Package: ondisc 1.0.0
Timothy Barry
ondisc: Fast, Universal, and Intuitive Computing on Large-Scale Single-Cell Data
Single-cell datasets are growing in size, posing challenges as well as opportunities for biology researchers. 'ondisc' (short for "on-disk single cell") enables users to easily and efficiently analyze large-scale single-cell data. 'ondisc' makes computing on large-scale single-cell data FUN: Fast, Universal, and iNtuitive.
Authors:
ondisc_1.0.0.tar.gz
ondisc_1.0.0.tar.gz(r-4.5-noble)ondisc_1.0.0.tar.gz(r-4.4-noble)
ondisc.pdf |ondisc.html✨
ondisc/json (API)
| # Install 'ondisc' in R: |
| install.packages('ondisc', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/timothy-barry/ondisc/issues
Last updated 4 years agofrom:e6e8cf782d. Checks:OK: 2. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 27 2024 |
| R-4.5-linux-x86_64 | OK | Nov 27 2024 |
Exports:create_ondisc_matrix_from_mtxget_cell_barcodesget_feature_idsget_feature_namesheadmetadata_ondisc_matrixmultimodal_ondisc_matrixncolnrowondisc_matrixshow
Dependencies:bitbit64clicliprcpp11crayondata.tabledplyrfansigenericsgluehmslatticelifecyclemagrittrMatrixpillarpkgconfigprettyunitsprogressR6Rcppreadrrhdf5rhdf5filtersRhdf5librlangtibbletidyselecttzdbutf8vctrsvroomwithr
Tutorial 1: Using the ondisc_matrix class
Rendered fromtutorial_odm_class.Rmdusingknitr::rmarkdownon Nov 27 2024.Last update: 2021-03-05
Started: 2021-03-05
Tutorial 2: Using metadata_ondisc_matrix and multimodal_ondisc_matrix
Rendered fromtutorial_other_classes.Rmdusingknitr::rmarkdownon Nov 27 2024.Last update: 2021-03-05
Started: 2021-03-05
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create an 'ondisc_matrix' from a .mtx file. | create_ondisc_matrix_from_mtx |
| Get dimension | dim dim,metadata_ondisc_matrix-method dim,multimodal_ondisc_matrix-method dim,ondisc_matrix-method ncol ncol,multimodal_ondisc_matrix-method nrow nrow,multimodal_ondisc_matrix-method |
| Pull a submatrix into memory using the '[[' operator. | extract-odm [[,metadata_ondisc_matrix,ANY,ANY-method [[,multimodal_ondisc_matrix,ANY,ANY-method [[,ondisc_matrix,ANY,ANY-method [[,ondisc_matrix,ANY,missing-method [[,ondisc_matrix,missing,ANY-method [[,ondisc_matrix,missing,missing-method |
| Get cell barcodes, feature names, and feature IDs | get-names get_cell_barcodes get_cell_barcodes,metadata_ondisc_matrix-method get_cell_barcodes,multimodal_ondisc_matrix-method get_cell_barcodes,ondisc_matrix-method get_feature_ids get_feature_ids,metadata_ondisc_matrix-method get_feature_ids,multimodal_ondisc_matrix-method get_feature_ids,ondisc_matrix-method get_feature_names get_feature_names,metadata_ondisc_matrix-method get_feature_names,multimodal_ondisc_matrix-method get_feature_names,ondisc_matrix-method |
| head | head,ondisc_matrix-method |
| 'metadata_ondisc_matrix' class | metadata_ondisc_matrix |
| 'multimodal_ondisc_matrix' class | multimodal_ondisc_matrix |
| ondisc: A package for out-of-memory computing on single-cell data | ondisc |
| 'ondisc_matrix' class | ondisc_matrix |
| Print basic information to the console | show show,metadata_ondisc_matrix-method show,multimodal_ondisc_matrix-method show,ondisc_matrix-method |
| Subset using the '[' operator. | subset-odm [,metadata_ondisc_matrix,ANY,ANY,missing-method [,metadata_ondisc_matrix,ANY,missing,missing-method [,metadata_ondisc_matrix,missing,ANY,missing-method [,metadata_ondisc_matrix,missing,missing,missing-method [,multimodal_ondisc_matrix,ANY,ANY,ANY-method [,multimodal_ondisc_matrix,missing,ANY,missing-method [,multimodal_ondisc_matrix,missing,missing,missing-method [,ondisc_matrix,ANY,ANY,missing-method [,ondisc_matrix,ANY,missing,missing-method [,ondisc_matrix,missing,ANY,missing-method [,ondisc_matrix,missing,missing,missing-method |