSupplementaryDataDeconvolution.xlsx</b><br>本文件为论文图1a的源数据，包含计算机模拟混合样本的解卷积结果。<br>列名说明：<br>Method：用于解卷积的方法名称<br>CellType：以特定比例掺入的细胞类型；SpikePercentage：该细胞类型的掺入比例<br>TumorContent：添加至甲基化混合样本中的肿瘤组分占比<br>CancerType：用作肿瘤组分的癌细胞系<br>Replicate：重复实验编号<br><br>以“_GT”结尾的细胞类型名称代表该细胞类型的真实百分比（ground truth）；未以“_GT”结尾的细胞类型名称则代表使用对应方法预测得到的细胞类型占比。<br><br><b>Fig1bSupplementaryDataMixture.xlsx</b><br>本文件为论文图1b的源数据，包含待解卷积的体外（in vitro）混合样本。<br>行名说明：<br>Mixture：体外混合样本名称，对应混合样本中的细胞类型占比<br>TumorContent：添加至甲基化混合样本中的肿瘤组分占比<br>CancerType：用作肿瘤组分的癌细胞系<br>NoiseCoefficient：添加至混合样本中的噪声系数<br>Replicate：重复实验编号<br><br>以“_GT”结尾的细胞类型名称代表该细胞类型的真实百分比（ground truth）。<br><br>行名包含“cg”的行对应450k甲基化芯片上的CpG位点，列则为各混合样本对应的Beta值。<br><br><b>Fig1bSupplementaryDataDeconvolution.xlsx</b><br><br>本文件为论文图1b的源数据，包含体外混合样本的解卷积结果。<br>列名说明：<br>Method：用于解卷积的方法名称<br>Mixture：体外混合样本名称，对应混合样本中的细胞类型占比<br>TumorContent：添加至甲基化混合样本中的肿瘤组分占比<br>CancerType：用作肿瘤组分的癌细胞系<br>NoiseCoefficient：添加至混合样本中的噪声系数<br>Replicate：重复实验编号<br><br>以“_GT”结尾的细胞类型名称代表该细胞类型的真实百分比（ground truth）；未以“_GT”结尾的细胞类型名称则代表使用对应方法预测得到的细胞类型占比。<br><br><b>Fig1cSupplementaryDataDeconvolution.xlsx</b><br>本文件为论文图1c的源数据，包含使用最小截平方回归（LTS regression）与新型特征矩阵对全血及工程化混合样本进行解卷积的结果。<br><br>列名说明：<br>Mixture：混合样本名称，对应混合样本中的细胞类型占比<br>以“_GT”结尾的细胞类型名称代表该细胞类型的真实百分比（ground truth）；未以“_GT”结尾的细胞类型名称则代表使用对应方法预测得到的细胞类型占比。<br>RMSE1、RMSE2、R1、R2：对应拟合优度指标。<br><br><b>Fig2a2bSupplementaryDataDeconvolution.xlsx</b><br>本文件为论文图2a与图2b的源数据，包含使用最小截平方回归与新型特征矩阵对阳性真实样本与阴性真实样本进行解卷积的结果。<br><br>列名说明：<br>Sample：样本的GEO登录号（GEO accession）<br>RMSE1、R1、RMSE2、R2：拟合优度指标，即图2a与图2b中绘制的指标<br>Cell type names：使用最小截平方回归与新型特征矩阵预测得到的细胞类型占比<br>Tissue：注释的组织（或组织来源）<br><br><b>Fig2c2dSupplementaryDataDeconvolution.xlsx</b><br>本文件为论文图2c与图2d的源数据，包含使用最小截平方回归与新型特征矩阵，对由阳性真实样本与阴性真实样本按不同比例组合生成的混合样本进行解卷积的结果。<br><br>列名说明：<br>Mixture：混合样本名称，名称中包含了该混合样本中阴性真实组分的占比<br>RMSE1、R1、RMSE2、R2：拟合优度指标，即图2c与图2d中绘制的指标<br>Cell type names：使用最小截平方回归与新型特征矩阵预测得到的细胞类型占比