Hi,

When I tried to read the rsem results into ballgown using ballgownrsem function, I encountered the following error:

> bg <- ballgownrsem(
    dir = data_dir,
    samples = samples,
    gtf = gtf,
    pData = pheno_data,
    meas = 'TPM'
)

Thu Dec 19 16:27:50 2019
Thu Dec 19 16:27:52 2019: reading annotation
Thu Dec 19 16:33:51 2019: handling exons
Thu Dec 19 16:34:23 2019: handling introns
Error in .Call2("solve_user_SEW0", start, end, width, PACKAGE = "IRanges") : 
  solving row 6: negative widths are not allowed
Calls: ballgownrsem ... GRanges -> new_GRanges -> IRanges -> solveUserSEW0 -> .Call2
Execution halted

From the message, it seems that IRanges can't read the minus strand record as it is. The only way to solve this problem is to invert the minus strand records?

NOTE: I downloaded the gtf file from the url below. https://www.gencodegenes.org/human/

SessionInfo:

R version 3.5.1 (2018-07-02)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.5 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.6.0
LAPACK: /usr/lib/lapack/liblapack.so.3.6.0

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

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

other attached packages:
[1] readr_1.3.1       dplyr_0.8.3       genefilter_1.64.0 ballgown_2.14.1  
[5] docopt_0.6.1     

loaded via a namespace (and not attached):
 [1] SummarizedExperiment_1.12.0 tidyselect_0.2.5           
 [3] purrr_0.3.2                 splines_3.5.1              
 [5] lattice_0.20-38             vctrs_0.2.0                
 [7] stats4_3.5.1                rtracklayer_1.42.2         
 [9] mgcv_1.8-28                 blob_1.2.0                 
[11] XML_3.98-1.20               survival_2.44-1.1          
[13] rlang_0.4.0                 pillar_1.4.2               
[15] glue_1.3.1                  DBI_1.0.0                  
[17] BiocParallel_1.16.6         BiocGenerics_0.28.0        
[19] bit64_0.9-7                 RColorBrewer_1.1-2         
[21] matrixStats_0.54.0          GenomeInfoDbData_1.2.0     
[23] sva_3.30.1                  zlibbioc_1.28.0            
[25] Biostrings_2.50.2           memoise_1.1.0              
[27] Biobase_2.42.0              IRanges_2.16.0             
[29] GenomeInfoDb_1.18.2         parallel_3.5.1             
[31] AnnotationDbi_1.44.0        Rcpp_1.0.2                 
[33] xtable_1.8-4                backports_1.1.4            
[35] limma_3.38.3                DelayedArray_0.8.0         
[37] S4Vectors_0.20.1            annotate_1.60.1            
[39] XVector_0.22.0              bit_1.1-14                 
[41] Rsamtools_1.34.1            hms_0.5.1                  
[43] digest_0.6.20               GenomicRanges_1.34.0       
[45] grid_3.5.1                  tools_3.5.1                
[47] bitops_1.0-6                magrittr_1.5               
[49] RCurl_1.95-4.12             RSQLite_2.1.2              
[51] tibble_2.1.3                crayon_1.3.4               
[53] pkgconfig_2.0.2             zeallot_0.1.0              
[55] Matrix_1.2-17               assertthat_0.2.1           
[57] R6_2.4.0                    GenomicAlignments_1.18.1   
[59] nlme_3.1-141                compiler_3.5.1    

Thanks!