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me5537
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@me5537-22246
Last seen 5.1 years ago
hello, I am new to bioinformatics and Galaxy, so maybe my question is kind of naive. I’m reading RNAseq count data generated from kallito using tximport:
humandb<- EnsDb.Hsapiens.v75
tran.human<- transcripts(humandb, return.type = “DataFrame”)
tran.human<- tran.human[, c(“tx_id”, “gene_id”)]
gene.human<- genes(humandb, return.type = “DataFrame”)
gene.human<- gene.human[, c(“gene_id”, “symbol”)]
tx2genes.human <- merge(tran.human, gene.human, by = “gene_id”)
tx2genes <- as.data.frame(tx2genes.human[, 2:3])
colnames(tx2genes)[1]<-“target_id”
txi.kallisto <- tximport(files, type = “kallisto”, tx2gene = tx2genes, ignoreTxVersion = TRUE)
loadname <- c(“ERR2814755”,“ERR2814756”)
name<-candidate$sample
files <- file.path(path,loadname, “abundance.h5”)
names(files) <- loadname
txi.kallisto <- tximport(files, type = “kallisto”, tx2gene = tx2genes, ignoreTxVersion = TRUE)
it used to work, but after 10.29, when I try it again without any change, it gave the error information as follows:
Error: Unable to read dataset. Not all required filters available. Missing filters: deflate
my library
> sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-conda_cos6-linux-gnu (64-bit)
Running under: Ubuntu 16.04.5 LTS
Matrix products: default
BLAS/LAPACK: /pub/anaconda3/lib/R/lib/libRblas.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=en_US.UTF-8
[4] LC_COLLATE=en_US.UTF-8 LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=en_US.UTF-8 LC_ADDRESS=en_US.UTF-8
[10] LC_TELEPHONE=en_US.UTF-8 LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=en_US.UTF-8
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 ggord_1.1.4
[3] EnsDb.Hsapiens.v75_2.99.0 ensembldb_2.6.2
[5] AnnotationFilter_1.8.0 clusterProfiler_3.12.0
[7] sva_3.32.1 genefilter_1.66.0
[9] mgcv_1.8-30 nlme_3.1-141
[11] ggpubr_0.2.3 magrittr_1.5
[13] dplyr_0.8.3 data.table_1.12.6
[15] xlsx_0.6.1 gplots_3.0.1.1
[17] hexbin_1.27.3 rhdf5_2.28.1
[19] readxl_1.3.1 RColorBrewer_1.1-2
[21] pheatmap_1.0.12 tximportData_1.12.0
[23] stringr_1.4.0 stringi_1.4.3
[25] DESeq2_1.24.0 SummarizedExperiment_1.14.1
[27] DelayedArray_0.10.0 BiocParallel_1.18.1
[29] matrixStats_0.55.0 readr_1.3.1
[31] tximport_1.12.3 edgeR_3.26.8
[33] limma_3.40.6 GenomicFeatures_1.36.4
[35] AnnotationDbi_1.46.1 Biobase_2.44.0
[37] GenomicRanges_1.36.1 GenomeInfoDb_1.20.0
[39] IRanges_2.18.3 ggplot2_3.2.1
[41] S4Vectors_0.22.1 BiocGenerics_0.30.0
loaded via a namespace (and not attached):
[1] backports_1.1.5 Hmisc_4.2-0 fastmatch_1.1-0
[4] plyr_1.8.4 igraph_1.2.4.1 lazyeval_0.2.2
[7] splines_3.6.1 urltools_1.7.3 digest_0.6.22
[10] htmltools_0.4.0 GOSemSim_2.10.0 viridis_0.5.1
[13] GO.db_3.8.2 gdata_2.18.0 checkmate_1.9.4
[16] memoise_1.1.0 cluster_2.1.0 Biostrings_2.52.0
[19] annotate_1.62.0 graphlayouts_0.5.0 enrichplot_1.4.0
[22] prettyunits_1.0.2 colorspace_1.4-1 blob_1.2.0
[25] ggrepel_0.8.1 xfun_0.10 jsonlite_1.6
[28] crayon_1.3.4 RCurl_1.95-4.12 zeallot_0.1.0
[31] survival_2.44-1.1 glue_1.3.1 polyclip_1.10-0
[34] gtable_0.3.0 zlibbioc_1.30.0 XVector_0.24.0
[37] UpSetR_1.4.0 Rhdf5lib_1.6.3 scales_1.0.0
[40] DOSE_3.10.2 DBI_1.0.0 Rcpp_1.0.2
[43] viridisLite_0.3.0 xtable_1.8-4 progress_1.2.2
[46] htmlTable_1.13.2 gridGraphics_0.4-1 europepmc_0.3
[49] foreign_0.8-72 bit_1.1-14 Formula_1.2-3
[52] htmlwidgets_1.5.1 httr_1.4.1 fgsea_1.10.1
[55] acepack_1.4.1 pkgconfig_2.0.3 XML_3.98-1.20
[58] rJava_0.9-11 farver_1.1.0 nnet_7.3-12
[61] locfit_1.5-9.1 ggplotify_0.0.4 tidyselect_0.2.5
[64] rlang_0.4.1 reshape2_1.4.3 munsell_0.5.0
[67] cellranger_1.1.0 tools_3.6.1 RSQLite_2.1.2
[70] ggridges_0.5.1 yaml_2.2.0 knitr_1.25
[73] bit64_0.9-7 tidygraph_1.1.2 caTools_1.17.1.2
[76] purrr_0.3.3 ggraph_2.0.0 xml2_1.2.2
[79] DO.db_2.9 biomaRt_2.40.5 compiler_3.6.1
[82] rstudioapi_0.10 curl_4.2 ggsignif_0.6.0
[85] tibble_2.1.3 tweenr_1.0.1 geneplotter_1.62.0
[88] lattice_0.20-38 ProtGenerics_1.16.0 Matrix_1.2-17
[91] vctrs_0.2.0 pillar_1.4.2 lifecycle_0.1.0
[94] BiocManager_1.30.9 triebeard_0.3.0 cowplot_1.0.0
[97] bitops_1.0-6 rtracklayer_1.44.4 qvalue_2.16.0
[100] R6_2.4.0 latticeExtra_0.6-28 KernSmooth_2.23-16
[103] gridExtra_2.3 MASS_7.3-51.4 gtools_3.8.1
[106] assertthat_0.2.1 xlsxjars_0.6.1 withr_2.1.2
[109] GenomicAlignments_1.20.1 Rsamtools_2.0.3 GenomeInfoDbData_1.2.1
[112] hms_0.5.1 grid_3.6.1 rpart_4.1-15
[115] tidyr_1.0.0 rvcheck_0.1.5 ggforce_0.3.1
[118] base64enc_0.1-3
I check the packages as follows:but it seems that it won't affect the dataset reading?
sessionInfo()
R version 3.6.1 (2019-07-05) Platform: x8664-condacos6-linux-gnu (64-bit) Running under: Ubuntu 16.04.6 LTS
Matrix products: default BLAS/LAPACK: /pub/anaconda3/lib/R/lib/libRblas.so
locale: [1] LCCTYPE=enUS.UTF-8 LCNUMERIC=C LCTIME=enUS.UTF-8
[4] LCCOLLATE=enUS.UTF-8 LCMONETARY=enUS.UTF-8 LCMESSAGES=enUS.UTF-8
[7] LCPAPER=enUS.UTF-8 LCNAME=enUS.UTF-8 LCADDRESS=enUS.UTF-8
[10] LCTELEPHONE=enUS.UTF-8 LCMEASUREMENT=enUS.UTF-8 LCIDENTIFICATION=en_US.UTF-8
attached base packages: [1] stats4 parallel stats graphics grDevices utils datasets methods base
other attached packages: [1] EnsDb.Hsapiens.v752.99.0 sva3.32.1 mgcv1.8-30
[4] nlme3.1-141 ggpubr0.2.3 magrittr1.5
[7] dplyr0.8.3 data.table1.12.6 xlsx0.6.1
[10] gplots3.0.1.1 hexbin1.27.3 rhdf52.28.1
[13] readxl1.3.1 RColorBrewer1.1-2 pheatmap1.0.12
[16] tximportData1.12.0 stringr1.4.0 stringi1.4.3
[19] DESeq21.24.0 SummarizedExperiment1.14.1 DelayedArray0.10.0
[22] BiocParallel1.18.1 matrixStats0.55.0 readr1.3.1
[25] tximport1.12.3 edgeR3.26.8 limma3.40.6
[28] ggplot23.2.1 ensembldb2.8.1 GenomicFeatures1.36.4
[31] AnnotationDbi1.46.1 GenomicRanges1.36.1 GenomeInfoDb1.20.0
[34] IRanges2.18.3 S4Vectors0.22.1 AnnotationFilter1.8.0
[37] affyPLM1.60.0 preprocessCore1.46.0 simpleaffy2.60.0
[40] gcrma2.56.0 genefilter1.66.0 affyQCReport1.62.0
[43] lattice0.20-38 affy1.62.0 Biobase2.44.0
[46] BiocGenerics0.30.0
Bioconductor version '3.9'
create a valid installation with
BiocManager::install(c( "hms", "tinytex" ), update = TRUE, ask = FALSE)
Try reinstalling rhdf5. Something isn’t working with this library. The error isn’t from the tximport package but one of its dependencies, which must have been changed by some other action on the system.
I have tried reinstalled rhdf5 2.3.0, it still doesn't work and I try to read dataset by tximport using the following code
but it doesn't work either.
but it is .tsv format…… T-T
Oh, I didn’t realize this was TSV. I think it’s actually an error from readr. Could you try updating/reinstalling that package?
actually, I have tried both "abundance.h5" and "abundance.tsv" files using tximport but it gave the same ERROR information^
Ok I take it back, searching through my email I've found that this is linked to rhdf5. See the identical error message here:
https://stat.ethz.ch/pipermail/bioc-devel/2019-July/015326.html
It looks like this was addressed in the devel branch in July and so now it is available as the lastest Bioc release (3.10). Can you update Bioc to 3.10 and see if the issue is fixed on your end.
Thank you very much…… I asked the administrator to help me update the bioc to 3.10, but he refused for the reason that not all the R packages can be used in Bioc 3.10
the administrator told me that the reason why I suddenly couldn't use the tximport is that the server is named NFS, they depose software in one of the servers and let the other 8 servers use together, so some of them may produce error information.
It really troubles me so I change to another server producers and find that even in Bioc 3.09 it does work……
Thank you all the way!!! I do really appreciate that!!
Hi Michael. I am getting this same error even with BiocManager 3.10 and after reinstalling Rhdf5lib & rhdf5
This is my session info:
Can you try to open the h5 file using rhdf5? I think the error is coming from that package. That will help you/me debug, because the error isn't directly from one of the functions in tximport.
Alternatively, if you can't seem to nail down why rhdf5 doesn't want to import this file, I think you can just specify
dropInfReps=TRUE
and it will work without loading the information in the h5 file.Thank you Michael! I managed to solve it by installing
rhdf5
via conda directly:conda install --channel https://conda.anaconda.org/bioconda bioconductor-rhdf5
rather than via
BiocManager::install("rhdf5")
which caused the issue.