Hello, i am trying to do motif discovery in a ChIPseq dataset. I am using the rGADEM package to do de novo motif discovery, but the GADEM() function returns an error. My data consists of 576 regions which I have in bed format and convert to GRanges via makeGRangeFromDataFrame(). To provide an example, I shortened my dataframe to 20 regions and the error remains. Any suggestions on how to solve this?

data

   seqnames     start       end
1      chr6  29723590  29723790
2     chr14 103334312 103334512
3      chr1 150579030 150579230
4      chr7  76358527  76358727
5      chr6  11537891  11538091
6     chr14  49893256  49893456
7      chr5 179623200 179623400
8      chr1 228082831 228083031
9     chr12  93441644  93441844
10    chr10   3784776   3784976
11     chr3 183635833 183636033
12     chr7    975301    975501
13    chr12 123364510 123364710
14     chr1   1615578   1615778
15     chr1  36156320  36156520
16    chr14  55051781  55051981
17     chr8  11867697  11867897
18    chr22  38706135  38706335
19     chr6  44265256  44265456
20     chr1 185316658 185316858

The code I use

library(GenomicRanges)
library(IRanges)

dataRange <- makeGRangesFromDataFrame(data)

#merge nearby peaks
dataRange <- reduce(dataRange)

# expand the peaks
dataRange_resized = resize(dataRange, width = 50, fix='center')

library(rGADEM)
library(BSgenome.Hsapiens.UCSC.hg38)
novel_motifs <- GADEM(dataRange_resized, seed = 2, nmotifs = 10, genome = Hsapiens)

Error in .Call2("C_solve_user_SEW", refwidths, start, end, width, translate.negative.coord,  : 
  solving row 4: 'allow.nonnarrowing' is FALSE and the supplied start (185316733) is > refwidth + 1

sessionInfo( )

``` R version 4.1.3 (2022-03-10) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 19042)

Matrix products: default

locale: [1] LC_COLLATE=Dutch_Netherlands.1252 LC_CTYPE=Dutch_Netherlands.1252 LC_MONETARY=Dutch_Netherlands.1252 [4] LC_NUMERIC=C LC_TIME=Dutch_Netherlands.1252

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

other attached packages: [1] BSgenome.Hsapiens.UCSC.hg38_1.4.4 rGADEM_2.42.0 seqLogo_1.60.0
[4] BSgenome_1.62.0 rtracklayer_1.54.0 Biostrings_2.62.0
[7] XVector_0.34.0 GenomicRanges_1.46.1 GenomeInfoDb_1.30.1
[10] IRanges_2.28.0 S4Vectors_0.32.4 BiocGenerics_0.40.0

loaded via a namespace (and not attached): [1] pillar_1.8.1 compiler_4.1.3 restfulr_0.0.15 BiocManager_1.30.18
[5] MatrixGenerics_1.6.0 bitops_1.0-7 tools_4.1.3 zlibbioc_1.40.0
[9] tibble_3.1.8 lifecycle_1.0.1 lattice_0.20-45 pkgconfig_2.0.3
[13] rlang_1.0.4 Matrix_1.5-1 DBI_1.1.3 DelayedArray_0.20.0
[17] cli_3.4.1 rstudioapi_0.14 yaml_2.3.5 parallel_4.1.3
[21] GenomeInfoDbData_1.2.7 dplyr_1.0.9 generics_0.1.3 vctrs_0.4.1
[25] tidyselect_1.1.2 glue_1.6.2 Biobase_2.54.0 R6_2.5.1
[29] fansi_1.0.3 XML_3.99-0.10 BiocParallel_1.28.3 purrr_0.3.4
[33] magrittr_2.0.3 Rsamtools_2.10.0 matrixStats_0.62.0 GenomicAlignments_1.30.0
[37] assertthat_0.2.1 SummarizedExperiment_1.24.0 utf8_1.2.2 RCurl_1.98-1.8
[41] crayon_1.5.2 rjson_0.2.21 BiocIO_1.4.0