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License: Other
Reconstruction of higher order chromatin from scRNA-seq and scATAC-seq
License: Other
Hi,
trying to figure out how to start from the standard scATAC object generated and annotated using Seurat/Signac.
Does compartmap have the ability to use those as input? There is no existing conversion method for Seurat/Signac to RangedSummarizedExperiment.
Thank you!
Figures are important and having a script to regenerate them might be more important.
We pretend to have some unit tests, but actually need to add them for possible edge cases. This becomes particularly relevant when we start working out of core.
Dense matrices are nice, but large-scale single-cell experiments don't play nicely.
Push all the API changes into bioc-devel for the version to be associated with the paper. This also means that we need to have a version freeze for the paper.
Update vignette to use latest functions and note deprecated functions/wrappers (e.g. getCompartments).
Hi,
When I use the vignette example or the example in getArrayABsignal there are several errors:
library(compartmap)
data("meth_array_450k_chr14", package = "compartmap")
array_compartments <- getArrayABsignal(array.data.chr14, parallel=F, chr="chr14", bootstrap=F, genome="hg19", array.type="hm450")
Loading required package: minfi
Loading required package: bumphunter
Loading required package: foreach
Loading required package: iterators
Loading required package: locfit
locfit 1.5-9.1 2013-03-22
Setting options('download.file.method.GEOquery'='auto')
Setting options('GEOquery.inmemory.gpl'=FALSE)
Attaching package: ‘minfi’
The following object is masked from ‘package:bsseq’:
getMeth
Filtering to open sea CpG loci...
Converting to squeezed M-values.
Imputing missing values.
Dropping samples with >80% NAs.
Imputing missing data with kNN.
Cluster size 3384 broken into 2771 613
Cluster size 2771 broken into 1052 1719
Done cluster 1052
Cluster size 1719 broken into 476 1243
Done cluster 476
Done cluster 1243
Done cluster 1719
Done cluster 2771
Done cluster 613
Working on naive.1
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on rTreg.2
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on act_naive.3
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on naive.4
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on act_naive.5
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on act_rTreg.6
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on naive.7
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on rTreg.8
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on act_naive.9
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on act_rTreg.10
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Working on birth.11
Computing compartments for chr14
Calculating correlations...
Done...
Calculating eigenvectors.
Smoothing eigenvector.
Done smoothing.
Error in as(objects[[1L]], "CompressedGRangesList", strict = FALSE) :
no method or default for coercing “SimpleGRangesList” to “CompressedGRangesList”
# In addition when I use
array_compartments <- getCompartments(array.data.chr14, type = "array", parallel = FALSE, chrs = "chr14")
Error in getCompartments(arrau.data.ch14, type = "array", parallel = FALSE, :
could not find function "getComparments"
sessionInfo()
R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 18.10
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.3.3.so
locale:
[1] LC_CTYPE=fr_FR.UTF-8 LC_NUMERIC=C LC_TIME=fr_FR.UTF-8 LC_COLLATE=fr_FR.UTF-8
[5] LC_MONETARY=fr_FR.UTF-8 LC_MESSAGES=fr_FR.UTF-8 LC_PAPER=fr_FR.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=fr_FR.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats4 stats graphics grDevices utils datasets methods base
other attached packages:
[1] minfi_1.31.1 bumphunter_1.27.0
[3] locfit_1.5-9.1 iterators_1.0.12
[5] foreach_1.4.7 compartmap_1.65.6
[7] bsseq_1.21.1 BiocSingular_1.1.5
[9] BSgenome.Mmusculus.UCSC.mm9_1.4.0 Mus.musculus_1.3.1
[11] TxDb.Mmusculus.UCSC.mm10.knownGene_3.4.7 org.Mm.eg.db_3.8.2
[13] BSgenome.Hsapiens.UCSC.hg38_1.4.1 BSgenome_1.53.2
[15] rtracklayer_1.45.5 Biostrings_2.53.2
[17] XVector_0.25.0 Homo.sapiens_1.3.1
[19] TxDb.Hsapiens.UCSC.hg19.knownGene_3.2.2 org.Hs.eg.db_3.8.2
[21] GO.db_3.8.2 OrganismDbi_1.27.1
[23] GenomicFeatures_1.37.4 AnnotationDbi_1.47.1
[25] RaggedExperiment_1.9.1 SummarizedExperiment_1.15.8
[27] DelayedArray_0.11.4 BiocParallel_1.19.2
[29] matrixStats_0.54.0 Biobase_2.45.1
[31] GenomicRanges_1.37.15 GenomeInfoDb_1.21.1
[33] IRanges_2.19.14 S4Vectors_0.23.21
[35] BiocGenerics_0.31.5
loaded via a namespace (and not attached):
[1] backports_1.1.4 BiocFileCache_1.9.1 plyr_1.8.4 igraph_1.2.4.1
[5] lazyeval_0.2.2 splines_3.6.1 ggplot2_3.2.1 digest_0.6.20
[9] viridis_0.5.1 magrittr_1.5 memoise_1.1.0 limma_3.41.15
[13] readr_1.3.1 annotate_1.63.0 R.utils_2.9.0 askpass_1.1
[17] siggenes_1.59.0 prettyunits_1.0.2 colorspace_1.4-1 blob_1.2.0
[21] rappdirs_0.3.1 dplyr_0.8.3 crayon_1.3.4 RCurl_1.95-4.12
[25] graph_1.63.0 genefilter_1.67.1 GEOquery_2.53.0 zeallot_0.1.0
[29] impute_1.59.0 survival_2.44-1.1 glue_1.3.1 registry_0.5-1
[33] gtable_0.3.0 zlibbioc_1.31.0 Rhdf5lib_1.7.4 HDF5Array_1.13.5
[37] scales_1.0.0 DBI_1.0.0 rngtools_1.4 bibtex_0.4.2
[41] Rcpp_1.0.2 viridisLite_0.3.0 xtable_1.8-4 progress_1.2.2
[45] bit_1.1-14 rsvd_1.0.2 mclust_5.4.5 preprocessCore_1.47.1
[49] httr_1.4.1 RColorBrewer_1.1-2 pkgconfig_2.0.2 reshape_0.8.8
[53] XML_3.98-1.20 R.methodsS3_1.7.1 dbplyr_1.4.2 tidyselect_0.2.5
[57] rlang_0.4.0 munsell_0.5.0 tools_3.6.1 RSQLite_2.1.2
[61] stringr_1.4.0 bit64_0.9-7 beanplot_1.2 scrime_1.3.5
[65] purrr_0.3.2 RANN_2.6.1 nlme_3.1-141 pbapply_1.4-2
[69] RBGL_1.61.0 doRNG_1.7.1 nor1mix_1.3-0 R.oo_1.22.0
[73] xml2_1.2.2 biomaRt_2.41.8 compiler_3.6.1 rstudioapi_0.10
[77] curl_4.0 tibble_2.1.3 stringi_1.4.3 lattice_0.20-38
[81] Matrix_1.2-17 permute_0.9-5 multtest_2.41.0 vctrs_0.2.0
[85] pillar_1.4.2 BiocManager_1.30.4 data.table_1.12.2 bitops_1.0-6
[89] irlba_2.3.3 R6_2.4.0 gridExtra_2.3 codetools_0.2-16
[93] MASS_7.3-51.4 gtools_3.8.1 assertthat_0.2.1 rhdf5_2.29.0
[97] openssl_1.4.1 pkgmaker_0.27 withr_2.1.2 GenomicAlignments_1.21.5
[101] Rsamtools_2.1.4 GenomeInfoDbData_1.2.1 hms_0.5.1 quadprog_1.5-7
[105] grid_3.6.1 tidyr_0.8.3 base64_2.0 DelayedMatrixStats_1.7.1
[109] illuminaio_0.27.1
Could you help me ?
Best,
A
While trying to replicate this function, I noticed two cases which might cause issues:
T <- nrow(.data)
Correct me if I am wrong, but it is not clear if defining a variable using the T letter (same as the abbreviation for TRUE) would pose problems later on as T variable is heavily used in the calculation. Maybe rename it to NR?
lambdas.cleaned <- c(val, rep(1, M))
lambdas.cleaned <- c(val, rep(0, M))
maybe cause problems on the handle of output (e.g. in a temporal setting), as they give consistently different lengths of eigenvalue vector. Maybe something like:
lambdas.cleaned <- c(val, rep(1, M-length(val)))
would be more preferred?
Use the valr package as a template for package down and incorporate the draft logo.
logo_draft2.pdf
This is a TODO and really needs to be done for full functionality. Reason for removing it initially is that the pre-print didn't focus on methylation data, but follow-up results do.
I would love to be able to have CI working to check for things that may be breaking changes. Also, it would be excellent to have it be able to run BiocCheck, etc. with the existing devel R version and BioC packages.
What it says on the tin. Remove any dead code that is not being used or called in any way.
Just wondering if this is compatible to MM285 array dataset processed from SeSaMe?
There is a breaking change for flogit and fexpit made that only impacts the arrays. Will reconcile and update here.
Hello,
I am not sure whether you are aware that the Bioconductor check fails on Linux x86_64 and aarch64 with:
* checking data for non-ASCII characters ... WARNING
Error loading dataset 'k562_scatac_chr14':
Error in .requirePackage(package) :
unable to find required package 'csaw'
Error loading dataset 'ss3_umi_sce':
Error in .requirePackage(package) :
unable to find required package 'SingleCellExperiment'
The dataset(s) may use package(s) not declared in Depends/Imports.
* checking data for ASCII and uncompressed saves ... OK
* checking files in ‘vignettes’ ... OK
* checking examples ... OK
Examples with CPU (user + system) or elapsed time > 5s
user system elapsed
scCompartments 81.621 1.832 83.454
getDenoisedMatrix 7.197 0.272 7.468
* checking for unstated dependencies in vignettes ... OK
* checking package vignettes in ‘inst/doc’ ... OK
* checking running R code from vignettes ...
‘compartmap_vignette.Rmd’ using ‘UTF-8’... OK
NONE
* checking re-building of vignette outputs ... ERROR
Error(s) in re-building vignettes:
...
--- re-building ‘compartmap_vignette.Rmd’ using rmarkdown
Quitting from lines 2-16 (compartmap_vignette.Rmd)
Error: processing vignette 'compartmap_vignette.Rmd' failed with diagnostics:
there is no package called 'BiocStyle'
--- failed re-building ‘compartmap_vignette.Rmd’
SUMMARY: processing the following file failed:
‘compartmap_vignette.Rmd’
Error: Vignette re-building failed.
Execution halted
This is useful for a variety of reasons, notwithstanding the missing velocity inference.
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