Open dylanmr opened 4 years ago
dylanmr
commented
4 years ago I was able to semi-fix this by removing any columns with NA from the metadata but now receive this error.
Error in attr$write(robj) : HDF5-API Errors: error #000: /home/hdftest/snapshots-hdf5_1_10_5/current/src/H5A.c in H5Awrite(): line 619: null attribute buffer class: HDF5 major: Invalid arguments to routine minor: Bad value
vincent-marty
commented
3 years ago I have the same issue while trying to save H5Seurat after using the FindVariableFeatures function (method "mvp") with data from https://broadinstitute.github.io/wot/tutorial/ (after converting h5ad fil to seurat file).
var2 <- FindVariableFeatures(df, selection.method = "mvp", num.bin = 20) Calculating gene means 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **| Calculating gene variance to mean ratios 0% 10 20 30 40 50 60 70 80 90 100% [----|----|----|----|----|----|----|----|----|----| **| SaveH5Seurat(var2, overwrite = TRUE) Creating h5Seurat file for version 3.1.5.9900 Adding counts for RNA Adding data for RNA Adding variable features for RNA Adding feature-level metadata for RNA Error in attr$write(robj) : HDF5-API Errors: error #000: ../../../src/H5A.c in H5Awrite(): line 638: null attribute buffer class: HDF5 major: Invalid arguments to routine minor: Bad value
Would you have any clue how to solve this ? (When I use SaveH5Seurat before FindVariableFeatures all is working well)
Thank you in advance
ShaowenJ
commented
3 years ago Same error here....
Creating h5Seurat file for version 3.1.5.9900 Adding counts for RNA Adding data for RNA No variable features found for RNA No feature-level metadata found for RNA Adding cell embeddings for umap No loadings for umap No projected loadings for umap Error in attr$write(robj) : HDF5-API Errors: error #000: ../../../src/H5A.c in H5Awrite(): line 638: null attribute buffer class: HDF5 major: Invalid arguments to routine minor: Bad value
lavon79
commented
3 years ago Same error here....
Creating h5Seurat file for version 3.1.5.9900 Adding counts for RNA Adding data for RNA No variable features found for RNA No feature-level metadata found for RNA Adding cell embeddings for umap No loadings for umap No projected loadings for umap Error in attr$write(robj) : HDF5-API Errors: error #0: ../../../src/H5A.c in H5Awrite(): line 638: null attribute buffer class: HDF5 major: Invalid arguments to routine minor: Bad value
I faced the same error too. have you sloved it?
ShaowenJ
commented
3 years ago @lavon79 I have not....
yueqiw
commented
3 years ago Same error:
Creating h5Seurat file for version 3.1.5.9900
Adding counts for RNA
Adding data for RNA
Adding scale.data for RNA
Adding variable features for RNA
No feature-level metadata found for RNA
Adding cell embeddings for pca
No loadings for pca
No projected loadings for pca
Error in attr$write(robj): HDF5-API Errors:
error #000: H5A.c in H5Awrite(): line 619: null attribute buffer
class: HDF5
major: Invalid arguments to routine
minor: Bad value
Traceback:
1. SaveH5Seurat(seurat3_data, filename = h5seurat_fname)
2. SaveH5Seurat.Seurat(seurat3_data, filename = h5seurat_fname)
3. as.h5Seurat(x = object, filename = filename, overwrite = overwrite,
. verbose = verbose, ...)
4. as.h5Seurat.Seurat(x = object, filename = filename, overwrite = overwrite,
. verbose = verbose, ...)
5. WriteH5Group(x = x[[reduc]], name = reduc, hgroup = hfile[["reductions"]],
. verbose = verbose)
6. WriteH5Group(x = x[[reduc]], name = reduc, hgroup = hfile[["reductions"]],
. verbose = verbose)
7. xgroup$create_attr(attr_name = "global", robj = BoolToInt(x = IsGlobal(object = x)),
. dtype = GuessDType(x = IsGlobal(object = x)))
8. attr$write(robj)
AAA-3
commented
3 years ago Same here. My Seurata Object was an older version which I updated.
Creating h5Seurat file for version 3.1.5.9900
Adding counts for RNA
Adding data for RNA
Adding scale.data for RNA
Adding variable features for RNA
No feature-level metadata found for RNA
Adding cell embeddings for pca
Adding loadings for pca
No projected loadings for pca
Error in attr$write(robj) : HDF5-API Errors:
error #000: ../../../src/H5A.c in H5Awrite(): line 638: null attribute buffer
class: HDF5
major: Invalid arguments to routine
minor: Bad value
huawen-poppy
commented
2 years ago I faced the same issue here. To solve this problem, I firstly updated my old seurat object which contains PCA, UMAP, and TSNE embeddings. Then I reran the RunPCA, RunUMAP, and RunTSNE functions on my updated object. After this, I can successfully convert the object to h5ad format. Hope this information helps.
YY-SONG0718
commented
2 years ago I faced the same issue here. To solve this problem, I firstly updated my old seurat object which contains PCA, UMAP, and TSNE embeddings. Then I reran the RunPCA, RunUMAP, and RunTSNE functions on my updated object. After this, I can successfully convert the object to h5ad format. Hope this information helps.
I just had the same issue and this solution worked.
volkansevim
commented
2 years ago I encountered a different error saving a Seurat H5:
Creating h5Seurat file for version 3.1.5.9900
Adding counts for RNA
Adding data for RNA
No variable features found for RNA
No feature-level metadata found for RNA
Adding counts for ATAC
Adding data for ATAC
Adding variable features for ATAC
Adding feature-level metadata for ATAC
Writing out ranges for ATAC
Writing out motifs for ATAC
Error in attr$write(robj): HDF5-API Errors:
error #000: H5A.c in H5Awrite(): line 657: buf parameter can't be NULL
class: HDF5
major: Invalid arguments to routine
minor: Bad value
Traceback:
1. SaveH5Seurat(seurat, save_h5_file, overwrite = TRUE, verbose = TRUE)
2. SaveH5Seurat.Seurat(seurat, save_h5_file, overwrite = TRUE, verbose = TRUE)
3. as.h5Seurat(x = object, filename = filename, overwrite = overwrite,
. verbose = verbose, ...)
4. as.h5Seurat.Seurat(x = object, filename = filename, overwrite = overwrite,
. verbose = verbose, ...)
5. WriteH5Group(x = x[[assay]], name = assay, hgroup = hfile[["assays"]],
. verbose = verbose)
6. WriteH5Group(x = x[[assay]], name = assay, hgroup = hfile[["assays"]],
. verbose = verbose)
7. WriteH5Group(x = slot(object = x, name = slot), name = slot,
. hgroup = xgroup, verbose = verbose)
8. WriteH5Group(x = slot(object = x, name = slot), name = slot,
. hgroup = xgroup, verbose = verbose)
9. WriteH5Group(x = slot(object = x, name = i), name = i, hgroup = xgroup,
. verbose = verbose)
10. WriteH5Group(x = slot(object = x, name = i), name = i, hgroup = xgroup,
. verbose = verbose)
11. xgroup$create_attr(attr_name = "colnames", robj = intersect(x = colnames(x = x),
. y = names(x = xgroup)), dtype = GuessDType(x = colnames(x = x)))
12. attr$write(robj)This problem occurs after adding a motifs assay to the Seurat object:
DefaultAssay(seurat) <- "ATAC"
pwm_set <- getMatrixSet(x = JASPAR2020, opts = list(species = 9606, all_versions = FALSE))
motif.matrix <- CreateMotifMatrix(features = granges(seurat), pwm = pwm_set, genome = 'hg38', use.counts = FALSE)
motif.object <- CreateMotifObject(data = motif.matrix, pwm = pwm_set)
seurat <- SetAssayData(seurat, assay = 'ATAC', slot = 'motifs', new.data = motif.object)I was able to save the file without an error before this step.
Session info:
R version 4.1.3 (2022-03-10)
Platform: x86_64-conda-linux-gnu (64-bit)
Running under: Ubuntu 20.04.5 LTS
Matrix products: default
BLAS/LAPACK: /home/vsevim/software/anaconda3/envs/Renv/lib/libopenblasp-r0.3.20.so
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
attached base packages:
[1] stats4 stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] BSgenome.Hsapiens.UCSC.hg38_1.4.4 BSgenome_1.62.0
[3] rtracklayer_1.54.0 Biostrings_2.62.0
[5] XVector_0.34.0 motifmatchr_1.16.0
[7] TFBSTools_1.32.0 JASPAR2020_0.99.10
[9] chromVAR_1.16.0 SeuratDisk_0.0.0.9020
[11] bedr_1.0.7 ggplot2_3.3.6
[13] dplyr_1.0.9 EnsDb.Hsapiens.v86_2.99.0
[15] ensembldb_2.18.4 AnnotationFilter_1.18.0
[17] GenomicFeatures_1.46.5 AnnotationDbi_1.56.2
[19] Biobase_2.54.0 GenomicRanges_1.46.1
[21] GenomeInfoDb_1.30.1 IRanges_2.28.0
[23] S4Vectors_0.32.4 BiocGenerics_0.40.0
[25] Signac_1.7.0 sp_1.5-0
[27] SeuratObject_4.1.0 Seurat_4.1.1
loaded via a namespace (and not attached):
[1] rappdirs_0.3.3 pbdZMQ_0.3-7
[3] scattermore_0.8 R.methodsS3_1.8.2
[5] nabor_0.5.0 tidyr_1.2.0
[7] bit64_4.0.5 knitr_1.39
[9] irlba_2.3.5 DelayedArray_0.20.0
[11] R.utils_2.12.0 data.table_1.14.2
[13] rpart_4.1.16 KEGGREST_1.34.0
[15] RCurl_1.98-1.8 generics_0.1.3
[17] cowplot_1.1.1 lambda.r_1.2.4
[19] RSQLite_2.2.15 RANN_2.6.1
[21] future_1.27.0 tzdb_0.3.0
[23] bit_4.0.4 spatstat.data_2.2-0
[25] xml2_1.3.3 httpuv_1.6.5
[27] SummarizedExperiment_1.24.0 assertthat_0.2.1
[29] DirichletMultinomial_1.36.0 xfun_0.32
[31] hms_1.1.1 evaluate_0.16
[33] promises_1.2.0.1 fansi_1.0.3
[35] restfulr_0.0.15 progress_1.2.2
[37] caTools_1.18.2 dbplyr_2.2.1
[39] igraph_1.3.4 DBI_1.1.3
[41] htmlwidgets_1.5.4 futile.logger_1.4.3
[43] spatstat.geom_2.4-0 purrr_0.3.4
[45] ellipsis_0.3.2 RSpectra_0.16-1
[47] backports_1.4.1 annotate_1.72.0
[49] biomaRt_2.50.3 deldir_1.0-6
[51] MatrixGenerics_1.6.0 vctrs_0.4.1
[53] Cairo_1.6-0 ROCR_1.0-11
[55] abind_1.4-5 cachem_1.0.6
[57] withr_2.5.0 progressr_0.10.1
[59] checkmate_2.1.0 sctransform_0.3.3
[61] GenomicAlignments_1.30.0 prettyunits_1.1.1
[63] goftest_1.2-3 cluster_2.1.3
[65] seqLogo_1.60.0 IRdisplay_1.1
[67] lazyeval_0.2.2 crayon_1.5.1
[69] hdf5r_1.3.5 pkgconfig_2.0.3
[71] labeling_0.4.2 vipor_0.4.5
[73] nlme_3.1-159 ProtGenerics_1.26.0
[75] nnet_7.3-17 rlang_1.0.6
[77] globals_0.16.0 lifecycle_1.0.2
[79] miniUI_0.1.1.1 filelock_1.0.2
[81] BiocFileCache_2.2.1 dichromat_2.0-0.1
[83] VennDiagram_1.7.3 ggrastr_1.0.1
[85] polyclip_1.10-0 matrixStats_0.62.0
[87] lmtest_0.9-40 Matrix_1.4-1
[89] IRkernel_1.3 zoo_1.8-10
[91] beeswarm_0.4.0 base64enc_0.1-3
[93] ggridges_0.5.3 png_0.1-7
[95] viridisLite_0.4.1 rjson_0.2.21
[97] bitops_1.0-7 R.oo_1.25.0
[99] KernSmooth_2.23-20 blob_1.2.3
[101] stringr_1.4.0 parallelly_1.32.1
[103] spatstat.random_2.2-0 readr_2.1.2
[105] jpeg_0.1-9 CNEr_1.30.0
[107] scales_1.2.1 memoise_2.0.1
[109] magrittr_2.0.3 plyr_1.8.7
[111] ica_1.0-3 zlibbioc_1.40.0
[113] compiler_4.1.3 BiocIO_1.4.0
[115] RColorBrewer_1.1-3 fitdistrplus_1.1-8
[117] Rsamtools_2.10.0 cli_3.4.1
[119] listenv_0.8.0 patchwork_1.1.1
[121] pbapply_1.5-0 htmlTable_2.4.1
[123] formatR_1.12 Formula_1.2-4
[125] MASS_7.3-58.1 mgcv_1.8-40
[127] tidyselect_1.1.2 stringi_1.7.8
[129] yaml_2.3.5 latticeExtra_0.6-30
[131] ggrepel_0.9.1 grid_4.1.3
[133] VariantAnnotation_1.40.0 fastmatch_1.1-3
[135] tools_4.1.3 future.apply_1.9.0
[137] parallel_4.1.3 rstudioapi_0.13
[139] uuid_1.1-0 TFMPvalue_0.0.8
[141] foreign_0.8-82 gridExtra_2.3
[143] farver_2.1.1 Rtsne_0.16
[145] digest_0.6.29 rgeos_0.5-9
[147] pracma_2.3.8 shiny_1.7.2
[149] Rcpp_1.0.9 later_1.3.0
[151] RcppAnnoy_0.0.19 httr_1.4.4
[153] biovizBase_1.42.0 colorspace_2.0-3
[155] brio_1.1.3 XML_3.99-0.10
[157] tensor_1.5 reticulate_1.25-9000
[159] splines_4.1.3 uwot_0.1.11
[161] RcppRoll_0.3.0 spatstat.utils_2.3-1
[163] plotly_4.10.0 xtable_1.8-4
[165] poweRlaw_0.70.6 jsonlite_1.8.0
[167] futile.options_1.0.1 testthat_3.1.4
[169] R6_2.5.1 Hmisc_4.7-0
[171] pillar_1.8.1 htmltools_0.5.3
[173] mime_0.12 DT_0.24
[175] glue_1.6.2 fastmap_1.1.0
[177] BiocParallel_1.28.3 codetools_0.2-18
[179] utf8_1.2.2 lattice_0.20-45
[181] spatstat.sparse_2.1-1 tibble_3.1.8
[183] curl_4.3.2 ggbeeswarm_0.6.0
[185] leiden_0.4.2 gtools_3.9.3
[187] GO.db_3.14.0 interp_1.1-3
[189] survival_3.4-0 repr_1.1.4
[191] munsell_0.5.0 GenomeInfoDbData_1.2.7
[193] reshape2_1.4.4 gtable_0.3.1
[195] spatstat.core_2.4-4 
ShanshanHe-44
commented
1 year ago I tried the solution in #26 and it succeed. I think that could be the problem in 'reductions'.
srt@reductions$umap@misc <- list()
laurabchopp
commented
1 year ago I encountered a similar problem after adding motif object to my peaks assay. Solved it with this line:
SeuratObject@assays$peaks@motifs <- NULL
ShanshanHe-44
commented
1 year ago Once I update my Seurat to latest version, I got this error again. And I try to empty all my reductions layers but still useless.
Error in if (ncol(x = x[[]])) { : argument is of length zero
pravinavenk
commented
1 year ago Even I got this error Once I update my Seurat to latest version. Could someone help with this ?
Error in if (ncol(x = x[[]])) { : argument is of length zero
liuxiawei
commented
5 months ago Same problem. Data from GSE152766 , GSE152766_Root_Atlas.rds.gz ERROR:
Warning message:
“Overwriting previous file RNA.h5Seurat”
Creating h5Seurat file for version 3.1.5.9900
Adding counts for RNA
Adding data for RNA
No variable features found for RNA
No feature-level metadata found for RNA
Adding counts for SCT
Adding data for SCT
Adding scale.data for SCT
Adding variable features for SCT
Adding feature-level metadata for SCT
Adding data for integrated
Adding scale.data for integrated
Adding variable features for integrated
No feature-level metadata found for integrated
Adding cell embeddings for pca
Adding loadings for pca
No projected loadings for pca
Adding standard deviations for pca
No JackStraw data for pca
Adding cell embeddings for umap
No loadings for umap
No projected loadings for umap
No standard deviations for umap
No JackStraw data for umap
Adding cell embeddings for umap_3D
No loadings for umap_3D
No projected loadings for umap_3D
No standard deviations for umap_3D
No JackStraw data for umap_3D
Adding cell embeddings for umap_2D
No loadings for umap_2D
No projected loadings for umap_2D
No standard deviations for umap_2D
No JackStraw data for umap_2D
Adding cell embeddings for umap_50
No loadings for umap_50
No projected loadings for umap_50
No standard deviations for umap_50
No JackStraw data for umap_50
Error in xgroup$create_attr(attr_name = "names", robj = intersect(x = names(x = x), : HDF5-API Errors:
error #000: H5A.c in H5Acreate2(): line 298: unable to create attribute
class: HDF5
major: Attribute
minor: Unable to initialize object
error #001: H5VLcallback.c in H5VL_attr_create(): line 988: attribute create failed
class: HDF5
major: Virtual Object Layer
minor: Unable to create file
error #002: H5VLcallback.c in H5VL__attr_create(): line 955: attribute create failed
class: HDF5
major: Virtual Object Layer
minor: Unable to create file
error #003: H5VLnative_attr.c in H5VL__native_attr_create(): line 75: unable to create attribute
class: HDF5
major: Attribute
minor: Unable to initialize object
error #004: H5Aint.c in H5A__create(): line 268: unable to create attribute in object header
class: HDF5
major: Attribute
minor: Unable to insert object
error #005: H5Oattribute.c in H5O__attr_create(): line 317: unable to create
Traceback:
1. SaveH5Seurat(tmp, filename = "RNA.h5Seurat", overwrite = T)
2. SaveH5Seurat.Seurat(tmp, filename = "RNA.h5Seurat", overwrite = T)
3. as.h5Seurat(x = object, filename = filename, overwrite = overwrite,
. verbose = verbose, ...)
4. as.h5Seurat.Seurat(x = object, filename = filename, overwrite = overwrite,
. verbose = verbose, ...)
5. WriteH5Group(x = x[[]], name = "meta.data", hgroup = hfile, verbose = verbose)
6. WriteH5Group(x = x[[]], name = "meta.data", hgroup = hfile, verbose = verbose)
7. WriteH5Group(x = x[, i, drop = TRUE], name = i, hgroup = xgroup,
. verbose = verbose)
8. WriteH5Group(x = x[, i, drop = TRUE], name = i, hgroup = xgroup,
. verbose = verbose)
9. xgroup$create_attr(attr_name = "names", robj = intersect(x = names(x = x),
. y = names(x = xgroup)), dtype = GuessDType(x = names(x = x)[1]))session info
─ Session info ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
setting value
version R version 4.3.1 (2023-06-16)
os Ubuntu 18.04.6 LTS
system x86_64, linux-gnu
ui X11
language zh_CN:zh
collate zh_CN.UTF-8
ctype zh_CN.UTF-8
tz Asia/Shanghai
date 2024-06-15
pandoc 2.12 @ /bin/pandoc
─ Packages ───────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
abind 1.4-5 2016-07-21 [1] CRAN (R 4.3.1)
backports 1.4.1 2021-12-13 [1] CRAN (R 4.3.1)
base64enc 0.1-3 2015-07-28 [1] CRAN (R 4.3.1)
bit 4.0.5 2022-11-15 [1] CRAN (R 4.3.1)
bit64 4.0.5 2020-08-30 [1] CRAN (R 4.3.1)
broom 1.0.5 2023-06-09 [1] CRAN (R 4.3.1)
car 3.1-2 2023-03-30 [1] CRAN (R 4.3.1)
carData 3.0-5 2022-01-06 [1] CRAN (R 4.3.1)
cli 3.6.2 2023-12-11 [1] CRAN (R 4.3.1)
cluster 2.1.4 2022-08-22 [1] CRAN (R 4.3.1)
codetools 0.2-20 2024-03-31 [1] CRAN (R 4.3.1)
colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.3.1)
cowplot 1.1.1 2020-12-30 [1] CRAN (R 4.3.1)
crayon 1.5.2 2022-09-29 [1] CRAN (R 4.3.1)
data.table 1.14.8 2023-02-17 [1] CRAN (R 4.3.1)
deldir 1.0-9 2023-05-17 [1] CRAN (R 4.3.1)
digest 0.6.35 2024-03-11 [1] CRAN (R 4.3.1)
dotCall64 1.1-1 2023-11-28 [1] CRAN (R 4.3.1)
dplyr * 1.1.3 2023-09-03 [1] CRAN (R 4.3.1)
ellipsis 0.3.2 2021-04-29 [1] CRAN (R 4.3.1)
evaluate 0.22 2023-09-29 [1] CRAN (R 4.3.1)
fansi 1.0.5 2023-10-08 [1] CRAN (R 4.3.1)
fastmap 1.1.1 2023-02-24 [1] CRAN (R 4.3.1)
fitdistrplus 1.1-11 2023-04-25 [1] CRAN (R 4.3.1)
future 1.33.0 2023-07-01 [1] CRAN (R 4.3.1)
future.apply 1.11.0 2023-05-21 [1] CRAN (R 4.3.1)
generics 0.1.3 2022-07-05 [1] CRAN (R 4.3.1)
ggplot2 * 3.4.4 2023-10-12 [1] CRAN (R 4.3.1)
ggpubr * 0.6.0 2023-02-10 [1] CRAN (R 4.3.1)
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ggsignif 0.6.4 2022-10-13 [1] CRAN (R 4.3.1)
globals 0.16.2 2022-11-21 [1] CRAN (R 4.3.1)
glue 1.7.0 2024-01-09 [1] CRAN (R 4.3.1)
goftest 1.2-3 2021-10-07 [1] CRAN (R 4.3.1)
gridExtra 2.3 2017-09-09 [1] CRAN (R 4.3.1)
gtable 0.3.4 2023-08-21 [1] CRAN (R 4.3.1)
hdf5r 1.3.10 2024-03-02 [1] CRAN (R 4.3.1)
here 1.0.1 2020-12-13 [1] CRAN (R 4.3.1)
htmltools 0.5.6.1 2023-10-06 [1] CRAN (R 4.3.1)
htmlwidgets 1.6.2 2023-03-17 [1] CRAN (R 4.3.1)
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ica 1.0-3 2022-07-08 [1] CRAN (R 4.3.1)
igraph 1.5.1 2023-08-10 [1] CRAN (R 4.3.1)
IRdisplay 1.1 2022-01-04 [1] CRAN (R 4.3.1)
IRkernel 1.3.2 2023-09-23 [1] local
irlba 2.3.5.1 2022-10-03 [1] CRAN (R 4.3.1)
jsonlite 1.8.7 2023-06-29 [1] CRAN (R 4.3.1)
KernSmooth 2.23-22 2023-07-10 [1] CRAN (R 4.3.1)
later 1.3.1 2023-05-02 [1] CRAN (R 4.3.1)
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lazyeval 0.2.2 2019-03-15 [1] CRAN (R 4.3.1)
leiden 0.4.3 2022-09-10 [1] CRAN (R 4.3.1)
lifecycle 1.0.3 2022-10-07 [1] CRAN (R 4.3.1)
listenv 0.9.1 2024-01-29 [1] CRAN (R 4.3.1)
lmtest 0.9-40 2022-03-21 [1] CRAN (R 4.3.1)
magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.3.1)
MASS 7.3-60 2023-05-04 [1] CRAN (R 4.3.1)
Matrix 1.6-1.1 2023-09-18 [1] CRAN (R 4.3.1)
matrixStats 1.0.0 2023-06-02 [1] CRAN (R 4.3.1)
mime 0.12 2021-09-28 [1] CRAN (R 4.3.1)
miniUI 0.1.1.1 2018-05-18 [1] CRAN (R 4.3.1)
munsell 0.5.0 2018-06-12 [1] CRAN (R 4.3.1)
nlme 3.1-163 2023-08-09 [1] CRAN (R 4.3.1)
parallelly 1.37.1 2024-02-29 [1] CRAN (R 4.3.1)
patchwork * 1.1.3 2023-08-14 [1] CRAN (R 4.3.1)
pbapply 1.7-2 2023-06-27 [1] CRAN (R 4.3.1)
pbdZMQ 0.3-10 2023-09-05 [1] CRAN (R 4.3.1)
pillar 1.9.0 2023-03-22 [1] CRAN (R 4.3.1)
pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.3.1)
plotly 4.10.2 2023-06-03 [1] CRAN (R 4.3.1)
plyr 1.8.9 2023-10-02 [1] CRAN (R 4.3.1)
png 0.1-8 2022-11-29 [1] CRAN (R 4.3.1)
polyclip 1.10-6 2023-09-27 [1] CRAN (R 4.3.1)
progressr 0.14.0 2023-08-10 [1] CRAN (R 4.3.1)
promises 1.2.1 2023-08-10 [1] CRAN (R 4.3.1)
purrr 1.0.2 2023-08-10 [1] CRAN (R 4.3.1)
R6 2.5.1 2021-08-19 [1] CRAN (R 4.3.1)
RANN 2.6.1 2019-01-08 [1] CRAN (R 4.3.1)
rappdirs 0.3.3 2021-01-31 [1] CRAN (R 4.3.1)
RColorBrewer 1.1-3 2022-04-03 [1] CRAN (R 4.3.1)
Rcpp 1.0.12 2024-01-09 [1] CRAN (R 4.3.1)
RcppAnnoy 0.0.21 2023-07-02 [1] CRAN (R 4.3.1)
repr 1.1.6 2023-01-26 [1] CRAN (R 4.3.1)
reshape2 1.4.4 2020-04-09 [1] CRAN (R 4.3.1)
reticulate 1.34.0 2023-10-12 [1] CRAN (R 4.3.1)
rlang 1.1.4 2024-06-04 [1] CRAN (R 4.3.1)
ROCR 1.0-11 2020-05-02 [1] CRAN (R 4.3.1)
rprojroot 2.0.3 2022-04-02 [1] CRAN (R 4.3.1)
rstatix 0.7.2 2023-02-01 [1] CRAN (R 4.3.1)
Rtsne 0.16 2022-04-17 [1] CRAN (R 4.3.1)
scales 1.2.1 2022-08-20 [1] CRAN (R 4.3.1)
scattermore 1.2 2023-06-12 [1] CRAN (R 4.3.1)
sceasy 0.0.7 2023-07-19 [1] local
sctransform 0.4.1 2023-10-19 [1] CRAN (R 4.3.1)
sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.3.1)
Seurat * 4.4.0 2023-09-28 [1] CRAN (R 4.3.1)
SeuratDisk * 0.0.0.9021 2024-06-14 [1] Github (mojaveazure/seurat-disk@877d4e1)
SeuratObject * 5.0.0 2023-10-26 [1] CRAN (R 4.3.1)
shiny 1.7.5.1 2023-10-14 [1] CRAN (R 4.3.1)
sp 2.1-1 2023-10-16 [1] CRAN (R 4.3.1)
spam 2.9-1 2022-08-07 [1] CRAN (R 4.3.1)
spatstat.data 3.0-1 2023-03-12 [1] CRAN (R 4.3.1)
spatstat.explore 3.2-3 2023-09-07 [1] CRAN (R 4.3.1)
spatstat.geom 3.2-5 2023-09-05 [1] CRAN (R 4.3.1)
spatstat.random 3.1-6 2023-09-09 [1] CRAN (R 4.3.1)
spatstat.sparse 3.0-2 2023-06-25 [1] CRAN (R 4.3.1)
spatstat.utils 3.0-3 2023-05-09 [1] CRAN (R 4.3.1)
stringi 1.7.12 2023-01-11 [1] CRAN (R 4.3.1)
stringr 1.5.0 2022-12-02 [1] CRAN (R 4.3.1)
survival 3.5-7 2023-08-14 [1] CRAN (R 4.3.1)
tensor 1.5 2012-05-05 [1] CRAN (R 4.3.1)
tibble 3.2.1 2023-03-20 [1] CRAN (R 4.3.1)
tidyr 1.3.0 2023-01-24 [1] CRAN (R 4.3.1)
tidyselect 1.2.0 2022-10-10 [1] CRAN (R 4.3.1)
utf8 1.2.4 2023-10-22 [1] CRAN (R 4.3.1)
uuid 1.1-1 2023-08-17 [1] CRAN (R 4.3.1)
uwot 0.1.16 2023-06-29 [1] CRAN (R 4.3.1)
vctrs 0.6.4 2023-10-12 [1] CRAN (R 4.3.1)
viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.3.1)
withr 2.5.1 2023-09-26 [1] CRAN (R 4.3.1)
xtable 1.8-4 2019-04-21 [1] CRAN (R 4.3.1)
zoo 1.8-12 2023-04-13 [1] CRAN (R 4.3.1)
Thanks for this great tool. I was attempting to save a large dataset and came across an error right at the end of saving
` Creating h5Seurat file for version 3.1.5.9900 Adding counts for RNA Adding data for RNA No variable features found for RNA No feature-level metadata found for RNA Adding counts for hto Adding data for hto No variable features found for hto No feature-level metadata found for hto Adding counts for spliced Adding data for spliced No variable features found for spliced No feature-level metadata found for spliced Adding counts for unspliced Adding data for unspliced No variable features found for unspliced No feature-level metadata found for unspliced Adding counts for SCT Adding data for SCT Adding scale.data for SCT Adding variable features for SCT Adding feature-level metadata for SCT
Error in xgroup$create_attr(attr_name = "names", robj = intersect(x = names(x = x), : HDF5-API Errors: error #000: /home/hdftest/snapshots-hdf5_1_10_5/current/src/H5A.c in H5Acreate2(): line 279: unable to create attribute class: HDF5 major: Attribute minor: Unable to initialize object
`
Do you have any suggestions on dealing with this?
my session info is below
` R version 4.0.2 (2020-06-22) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Storage
Matrix products: default BLAS/LAPACK: /usr/lib64/libopenblas-r0.3.3.so
locale: [1] LC_CTYPE=en_DK.UTF-8 LC_NUMERIC=C [3] LC_TIME=en_DK.UTF-8 LC_COLLATE=en_DK.UTF-8 [5] LC_MONETARY=en_DK.UTF-8 LC_MESSAGES=en_DK.UTF-8 [7] LC_PAPER=en_DK.UTF-8 LC_NAME=C [9] LC_ADDRESS=C LC_TELEPHONE=C [11] LC_MEASUREMENT=en_DK.UTF-8 LC_IDENTIFICATION=C
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] SeuratDisk_0.0.0.9010 Seurat_3.2.0
loaded via a namespace (and not attached): [1] nlme_3.1-148 bit64_0.9-7.1 filelock_1.0.2 [4] RcppAnnoy_0.0.16 RColorBrewer_1.1-2 progress_1.2.2 [7] httr_1.4.2 sctransform_0.2.1 tools_4.0.2 [10] backports_1.1.8 R6_2.4.1 irlba_2.3.3 [13] rpart_4.1-15 KernSmooth_2.23-17 uwot_0.1.8 [16] mgcv_1.8-31 lazyeval_0.2.2 colorspace_1.4-1 [19] withr_2.2.0 gridExtra_2.3 tidyselect_1.1.0 [22] prettyunits_1.1.1 bit_1.1-15.2 compiler_4.0.2 [25] cli_2.0.2 hdf5r_1.3.2 plotly_4.9.2.1 [28] stringfish_0.13.3 scales_1.1.1 spatstat.data_1.4-3 [31] lmtest_0.9-37 ggridges_0.5.2 pbapply_1.4-2 [34] goftest_1.2-2 spatstat_1.64-1 stringr_1.4.0 [37] digest_0.6.25 spatstat.utils_1.17-0 txtq_0.2.3 [40] pkgconfig_2.0.3 htmltools_0.5.0 fastmap_1.0.1 [43] htmlwidgets_1.5.1 rlang_0.4.7 shiny_1.5.0 [46] generics_0.0.2 RApiSerialize_0.1.0 zoo_1.8-8 [49] drake_7.12.4 jsonlite_1.7.0 ica_1.0-2 [52] dplyr_1.0.0 magrittr_1.5 patchwork_1.0.1 [55] Matrix_1.2-18 Rcpp_1.0.5 munsell_0.5.0 [58] fansi_0.4.1 abind_1.4-5 ape_5.4 [61] reticulate_1.16 lifecycle_0.2.0 stringi_1.4.6 [64] MASS_7.3-51.6 storr_1.2.1 Rtsne_0.15 [67] plyr_1.8.6 grid_4.0.2 parallel_4.0.2 [70] listenv_0.8.0 promises_1.1.1 ggrepel_0.8.2 [73] crayon_1.3.4 deldir_0.1-28 miniUI_0.1.1.1 [76] lattice_0.20-41 cowplot_1.0.0 splines_4.0.2 [79] tensor_1.5 hms_0.5.3 pillar_1.4.6 [82] igraph_1.2.5 base64url_1.4 future.apply_1.6.0 [85] reshape2_1.4.4 codetools_0.2-16 leiden_0.3.3 [88] glue_1.4.1 data.table_1.13.0 vctrs_0.3.2 [91] png_0.1-7 httpuv_1.5.4 polyclip_1.10-0 [94] gtable_0.3.0 RANN_2.6.1 purrr_0.3.4 [97] tidyr_1.1.0 qs_0.23.2 future_1.18.0 [100] assertthat_0.2.1 ggplot2_3.3.2 rsvd_1.0.3 [103] mime_0.9 xtable_1.8-4 later_1.1.0.1 [106] survival_3.1-12 viridisLite_0.3.0 tibble_3.0.3 [109] cluster_2.1.0 globals_0.12.5 fitdistrplus_1.1-1 [112] ellipsis_0.3.1 ROCR_1.0-11 `