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seasoncloud / Clonalscope

Clonalscope is a subclone detection method based on copy number alterations (CNAs) for single-cell and ST tumor sequencing data. Clonalscope is able to detect subclones, label malignant cells, and trace subclones for both scRNA-seq and ST data.
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Output Files and Their Structure is Not Documented #5

Open DarioS opened 1 year ago

DarioS commented 1 year ago

What files does the software create and what does each of the columns mean? This should be defined in the user guide.

jiazhen-rong commented 1 year ago

Hello, thank you for the suggestions and we will change the tutorial and the documentation in the future update to reflect the output content. In short for explanation, the output (Cov_obj) is a list of several components generated by the RunCovCluster integrative function:

  1. "result"$: A list with the output files from the $ iteration.
  2. _"resultfinal": A list with the output files from the last iteration. (The final output that can be used for plotting)
  3. "celltype0": cell type used in the analysis. (same as our input celltype0 format)

"result_final" stores the variables that was performed in each step in the RunCovCluster integrative function:

  1. _Cov_obj$result_final$deltasall: containing the summary statistics of segments during coverage estimations, such as genes in each segment, etc. The detailed explaination is in the header of EstRegionCov.R.
  2. _Cov_obj$result_final$cna_statesWGS: CNA state based on input segments.
  3. _Cov_obj$result_final$dfobj: containing the final estiamted cell x segment CNV profile generated from fold changee estimation. Cov_obj$result_final$df_obj$df can be used for heatmap visualization, etc.
  4. _Cov_obj$resultfinal$clustering: correspond to the output in BayesNonparCluster.R. It contains the variables from the non parametric clustering process.
  5. _Cov_obj$resultfinal$clustering2: correspond to to the output in MCMCtrim.R.
  6. _Cov_obj$resultfinal$result: correspond to the output in AssignCluster.R. In this step we re-assign clusters of each cell based on input parameters like minimum number of cells in each cluster. _Cov_obj$resultfinal$result$Zest contains the final cluster assignment.