I am analyzing 4C-seq data with the FourCSeq package. It is an experiment with 1 viewpoint, 2 conditions, and 2 replicates per condition. I have read the FourCSeq documentation and adapted the example code on the vignette to my data. It worked until I encountered the following error when using the getZScores() function:

> fcf.example.u15 <- getZScores(fc.example.u15)
[1] "DMPK_u15"
gene-wise dispersion estimates
mean-dispersion relationship
-- note: fitType='parametric', but the dispersion trend was not well captured by the
   function: y = a/x + b, and a local regression fit was automatically substituted.
   specify fitType='local' or 'mean' to avoid this message next time.
final dispersion estimates
Error in getZScores(fc.example.u15) :
  Failed to estimate the parameters of the Variance stabilizing transformation.

Here is the code I used before getZScores():

library(FourCSeq)

referenceGenomeFile.chr19 = "/Users/gus/Documents/Science/3. PhD/Resources/Sequences/Homo_sapiens.GRCh38.dna.chromosome.19.fa"

bamFilePath.u15example = "/Users/gus/Documents/Science/3. PhD/Experiments/4C/DM1/Data_analysis/FourCSeq/example_u15_bam_files"

primerFile.u15 = "/Users/gus/Documents/Science/3. PhD/Experiments/4C/DM1/Data_analysis/FourCSeq/DMPK_u15_primer_file.fa"

metadata.example.u15 <- list(projectPath = "example_u15", 
                             fragmentDir = "example_u15_re_fragments", 
                             referenceGenomeFile = referenceGenomeFile.chr19, 
                             reSequence1 = "GATC", 
                             reSequence2 = "CTAG", 
                             primerFile = primerFile.u15, 
                             bamFilePath = bamFilePath.u15example)

colData.example.u15 <- DataFrame(viewpoint = "DMPK_u15", 
                                 condition = factor(rep(c("GM04604", "GM06077"), each=2), 
                                                    levels = c("GM04604", "GM06077")), 
                                 replicate = rep(c(2, 3), 2), 
                                 bamFile = c("DM1_2_pool_3_DMPK_u15_GM04604_filtered.bam", 
                                             "DM1_3_pool_1_DMPK_u15_GM04604_filtered.bam", 
                                             "DM1_2_pool_1_DMPK_u15_GM06077_filtered.bam", 
                                             "DM1_3_pool_2_DMPK_u15_GM06077_filtered.bam"), 
                                 sequencingPrimer = "first")

fc.example.u15 <- FourC(colData.example.u15, metadata.example.u15)

fc.example.u15 <- addFragments(fc.example.u15)

rowRanges(fc.example.u15)

findViewpointFragments(fc.example.u15)

fc.example.u15 <- addViewpointFrags(fc.example.u15)

fc.example.u15 <- countFragmentOverlaps(fc.example.u15, trim = 4, minMapq = 30)

fc.example.u15 <- combineFragEnds(fc.example.u15)

writeTrackFiles(fc.example.u15, format = 'bedGraph')

fc.example.u15 <- smoothCounts(fc.example.u15)

fcf.example.u15 <- getZScores(fc.example.u15)

traceback()
2: stop("Failed to estimate the parameters of the Variance stabilizing transformation.")
1: getZScores(fc.example.u15)

sessionInfo()
R version 3.4.4 (2018-03-15)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib

locale:
[1] C

attached base packages:
 [1] splines   parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] FourCSeq_1.12.0            LSD_4.0-0                  DESeq2_1.18.1              SummarizedExperiment_1.8.1
 [5] DelayedArray_0.4.1         matrixStats_0.53.1         Biobase_2.38.0             ggplot2_2.2.1             
 [9] GenomicRanges_1.30.3       GenomeInfoDb_1.14.0        IRanges_2.12.0             S4Vectors_0.16.0          
[13] BiocGenerics_0.24.0        BiocInstaller_1.28.0      

loaded via a namespace (and not attached):
 [1] ProtGenerics_1.10.0           bitops_1.0-6                  bit64_0.9-7                  
 [4] RColorBrewer_1.1-2            progress_1.1.2                httr_1.3.1                   
 [7] tools_3.4.4                   backports_1.1.2               R6_2.2.2                     
[10] rpart_4.1-13                  Hmisc_4.1-1                   DBI_0.8                      
[13] lazyeval_0.2.1                colorspace_1.3-2              nnet_7.3-12                  
[16] gridExtra_2.3                 prettyunits_1.0.2             GGally_1.3.2                 
[19] RMySQL_0.10.14                curl_3.2                      bit_1.1-12                   
[22] compiler_3.4.4                graph_1.56.0                  htmlTable_1.11.2             
[25] rtracklayer_1.38.3            ggbio_1.26.1                  scales_0.5.0                 
[28] checkmate_1.8.5               genefilter_1.60.0             RBGL_1.54.0                  
[31] stringr_1.3.0                 digest_0.6.15                 Rsamtools_1.30.0             
[34] foreign_0.8-69                XVector_0.18.0                base64enc_0.1-3              
[37] dichromat_2.0-0               htmltools_0.3.6               ensembldb_2.2.2              
[40] BSgenome_1.46.0               htmlwidgets_1.0               rlang_0.2.0                  
[43] rstudioapi_0.7                RSQLite_2.1.0                 shiny_1.0.5                  
[46] gtools_3.5.0                  BiocParallel_1.12.0           acepack_1.4.1                
[49] VariantAnnotation_1.24.5      RCurl_1.95-4.10               magrittr_1.5                 
[52] GenomeInfoDbData_1.0.0        Formula_1.2-2                 Matrix_1.2-14                
[55] Rcpp_0.12.16                  munsell_0.4.3                 stringi_1.1.7                
[58] yaml_2.1.18                   zlibbioc_1.24.0               plyr_1.8.4                   
[61] AnnotationHub_2.10.1          grid_3.4.4                    blob_1.1.1                   
[64] lattice_0.20-35               Biostrings_2.46.0             GenomicFeatures_1.30.3       
[67] annotate_1.56.2               locfit_1.5-9.1                knitr_1.20                   
[70] pillar_1.2.1                  fda_2.4.7                     geneplotter_1.56.0           
[73] reshape2_1.4.3                biomaRt_2.34.2                XML_3.98-1.10                
[76] biovizBase_1.26.0             latticeExtra_0.6-28           data.table_1.10.4-3          
[79] httpuv_1.3.6.2                gtable_0.2.0                  reshape_0.8.7                
[82] assertthat_0.2.0              mime_0.5                      xtable_1.8-2                 
[85] AnnotationFilter_1.2.0        survival_2.41-3               OrganismDbi_1.20.0           
[88] tibble_1.4.2                  GenomicAlignments_1.14.2      AnnotationDbi_1.40.0         
[91] memoise_1.1.0                 cluster_2.0.7-1               interactiveDisplayBase_1.16.0

Upon searching for similar questions, I found fourCseq - error getZscores. However, there doesn't seem to be a clear answer to this question. Nonetheless, I tried changing to fcf.example.u15 <- getZScores(fc.example.u15, minCount = 10), but it still didn't work.

I would greatly appreciate any suggestions/fixes for this.

Cheers,

Gustavo