A tool for cell-free DNA based cancer diagnosis and tissue-of-origin prediction.
Apache Commons Math (if you want to build the source)
java -jar CancerLocator.jar config_file
config_file is a configuration file in Java Properties format. Options in the configuration file: trainFile: the traning file, only methylation values needed testMethyFile: the testing file with methylation values testDepthFile: the testing file with number of CpG measurements for each cluster typeMappingFile: the file used to map sample types to prediction classes resultFile: the output file thetaStep: the interval of theta values used in the inference methylationRangeCutoff: methylation range cutoff used for feature filtering logLikelihoodRatioCutoff: the cutoff of log-likelihood ratio used in prediction nThreads: number of threads
All the input and output files are tab delimited. trainFile, testMethyFile and testDepthFile must have the same number of columns.
Each line represents a training sample. The first column is the sample type and the remaining columns are methylation values (beta values) of the features.
Each line represents a training sample. The first column is the sample ID and the remaining columns are methylation levels (beta values) of the features.
Each line represents a training sample. The first column is the sample ID and the remaining columns are CpG counts on reads aligned to these clusters.
Column 1: the sample types
Column 2: corresponding classes in the prediction
For example, the following two lines in this file indicates that both LUAD and LUSC samples would be considered as lung cancer in the prediction.
LUAD lung cancer
LUSC lung cancer
Column 1: sample ID
Column 2: likelihood ratio in logarithmic scale
Column 3: predicted blood tumor burden (i.e. theta value)
Column 4: predicted sample calss (normal or one of the cancer tissues)
Prepare the input files
trainFile is generated using methylation microarray and/or WGBS data. testMethyFile and testDepthFile are generated from processed WGBS data.
For microarray data, the average methylation level of all CpG sites in a cluster is used to represent methylation level of that cluster. A cluster’s methylation level is marked as “not available” (NA) if less than half of its CpG sites have methylation measurements.
For WGBS data, the methylation level of a CpG cluster is calculated as the ratio between the number of methylated cytosines and the total number of cytosines within the cluster. However, if the total number of cytosines in the reads aligned to a CpG cluster is less than a given threshold (30 as used in the paper), the methylation level of this cluster is considered as NA. Bismark was used in the CancerLocator paper to map WGBS reads and determine methylation states.
Two TSV files are provided under the data folder, in case you want to use the same set of CpG clusters as defined in our paper:
a. cpg_clusters_boundaries.tsv.gz_: The file with start and end positions of each CpG cluster.
b. cpg_clusters_cpg_sites.tsv.gz: The file with the mapping information between the probes on Infinium Human Methylation 450K array and these CpG clusters.
Please note that Hg19 is used as the reference genome assembly and all the coordinates are 1-based.
The examples of all the files needed to run CancerLocator are provided under the "example" folder.
To run the example:
CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA
Genome Biology, March 2017 18:53. DOI:10.1186/s13059-017-1191-5
Shuli Kang, Qingjiao Li, Quan Chen, Yonggang Zhou, Stacy Park, Gina Lee, Brandon Grimes, Kostyantyn Krysan, Min Yu, Wei Wang, Frank Alber, Fengzhu Sun, Steven M. Dubinett*, Wenyuan Li*, Xianghong Jasmine Zhou* (* Joint corresponding author)