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Maize run in seqArchRplus
Hi Sarvesh,
to compare Maize to Barley we wanted to test also CAGE data from Maize through seqArchR. But I have come to a problem.
- The "seqArchR::viz_seqs_acgt_mat()" comes out with error and no heatmap is created:
> seqArchR::viz_seqs_acgt_mat(as.character(promoter_seqs_Maize),
+ pos_lab = positionsMaize, save_fname = NULL)
Warning message:
In .seqs_to_mat(seqs = seqs, pos_lab = pos_lab) :
NAs introduced by coercion
The promoter_seqs_Maize is DNAstringSet, created from this fasta file:
Maize_promoters.zip
promoter_seqs_Maize <- readDNAStringSet("/home/pavlu/R/SeqArchR_project/befiles/Maize_promoters.fa", format="fasta",
nrec=-1L, skip=0L, seek.first.rec=FALSE, use.names=TRUE)
> positionsMaize
[1] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34
[35] 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68
[69] 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100
This does not compromise the seqArchR run overall, and we were able to use seqArchRplus...
- but there are again errors during the final output creation, first in the "seqArchRplus::seqs_acgt_image()" of course
seqArchRplus::seqs_acgt_image(sname = sn,
seqs = results[[sn]]$rawSeqs,
seqs_ord = unlist(use_clusts),
pos_lab = -50:49, dir_path = use_dir)
! Directory exists: /home/pavlu/R/SeqArchR_project/output/Maize_results
RStudioGD
2
Warning message:
In .seqs_to_mat(seqs = seqs, pos_lab = pos_lab) :
NAs introduced by coercion
- And then, in the creation of BED files for clusters "seqArchRplus::write_seqArchR_cluster_track_bed()"
> seqArchRplus::write_seqArchR_cluster_track_bed(sname = sn,
+ use_q_bound = F,
+ use_as_names = "names",
+ clusts = use_clusts,
+ info_df = info_df,
+ one_zip_all = TRUE,
+ org_name = fname_prefix,
+ dir_path = use_dir,
+ include_in_report = FALSE,
+ strand_sep = FALSE)
ℹ Preparing cluster-wise BED for Maize
! Directory exists: /home/pavlu/R/SeqArchR_project/output/Maize_results
! Directory exists: /home/pavlu/R/SeqArchR_project/output/Maize_results/Cluster_BED_tracks
ℹ Writing cluster BED track files at: /home/pavlu/R/SeqArchR_project/output/Maize_results/Cluster_BED_tracks
Error in ans[npos] <- rep(no, length.out = len)[npos] :
replacement has length zero
In addition: Warning message:
In rep(no, length.out = len) : 'x' is NULL so the result will be NULL
There may be problem in the structure of our starting BED file since the results are not our own and we are missing some of the result columns from CAGEr, seqArchR would want...
Here is our befile used:
Maize_promoters_better.zip
Here is the info_df, maybe that also helps:
info_df <- read.delim(
file = bed_info_fname,
sep = "\t", header = TRUE,
col.names = c(
"chr", "start", "end", "names",
"score", "strand", "IQW"
)
)
Since we were not able to create bedfiles for clusters we were also not able to check the heatmaps of certain motives...
Here is our result, everything else except the parts I mentioned worked. (We don't have TPM values sadly as of now)
Maize_combined.pdf
Here is session info for both, hope you can help:
> sessionInfo()
R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=cs_CZ.UTF-8 LC_NUMERIC=C LC_TIME=cs_CZ.UTF-8 LC_COLLATE=cs_CZ.UTF-8 LC_MONETARY=cs_CZ.UTF-8
[6] LC_MESSAGES=cs_CZ.UTF-8 LC_PAPER=cs_CZ.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=cs_CZ.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] GenomicFeatures_1.48.3 AnnotationDbi_1.58.0 ggpubr_0.4.0 egg_0.4.5
[5] gridExtra_2.3 ggplot2_3.3.6 ChIPseeker_1.32.0 seqArchRplus_0.99.0.4
[9] dplyr_1.0.9 Biostrings_2.64.0 XVector_0.36.0 seqArchR_1.0.0
[13] CAGEr_2.2.0 MultiAssayExperiment_1.22.0 SummarizedExperiment_1.26.1 Biobase_2.56.0
[17] GenomicRanges_1.48.0 GenomeInfoDb_1.32.2 IRanges_2.30.0 S4Vectors_0.34.0
[21] BiocGenerics_0.42.0 MatrixGenerics_1.8.0 matrixStats_0.62.0
loaded via a namespace (and not attached):
[1] backports_1.4.1 shadowtext_0.1.2 fastmatch_1.1-3
[4] VGAM_1.1-6 BiocFileCache_2.4.0 plyr_1.8.7
[7] igraph_1.3.2 lazyeval_0.2.2 splines_4.2.1
[10] operator.tools_1.6.3 BiocParallel_1.30.3 digest_0.6.29
[13] yulab.utils_0.0.4 GOSemSim_2.22.0 viridis_0.6.2
[16] GO.db_3.15.0 fansi_1.0.3 magrittr_2.0.3
[19] memoise_2.0.1 BSgenome_1.64.0 cluster_2.1.3
[22] graphlayouts_0.8.0 formula.tools_1.7.1 enrichplot_1.16.1
[25] prettyunits_1.1.1 colorspace_2.0-3 blob_1.2.3
[28] rappdirs_0.3.3 ggrepel_0.9.1 crayon_1.5.1
[31] RCurl_1.98-1.7 jsonlite_1.8.0 TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2
[34] scatterpie_0.1.7 ape_5.6-2 glue_1.6.2
[37] polyclip_1.10-0 gtable_0.3.0 zlibbioc_1.42.0
[40] DelayedArray_0.22.0 car_3.0-13 abind_1.4-5
[43] scales_1.2.0 DOSE_3.22.0 som_0.3-5.1
[46] DBI_1.1.2 rstatix_0.7.0 Rcpp_1.0.8.3
[49] plotrix_3.8-2 viridisLite_0.4.0 progress_1.2.2
[52] gridGraphics_0.5-1 tidytree_0.3.9 bit_4.0.4
[55] httr_1.4.3 fgsea_1.22.0 gplots_3.1.3
[58] RColorBrewer_1.1-3 ellipsis_0.3.2 factoextra_1.0.7
[61] pkgconfig_2.0.3 XML_3.99-0.10 farver_2.1.0
[64] ggseqlogo_0.1 dbplyr_2.2.0 utf8_1.2.2
[67] labeling_0.4.2 ggplotify_0.1.0 tidyselect_1.1.2
[70] rlang_1.0.2 reshape2_1.4.4 munsell_0.5.0
[73] tools_4.2.1 cachem_1.0.6 cli_3.3.0
[76] generics_0.1.2 RSQLite_2.2.14 broom_0.8.0
[79] stringr_1.4.0 fastmap_1.1.0 yaml_2.3.5
[82] ggtree_3.4.0 bit64_4.0.5 tidygraph_1.2.1
[85] caTools_1.18.2 purrr_0.3.4 dendextend_1.15.2
[88] KEGGREST_1.36.2 ggraph_2.0.5 sparseMatrixStats_1.8.0
[91] nlme_3.1-157 aplot_0.1.6 DO.db_2.9
[94] xml2_1.3.3 biomaRt_2.52.0 compiler_4.2.1
[97] rstudioapi_0.13 filelock_1.0.2 curl_4.3.2
[100] png_0.1-7 ggsignif_0.6.3 treeio_1.20.0
[103] tibble_3.1.7 tweenr_1.0.2 stringi_1.7.6
[106] forcats_0.5.1 lattice_0.20-45 Matrix_1.4-1
[109] permute_0.9-7 vegan_2.6-2 vctrs_0.4.1
[112] stringdist_0.9.8 pillar_1.7.0 lifecycle_1.0.1
[115] data.table_1.14.2 cowplot_1.1.1 bitops_1.0-7
[118] patchwork_1.1.1 rtracklayer_1.56.0 qvalue_2.28.0
[121] R6_2.5.1 BiocIO_1.6.0 KernSmooth_2.23-20
[124] codetools_0.2-18 boot_1.3-28 MASS_7.3-57
[127] gtools_3.9.2.2 assertthat_0.2.1 rjson_0.2.21
[130] withr_2.5.0 GenomicAlignments_1.32.0 Rsamtools_2.12.0
[133] GenomeInfoDbData_1.2.8 mgcv_1.8-40 parallel_4.2.1
[136] hms_1.1.1 grid_4.2.1 ggfun_0.0.6
[139] tidyr_1.2.0 DelayedMatrixStats_1.18.0 carData_3.0-5
[142] ggforce_0.3.3 restfulr_0.0.14
Tasks
- Specify in the help/documentation that output filenames have fixed names
- Go term enrichment for non-model organism
- HTML report generation
- Provide for a way to set all the extensive set of options available for individual wrapper functions.
Annotation issue
Hi Sarvesh,
here is my annotation call:
merged_sample_names <- c("24DAP", "8DAP", "4DAG")
txdb <-makeTxDbFromGFF("/home/pavlu/Dokumenty/references/Hv_Morex.pgsb.Jul2020.gff3", format="gff3")
for(sn in merged_sample_names){
sample_name <- paste0("morex_", sn)
annotations_oneplot_pl[[sn]] <-
seqArchRplus::per_cluster_annotations(
sname = sn,
clusts = use_clusts,
tc_gr = CAGEr::tagClustersGR(cager_obj,
sample = sample_name),
cager_obj = NULL,
qLow = 0.1, qUp = 0.9,
txdb_obj = txdb,
tss_region = c(-500,100),
orgdb_obj = NULL, dir_path = use_dir,
one_plot = TRUE,
txt_size = use_txt_size)
}
"cager_obj" is CAGEexp from our CAGEr analysis
"use_clusts" is created according to your vignette
This works when called for the whole bedfile. But when called for bedfile containing only a certain subset of sequences it does not work as intended. (in the zip, there is "unannot" file which contains all of the sequences and "candidates" which contains just the subset)
BEDs.zip
Here is merged panel for the full bedfile:
4DAG_combined_plots.pdf
Here is merged panel for the subset (obviously the first few clusters should be annotated as intronic, the IQW is the same as the previous panel):
4DAG_combined_plots.pdf
Here is session info:
> sessionInfo()
R version 4.2.0 (2022-04-22)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 20.04.4 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
locale:
[1] LC_CTYPE=cs_CZ.UTF-8 LC_NUMERIC=C LC_TIME=cs_CZ.UTF-8 LC_COLLATE=cs_CZ.UTF-8 LC_MONETARY=cs_CZ.UTF-8
[6] LC_MESSAGES=cs_CZ.UTF-8 LC_PAPER=cs_CZ.UTF-8 LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=cs_CZ.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] cowplot_1.1.1 GenomicFeatures_1.48.0 AnnotationDbi_1.58.0
[4] BSgenome.Hvulgare2.GACR.MorexV3_3.0.0 BSgenome_1.64.0 rtracklayer_1.56.0
[7] ggpubr_0.4.0 egg_0.4.5 gridExtra_2.3
[10] ggplot2_3.3.6 Biostrings_2.64.0 XVector_0.36.0
[13] ChIPseeker_1.32.0 seqArchRplus_0.99.0.3 seqArchR_1.0.0
[16] CAGEr_2.2.0 MultiAssayExperiment_1.22.0 SummarizedExperiment_1.26.1
[19] Biobase_2.56.0 GenomicRanges_1.48.0 GenomeInfoDb_1.32.1
[22] IRanges_2.30.0 S4Vectors_0.34.0 BiocGenerics_0.42.0
[25] MatrixGenerics_1.8.0 matrixStats_0.62.0
loaded via a namespace (and not attached):
[1] utf8_1.2.2 tidyselect_1.1.2 htmlwidgets_1.5.4
[4] RSQLite_2.2.14 grid_4.2.0 BiocParallel_1.30.0
[7] scatterpie_0.1.7 munsell_0.5.0 withr_2.5.0
[10] colorspace_2.0-3 GOSemSim_2.22.0 filelock_1.0.2
[13] rstudioapi_0.13 ggsignif_0.6.3 DOSE_3.22.0
[16] labeling_0.4.2 GenomeInfoDbData_1.2.8 polyclip_1.10-0
[19] bit64_4.0.5 farver_2.1.0 vctrs_0.4.1
[22] treeio_1.20.0 generics_0.1.2 BiocFileCache_2.4.0
[25] ggseqlogo_0.1 R6_2.5.1 graphlayouts_0.8.0
[28] VGAM_1.1-6 locfit_1.5-9.5 heatmaps_1.20.0
[31] bitops_1.0-7 cachem_1.0.6 fgsea_1.22.0
[34] gridGraphics_0.5-1 DelayedArray_0.22.0 assertthat_0.2.1
[37] BiocIO_1.6.0 scales_1.2.0 ggraph_2.0.5
[40] enrichplot_1.16.0 gtable_0.3.0 formula.tools_1.7.1
[43] tidygraph_1.2.1 rlang_1.0.2 splines_4.2.0
[46] rstatix_0.7.0 lazyeval_0.2.2 broom_0.8.0
[49] yaml_2.3.5 reshape2_1.4.4 abind_1.4-5
[52] backports_1.4.1 qvalue_2.28.0 tools_4.2.0
[55] ggplotify_0.1.0 ellipsis_0.3.2 gplots_3.1.3
[58] RColorBrewer_1.1-3 Rcpp_1.0.8.3 plyr_1.8.7
[61] sparseMatrixStats_1.8.0 progress_1.2.2 zlibbioc_1.42.0
[64] purrr_0.3.4 RCurl_1.98-1.6 prettyunits_1.1.1
[67] viridis_0.6.2 ggrepel_0.9.1 cluster_2.1.3
[70] factoextra_1.0.7 magrittr_2.0.3 data.table_1.14.2
[73] DO.db_2.9 fftwtools_0.9-11 hms_1.1.1
[76] patchwork_1.1.1 XML_3.99-0.9 jpeg_0.1-9
[79] compiler_4.2.0 biomaRt_2.52.0 tibble_3.1.7
[82] KernSmooth_2.23-20 crayon_1.5.1 shadowtext_0.1.2
[85] htmltools_0.5.2 tiff_0.1-11 ggfun_0.0.6
[88] mgcv_1.8-40 tidyr_1.2.0 aplot_0.1.4
[91] DBI_1.1.2 tweenr_1.0.2 dbplyr_2.1.1
[94] MASS_7.3-57 rappdirs_0.3.3 boot_1.3-28
[97] som_0.3-5.1 Matrix_1.4-1 car_3.0-13
[100] permute_0.9-7 cli_3.3.0 parallel_4.2.0
[103] igraph_1.3.1 forcats_0.5.1 pkgconfig_2.0.3
[106] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 GenomicAlignments_1.32.0 xml2_1.3.3
[109] ggtree_3.4.0 stringdist_0.9.8 yulab.utils_0.0.4
[112] stringr_1.4.0 digest_0.6.29 vegan_2.6-2
[115] fastmatch_1.1-3 tidytree_0.3.9 operator.tools_1.6.3
[118] dendextend_1.15.2 DelayedMatrixStats_1.18.0 restfulr_0.0.13
[121] curl_4.3.2 EBImage_4.38.0 Rsamtools_2.12.0
[124] gtools_3.9.2 rjson_0.2.21 lifecycle_1.0.1
[127] nlme_3.1-157 jsonlite_1.8.0 carData_3.0-5
[130] viridisLite_0.4.0 fansi_1.0.3 pillar_1.7.0
[133] lattice_0.20-45 KEGGREST_1.36.0 fastmap_1.1.0
[136] httr_1.4.3 plotrix_3.8-2 GO.db_3.15.0
[139] glue_1.6.2 png_0.1-7 bit_4.0.4
[142] ggforce_0.3.3 stringi_1.7.6 blob_1.2.3
[145] caTools_1.18.2 memoise_2.0.1 dplyr_1.0.9
[148] ape_5.6-2
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