An introduction to the bambu package using NanoporeRNASeq data
Introduction
NanoporeRNASeq contains RNA-Seq data from the K562 and MCF7 cell lines that were generated by the SG-NEx project (https://github.com/GoekeLab/sg-nex-data). Each of these cell line has three replicates, with 1 direct RNA sequencing data and 2 cDNA sequencing data. The files contains reads aligned to the human genome (Grch38) chromosome 22 (1:25500000).
Accessing NanoporeRNASeq data
List the samples
data("SGNexSamples")
SGNexSamples
##> DataFrame with 6 rows and 6 columns
##> sample_id Platform cellLine protocol cancer_type
##> <character> <character> <character> <character> <character>
##> 1 K562_directcDNA_repl.. MinION K562 directcDNA Leukocyte
##> 2 K562_directcDNA_repl.. GridION K562 directcDNA Leukocyte
##> 3 K562_directRNA_repli.. GridION K562 directRNA Leukocyte
##> 4 MCF7_directcDNA_repl.. MinION MCF7 directcDNA Breast
##> 5 MCF7_directcDNA_repl.. GridION MCF7 directcDNA Breast
##> 6 MCF7_directRNA_repli.. GridION MCF7 directRNA Breast
##> fileNames
##> <character>
##> 1 NanoporeRNASeq/versi..
##> 2 NanoporeRNASeq/versi..
##> 3 NanoporeRNASeq/versi..
##> 4 NanoporeRNASeq/versi..
##> 5 NanoporeRNASeq/versi..
##> 6 NanoporeRNASeq/versi..List the available BamFile
Get the annotation GRangesList
data("HsChr22BambuAnnotation")
HsChr22BambuAnnotation
##> GRangesList object of length 1500:
##> $ENST00000043402
##> GRanges object with 2 ranges and 2 metadata columns:
##> seqnames ranges strand | exon_rank exon_endRank
##> <Rle> <IRanges> <Rle> | <integer> <integer>
##> [1] 22 20241415-20243110 - | 2 1
##> [2] 22 20268071-20268531 - | 1 2
##> -------
##> seqinfo: 1 sequence from an unspecified genome; no seqlengths
##>
##> $ENST00000086933
##> GRanges object with 3 ranges and 2 metadata columns:
##> seqnames ranges strand | exon_rank exon_endRank
##> <Rle> <IRanges> <Rle> | <integer> <integer>
##> [1] 22 19148576-19149095 - | 3 1
##> [2] 22 19149663-19149916 - | 2 2
##> [3] 22 19150025-19150283 - | 1 3
##> -------
##> seqinfo: 1 sequence from an unspecified genome; no seqlengths
##>
##> $ENST00000155674
##> GRanges object with 8 ranges and 2 metadata columns:
##> seqnames ranges strand | exon_rank exon_endRank
##> <Rle> <IRanges> <Rle> | <integer> <integer>
##> [1] 22 17137511-17138357 - | 8 1
##> [2] 22 17138550-17138738 - | 7 2
##> [3] 22 17141059-17141233 - | 6 3
##> [4] 22 17143098-17143131 - | 5 4
##> [5] 22 17145024-17145117 - | 4 5
##> [6] 22 17148448-17148560 - | 3 6
##> [7] 22 17149542-17149745 - | 2 7
##> [8] 22 17165209-17165287 - | 1 8
##> -------
##> seqinfo: 1 sequence from an unspecified genome; no seqlengths
##>
##> ...
##> <1497 more elements>Visualizing gene of interest from a single bam file
We can visualize the one sample for a single gene ENST00000215832 (MAPK1)
library(ggbio)
range <- HsChr22BambuAnnotation$ENST00000215832
# plot mismatch track
library(BSgenome.Hsapiens.NCBI.GRCh38)
# plot annotation track
tx <- autoplot(range, aes(col = strand), group.selfish = TRUE)
# plot coverage track
coverage <- autoplot(bamFiles[[1]], aes(col = coverage), which = range)
# merge the tracks into one plot
tracks(annotation = tx, coverage = coverage, heights = c(1, 3)) + theme_minimal()
Running Bambu with NanoporeRNASeq data
Load the bambu package
Run bambu
Applying bambu to bamFiles
bambu returns a SummarizedExperiment object
se
##> class: RangedSummarizedExperiment
##> dim: 1542 6
##> metadata(2): incompatibleCounts warnings
##> assays(4): counts CPM fullLengthCounts uniqueCounts
##> rownames(1542): BambuTx1 BambuTx2 ... ENST00000641933 ENST00000641967
##> rowData names(11): TXNAME GENEID ... txid eqClassById
##> colnames(6): 1a035ced45be_3844 1a03651cbab7_3846 ... 1a035efe117c_3852
##> 1a03567a480b_3854
##> colData names(1): nameVisualizing gene examples
We can visualize the annotated and novel isoforms identified in this gene example using plot functions from bambu
##> [[1]]
##> TableGrob (4 x 1) "arrange": 4 grobs
##> z cells name grob
##> 1 1 (2-2,1-1) arrange gtable[layout]
##> 2 2 (3-3,1-1) arrange gtable[layout]
##> 3 3 (4-4,1-1) arrange gtable[layout]
##> 4 4 (1-1,1-1) arrange text[GRID.text.285]sessionInfo()
##> R version 4.6.1 (2026-06-24)
##> Platform: x86_64-pc-linux-gnu
##> Running under: Ubuntu 26.04.1 LTS
##>
##> Matrix products: default
##> BLAS: /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3
##> LAPACK: /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblasp-r0.3.32.so; LAPACK version 3.12.0
##>
##> 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
##>
##> time zone: Etc/UTC
##> tzcode source: system (glibc)
##>
##> attached base packages:
##> [1] stats4 stats graphics grDevices utils datasets methods
##> [8] base
##>
##> other attached packages:
##> [1] bambu_3.14.0
##> [2] SummarizedExperiment_1.42.0
##> [3] Biobase_2.72.0
##> [4] MatrixGenerics_1.24.0
##> [5] matrixStats_1.5.0
##> [6] BSgenome.Hsapiens.NCBI.GRCh38_1.3.1000
##> [7] BSgenome_1.80.0
##> [8] rtracklayer_1.72.0
##> [9] BiocIO_1.22.0
##> [10] ggbio_1.60.0
##> [11] ggplot2_4.0.3
##> [12] Rsamtools_2.28.0
##> [13] Biostrings_2.80.2
##> [14] XVector_0.52.0
##> [15] GenomicRanges_1.64.0
##> [16] IRanges_2.46.0
##> [17] S4Vectors_0.50.3
##> [18] Seqinfo_1.2.0
##> [19] NanoporeRNASeq_1.22.0
##> [20] ExperimentHub_3.2.2
##> [21] AnnotationHub_4.2.2
##> [22] BiocFileCache_3.2.0
##> [23] dbplyr_2.6.0
##> [24] BiocGenerics_0.58.1
##> [25] generics_0.1.4
##> [26] rmarkdown_2.32
##>
##> loaded via a namespace (and not attached):
##> [1] DBI_1.3.0 bitops_1.1-0 RBGL_1.88.0
##> [4] gridExtra_2.3.1 httr2_1.3.0 formatR_1.14
##> [7] rlang_1.3.0 magrittr_2.0.5 biovizBase_1.60.0
##> [10] compiler_4.6.1 RSQLite_3.53.3 GenomicFeatures_1.64.0
##> [13] png_0.1-9 vctrs_0.7.3 reshape2_1.4.5
##> [16] ProtGenerics_1.44.0 stringr_1.6.0 pkgconfig_2.0.3
##> [19] crayon_1.5.3 fastmap_1.2.0 backports_1.5.1
##> [22] labeling_0.4.3 graph_1.90.0 UCSC.utils_1.8.0
##> [25] purrr_1.2.2 bit_4.6.0 xfun_0.61
##> [28] cachem_1.1.0 cigarillo_1.2.1 GenomeInfoDb_1.48.0
##> [31] jsonlite_2.0.0 blob_1.3.0 DelayedArray_0.38.2
##> [34] BiocParallel_1.46.0 parallel_4.6.1 cluster_2.1.8.3
##> [37] VariantAnnotation_1.58.0 R6_2.6.1 bslib_0.12.0
##> [40] stringi_1.8.9 RColorBrewer_1.1-3 rpart_4.1.27
##> [43] xgboost_3.2.1.1 jquerylib_0.1.4 Rcpp_1.1.2
##> [46] knitr_1.52 base64enc_0.1-6 Matrix_1.7-6
##> [49] nnet_7.3-21 tidyselect_1.2.1 rstudioapi_0.19.0
##> [52] dichromat_2.0-1 abind_1.4-8 yaml_2.3.12
##> [55] codetools_0.2-20 curl_8.0.0 lattice_0.23-1
##> [58] tibble_3.3.1 plyr_1.8.9 withr_3.0.3
##> [61] KEGGREST_1.52.2 S7_0.2.2 evaluate_1.0.5
##> [64] foreign_0.8-91 pillar_1.11.1 BiocManager_1.30.27
##> [67] filelock_1.0.3 checkmate_2.3.4 OrganismDbi_1.54.0
##> [70] RCurl_1.98-1.20 ensembldb_2.36.1 BiocVersion_3.23.1
##> [73] scales_1.4.0 glue_1.8.1 lazyeval_0.2.3
##> [76] Hmisc_5.3-0 maketools_1.3.2 tools_4.6.1
##> [79] sys_3.4.3 data.table_1.18.6.1 GenomicAlignments_1.48.0
##> [82] XML_3.99-0.25 buildtools_1.0.0 grid_4.6.1
##> [85] tidyr_1.3.2 AnnotationDbi_1.74.0 colorspace_2.1-4
##> [88] restfulr_0.0.17 htmlTable_2.5.0 Formula_1.2-6
##> [91] cli_3.6.6 rappdirs_0.3.4 S4Arrays_1.12.1
##> [94] dplyr_1.2.1 AnnotationFilter_1.36.0 gtable_0.3.6
##> [97] sass_0.4.10 digest_0.6.39 SparseArray_1.12.3
##> [100] rjson_0.2.23 htmlwidgets_1.6.4 farver_2.1.2
##> [103] memoise_2.0.1 htmltools_0.5.9 lifecycle_1.0.5
##> [106] httr_1.4.9 bit64_4.8.6