Hi all, I got this error using the Aspli package. I cannot seem to fix it. Worked before. All packages updated and still fails. Thanks!

#RNA-seq BAM files
flsall <- dir(getwd(),".bam")
flsall<-paste0(getwd(),'/',flsall)
names(flsall)<-gsub('.bam','',dir(getwd(),".bam"))
BAMFiles <- flsall
#RNA-seq GTF file
flsgtf <- dir(getwd(),".gtf")
genomeTxDb <- makeTxDbFromGFF(file = flsgtf)
features <- binGenome(genomeTxDb)
#Combine BAM and target files
targets <- data.frame(row.names = paste0('Sample',c(1:9)),
bam = BAMFiles[1:9],
f1 = c( 'treatment','control','treatment','treatment','treatment','treatment','control','control','control'),
stringsAsFactors = FALSE)
mBAMs <- data.frame( bam = sub("_[012]","",targets$bam[c(1,4)]),
condition = c("control","treatment"))
#Read counting
gbcounts <- gbCounts(features=features, targets=targets,
minReadLength = 295, maxISize = 50000, libType="PE")
#Junction-based de-novo counting
asd <- jCounts(counts=gbcounts, features=features, minReadLength=295, libType="PE")
#Differential gene expression
gb <- gbDUreport(gbcounts, contrast = c(-1,1))
#Differential junction usage
jdur <- jDUreport(asd, contrast=c(-1,1), strongFilter=TRUE, useSubset = FALSE)

library(ASpli)
library(GenomicFeatures)
#Differential junction usage
jdur <- jDUreport(asd, contrast=c(-1,1), strongFilter=TRUE, useSubset = FALSE)
Running junctionsPJU test
Running junctionsPIR test
Error in xj[i] : invalid subscript type 'list'
sessionInfo()
R version 4.3.3 (2024-02-29 ucrt)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19045)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.utf8 LC_CTYPE=English_United States.utf8 LC_MONETARY=English_United States.utf8
[4] LC_NUMERIC=C LC_TIME=English_United States.utf8

time zone: America/Los_Angeles
tzcode source: internal

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

other attached packages:
[1] BiocManager_1.30.22 GenomicFeatures_1.54.4 GenomicRanges_1.54.1 GenomeInfoDb_1.38.8 ASpli_2.12.0
[6] AnnotationDbi_1.64.1 IRanges_2.36.0 S4Vectors_0.40.2 Biobase_2.60.0 BiocGenerics_0.48.1
[11] edgeR_4.0.16 limma_3.58.1

loaded via a namespace (and not attached):
[1] RColorBrewer_1.1-3 rstudioapi_0.16.0 magrittr_2.0.3 rmarkdown_2.26
[5] BiocIO_1.12.0 zlibbioc_1.48.2 vctrs_0.6.5 memoise_2.0.1
[9] Rsamtools_2.18.0 RCurl_1.98-1.14 base64enc_0.1-3 htmltools_0.5.8
[13] S4Arrays_1.2.1 progress_1.2.3 curl_5.2.1 SparseArray_1.2.4
[17] Formula_1.2-5 htmlwidgets_1.6.4 plyr_1.8.9 Gviz_1.46.1
[21] cachem_1.0.8 GenomicAlignments_1.38.2 igraph_2.0.3 lifecycle_1.0.4
[25] pkgconfig_2.0.3 Matrix_1.6-5 R6_2.5.1 fastmap_1.1.1
[29] GenomeInfoDbData_1.2.11 MatrixGenerics_1.14.0 digest_0.6.35 colorspace_2.1-0
[33] Hmisc_5.1-2 RSQLite_2.3.5 filelock_1.0.3 fansi_1.0.6
[37] httr_1.4.7 abind_1.4-5 compiler_4.3.3 bit64_4.0.5
[41] htmlTable_2.4.2 backports_1.4.1 BiocParallel_1.34.2 DBI_1.2.2
[45] UpSetR_1.4.0 biomaRt_2.58.2 MASS_7.3-60.0.1 rappdirs_0.3.3
[49] DelayedArray_0.28.0 rjson_0.2.21 tools_4.3.3 foreign_0.8-86
[53] nnet_7.3-19 glue_1.7.0 restfulr_0.0.15 grid_4.3.3
[57] checkmate_2.3.1 cluster_2.1.6 generics_0.1.3 gtable_0.3.5
[61] BSgenome_1.70.2 tidyr_1.3.1 ensembldb_2.26.0 data.table_1.15.2
[65] hms_1.1.3 xml2_1.3.6 utf8_1.2.4 XVector_0.42.0
[69] pillar_1.9.0 stringr_1.5.1 splines_4.3.3 dplyr_1.1.4
[73] BiocFileCache_2.10.2 lattice_0.22-6 deldir_2.0-4 rtracklayer_1.62.0
[77] bit_4.0.5 biovizBase_1.50.0 tidyselect_1.2.1 locfit_1.5-9.9
[81] Biostrings_2.70.3 knitr_1.46 gridExtra_2.3 ProtGenerics_1.34.0
[85] SummarizedExperiment_1.32.0 xfun_0.43 statmod_1.5.0 matrixStats_1.2.0
[89] DT_0.33 stringi_1.8.3 lazyeval_0.2.2 yaml_2.3.8
[93] evaluate_0.23 codetools_0.2-19 interp_1.1-6 tibble_3.2.1
[97] cli_3.6.2 rpart_4.1.23 pbmcapply_1.5.1 munsell_0.5.1
[101] dichromat_2.0-0.1 Rcpp_1.0.12 dbplyr_2.5.0 png_0.1-8
[105] XML_3.99-0.16.1 ggplot2_3.5.1 blob_1.2.4 prettyunits_1.2.0
[109] jpeg_0.1-10 latticeExtra_0.6-30 AnnotationFilter_1.26.0 bitops_1.0-7
[113] VariantAnnotation_1.48.1 scales_1.3.0 purrr_1.0.2 crayon_1.5.2
[117] BiocStyle_2.30.0 rlang_1.1.3 KEGGREST_1.42.0

traceback()
6: [.data.frame(J3, reliables, )
5: J3[reliables, ]
4: .makeJunctions(data, targets, start_J1, start_J2, start_J3, minAvgCounts,
filterWithContrasted, contrast, strongFilter)
3: .junctionDUreportExt(asd, minAvgCounts, contrast, filterWithContrasted,
runUniformityTest, mergedBams, maxPValForUniformityCheck,
strongFilter, maxConditionsForDispersionEstimate, formula,
coef, maxFDRForParticipation, useSubset)
2: jDUreport(asd, contrast = c(-1, 1), strongFilter = TRUE, useSubset = FALSE)
1: jDUreport(asd, contrast = c(-1, 1), strongFilter = TRUE, useSubset = FALSE)