lgeistlinger
commented
10 months ago It seems that none of your CNV regions harbors:
1) calls from samples representing more than one CN state, and
2) calls from at least min.samples samples that deviate from the 2n diploid state
You might want to check the output of the following commands:
library(CNVRanger)
multi.calls <- CNVRanger:::.largest
calls <- as(grl, "RaggedExperiment")
cnv.states <- RaggedExperiment::qreduceAssay(calls, query = sel.cnvrs, simplifyReduce = multi.calls, background = 2)
tab <- apply(cnv.states, 1, table)tab then lists for each CNV region how many samples are present in which CN state.
You then want to check:
isTestable <- function(states)
{
cond1 <- length(states) > 1
cond2 <- any(states[names(states) != "2"] >= min.samples)
cond1 && cond2
}
ind <- vapply(tab, isTestable, logical(1))
table(ind)and the result of table(ind) will presumably show that none of the regions satisfies the conditions outlined above.
renatoliguori88
Hi everyone, I'm pretty new to CNV ranger, however I was able to follow the vignette for most of the steps until the chapter 7 (CNV-expression association analysis).
I tried many times with my data but was always facing the same error:
I also tried to create a subset for testing since my dataset is pretty huge, restricting the analysis to chromosome 1 and 2 with the command:
and also reducing the number of min.samples when running the command:
res <- cnvEQTL(sel.cnvrs, grl, rse, window = "1Mbp", verbose = TRUE, min.samples = 2)Just for better understanding i will print here my objects that i put inside the cnvEQTL function:
<23 more elements> ``` > rse ``` class: RangedSummarizedExperiment dim: 2963 24 metadata(0): assays(1): rcounts rownames(2963): ENSMUSG00000051951 ENSMUSG00000025900 ... ENSMUSG00000038628 ENSMUSG00000098505 rowData names(0): colnames(24): KPC438 KPC479B ... KPCZ532 KPCZ746 colData names(0): ``` However the result never changed and I'm always getting the same error. Before sharing any data i would like to know if any of you ever got the same error as me Thank you so much in advance Sessioninfo: ``` R version 4.3.1 (2023-06-16) Platform: x86_64-conda-linux-gnu (64-bit) Running under: Ubuntu 20.04.6 LTS Matrix products: default BLAS/LAPACK: /data/research/restools/miniconda/envs/R.4.3.1/lib/libopenblasp-r0.3.24.so; LAPACK version 3.11.0 locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C 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 LC_PAPER=en_US.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C time zone: Etc/UTC tzcode source: system (glibc) attached base packages: [1] grid stats4 stats graphics grDevices utils datasets methods base other attached packages: [1] ComplexHeatmap_2.16.0 EnsDb.Mmusculus.v79_2.99.0 ensembldb_2.24.1 [4] AnnotationFilter_1.24.0 GenomicFeatures_1.52.2 AnnotationDbi_1.62.2 [7] Gviz_1.44.2 SummarizedExperiment_1.30.2 Biobase_2.60.0 [10] MatrixGenerics_1.12.3 matrixStats_1.0.0 BSgenome.Mmusculus.UCSC.mm10_1.4.3 [13] BSgenome_1.68.0 rtracklayer_1.60.1 Biostrings_2.68.1 [16] XVector_0.40.0 regioneR_1.32.0 AnnotationHub_3.8.0 [19] BiocFileCache_2.8.0 dbplyr_2.3.4 tibble_3.2.1 [22] CNVRanger_1.16.5 RaggedExperiment_1.24.2 GenomicRanges_1.52.1 [25] GenomeInfoDb_1.36.4 IRanges_2.34.1 S4Vectors_0.38.2 [28] BiocGenerics_0.46.0 loaded via a namespace (and not attached): [1] RColorBrewer_1.1-3 shape_1.4.6 rstudioapi_0.15.0 magrittr_2.0.3 [5] rmarkdown_2.25 GlobalOptions_0.1.2 BiocIO_1.10.0 zlibbioc_1.46.0 [9] vctrs_0.6.4 memoise_2.0.1 Rsamtools_2.16.0 RCurl_1.98-1.12 [13] base64enc_0.1-3 htmltools_0.5.6.1 S4Arrays_1.0.6 progress_1.2.2 [17] curl_5.1.0 Formula_1.2-5 htmlwidgets_1.6.2 cachem_1.0.8 [21] GenomicAlignments_1.36.0 iterators_1.0.14 mime_0.12 lifecycle_1.0.3 [25] pkgconfig_2.0.3 Matrix_1.6-1.1 R6_2.5.1 fastmap_1.1.1 [29] clue_0.3-65 GenomeInfoDbData_1.2.10 shiny_1.7.5.1 digest_0.6.33 [33] colorspace_2.1-0 Hmisc_5.1-1 RSQLite_2.3.1 filelock_1.0.2 [37] fansi_1.0.5 httr_1.4.7 abind_1.4-5 compiler_4.3.1 [41] doParallel_1.0.17 bit64_4.0.5 htmlTable_2.4.1 backports_1.4.1 [45] BiocParallel_1.34.2 DBI_1.1.3 biomaRt_2.56.1 rappdirs_0.3.3 [49] DelayedArray_0.26.7 rjson_0.2.21 tools_4.3.1 foreign_0.8-85 [53] interactiveDisplayBase_1.38.0 httpuv_1.6.12 nnet_7.3-19 glue_1.6.2 [57] restfulr_0.0.15 promises_1.2.1 checkmate_2.2.0 cluster_2.1.4 [61] generics_0.1.3 gtable_0.3.4 data.table_1.14.8 hms_1.1.3 [65] xml2_1.3.5 utf8_1.2.4 foreach_1.5.2 BiocVersion_3.17.1 [69] pillar_1.9.0 stringr_1.5.0 limma_3.56.2 later_1.3.1 [73] circlize_0.4.15 dplyr_1.1.3 lattice_0.22-5 deldir_1.0-9 [77] bit_4.0.5 biovizBase_1.48.0 tidyselect_1.2.0 locfit_1.5-9.8 [81] knitr_1.44 gridExtra_2.3 ProtGenerics_1.32.0 edgeR_3.42.4 [85] xfun_0.40 stringi_1.7.12 lazyeval_0.2.2 yaml_2.3.7 [89] evaluate_0.22 codetools_0.2-19 interp_1.1-4 BiocManager_1.30.22 [93] cli_3.6.1 rpart_4.1.21 xtable_1.8-4 munsell_0.5.0 [97] dichromat_2.0-0.1 Rcpp_1.0.11 png_0.1-8 XML_3.99-0.14 [101] parallel_4.3.1 ellipsis_0.3.2 ggplot2_3.4.4 blob_1.2.4 [105] prettyunits_1.2.0 jpeg_0.1-10 latticeExtra_0.6-30 bitops_1.0-7 [109] VariantAnnotation_1.46.0 scales_1.2.1 crayon_1.5.2 GetoptLong_1.0.5 [113] rlang_1.1.1 KEGGREST_1.40.1 ```