Package check result: ERROR

Check: CRAN incoming feasibility, Result: NOTE
  Maintainer: ‘Diego Mañanes <dmananesc@cnic.es>’
  
  New submission
  
  Package was archived on CRAN
  
  Possibly misspelled words in DESCRIPTION:
    Cabo (10:401)
    Deconvolution (3:8, 10:14)
    Torroja (10:381)
    deconvolution (10:72)
    scRNA (10:129, 10:361)
  
  CRAN repository db overrides:
    X-CRAN-Comment: Archived on 2024-10-02 as issues were not corrected
      in time.
  
  Found the following (possibly) invalid URLs:
    URL: https://www.nature.com/articles/ncomms15081
      From: README.md
      Status: Error
      Message: Operation timed out after 60002 milliseconds with 0 bytes received
    URL: https://www.nature.com/articles/s41588-020-0636-z
      From: README.md
      Status: 503
      Message: Service Unavailable

Check: examples, Result: ERROR
  Running examples in ‘digitalDLSorteR-Ex.R’ failed
  The error most likely occurred in:
  
  > base::assign(".ptime", proc.time(), pos = "CheckExEnv")
  > ### Name: interGradientsDL
  > ### Title: Calculate gradients of predicted cell types/loss function with
  > ###   respect to input features for interpreting trained deconvolution
  > ###   models
  > ### Aliases: interGradientsDL
  > 
  > ### ** Examples
  > 
  > ## No test: 
  > set.seed(123)
  > sce <- SingleCellExperiment::SingleCellExperiment(
  +   assays = list(
  +     counts = matrix(
  +       rpois(30, lambda = 5), nrow = 15, ncol = 10,
  +       dimnames = list(paste0("Gene", seq(15)), paste0("RHC", seq(10)))
  +     )
  +   ),
  +   colData = data.frame(
  +     Cell_ID = paste0("RHC", seq(10)),
  +     Cell_Type = sample(x = paste0("CellType", seq(2)), size = 10,
  +                        replace = TRUE)
  +   ),
  +   rowData = data.frame(
  +     Gene_ID = paste0("Gene", seq(15))
  +   )
  + )
  > DDLS <- createDDLSobject(
  +   sc.data = sce,
  +   sc.cell.ID.column = "Cell_ID",
  +   sc.gene.ID.column = "Gene_ID",
  +   sc.filt.genes.cluster = FALSE
  + )
  === Bulk RNA-seq data not provided
  === Processing single-cell data
        - Filtering features:
           - Selected features: 15
           - Discarded features: 0
  
  === No mitochondrial genes were found by using ^mt- as regrex
  
  === Final number of dimensions for further analyses: 15
  > prop.design <- data.frame(
  +   Cell_Type = paste0("CellType", seq(2)),
  +   from = c(1, 30),
  +   to = c(15, 70)
  + )
  > DDLS <- generateBulkCellMatrix(
  +   object = DDLS,
  +   cell.ID.column = "Cell_ID",
  +   cell.type.column = "Cell_Type",
  +   prob.design = prop.design, 
  +   num.bulk.samples = 50,
  +   verbose = TRUE
  + )
  
  === The number of bulk RNA-Seq samples that will be generated is equal to 50
  
  === Training set cells by type:
      - CellType1: 4
      - CellType2: 3
  
  === Test set cells by type:
      - CellType1: 2
      - CellType2: 1
  
  === Probability matrix for training data:
      - Bulk RNA-Seq samples: 38
      - Cell types: 2
  
  === Probability matrix for test data:
      - Bulk RNA-Seq samples: 12
      - Cell types: 2
  
  DONE
  > DDLS <- simBulkProfiles(DDLS)
  === Setting parallel environment to 1 thread(s)
  
  === Generating train bulk samples:
  
  === Generating test bulk samples:
  
  DONE
  > DDLS <- trainDDLSModel(
  +   object = DDLS,
  +   batch.size = 12,
  +   num.epochs = 5
  + )
  Error: There is no a Python interpreter with all the digitalDLSorteR 
          dependencies covered available. Please, look at 
          https://diegommcc.github.io/digitalDLSorteR/articles/kerasIssues.html 
          or see ?installPythonDepend
  Execution halted