PICTographPlus: Data Sets and Resources

Published: 20 April 2026| Version 2 | DOI: 10.17632/cv66sgfcfn.2
Contributors:
Jiaying Lai, Yi Yang, Kathleen Noller, Yunzhou Liu, Archana Balan, Prathima Nagendra, Luciane Kagohara, Elana Fertig, Laura Wood, Rachel Karchin

Description

All the code are freely available at https://github.com/KarchinLab/pictographPlus and https://github.com/KarchinLab/PICTographPlus_manuscript. Benchmarking dataset ------------------------------------------------------------------------------- all benchmarking scripts and data information can be found in benchmarking folder. A README.md is provided with detailed instructions. Case analysis dataset ------------------------------------------------------------------------------- Inputs: CRUK0004_input: input data for TRACERx patient. CRUK0004_SNV.csv: input somatic mutation file CRUK0004_facets.csv: input somatic copy number file CRUK0004_RNA.csv: input RNA read counts MK74_input: input data for Semaan et al. IPMN patient. MK74_snv.csv: input somatic mutation file MK74_cn.csv: input somatic copy number file MK74_rna.csv: input RNA read counts PCSI0380_input: input data for PanCuRx PDAC patient. PCSI0380_snv.csv: input somatic mutation/copy number file PCSI0380_.csv: input RNA read counts Outputs: CRUK0004_output: output data for TRACERx patient. MK74_output: output data for Semaan et al. IPMN patient. PCSI0380_output: output data for PanCuRx PDAC patient. Each of the above output folder contains the following files: tree.csv: PICTographPlus tree subclone_proportion.csv: subclone proportion for each sample clusterAssign.csv: assignment of mutation to each cluster purity.csv: estimated purity per sample mcf.csv: cluster mutation cellular fraction clonal_expression.csv: clone-level gene expression GSEA: gene set enrichment analysis results

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Categories

Lung Cancer, Pancreatic Cancer, Computational Genomics, RNA Sequencing, Phylogeny, Genome Sequencing

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