Package: rsahmi 0.0.2
rsahmi: Single-Cell Analysis of Host-Microbiome Interactions
A computational resource designed to accurately detect microbial nucleic acids while filtering out contaminants and false-positive taxonomic assignments from standard transcriptomic sequencing of mammalian tissues. For more details, see Ghaddar (2023) <doi:10.1038/s43588-023-00507-1>. This implementation leverages the 'polars' package for fast and systematic microbial signal recovery and denoising from host tissue genomic sequencing.
Authors:
rsahmi_0.0.2.tar.gz
rsahmi_0.0.2.tar.gz(r-4.5-noble)rsahmi_0.0.2.tar.gz(r-4.4-noble)
rsahmi_0.0.2.tgz(r-4.4-emscripten)rsahmi_0.0.2.tgz(r-4.3-emscripten)
rsahmi.pdf |rsahmi.html✨
rsahmi/json (API)
NEWS
# Install 'rsahmi' in R: |
install.packages('rsahmi', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/yunuuuu/rsahmi/issues
Last updated 20 hours agofrom:c9b1cda3b7. Checks:3 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 24 2025 |
R-4.5-linux | OK | Mar 24 2025 |
R-4.4-linux | OK | Mar 24 2025 |
Exports:blsdextract_kraken_outputextract_kraken_readsextract_taxidsparse_kraken_reportprep_datasetread_datasetremove_contaminantsslsdtaxa_counts
Dependencies:abindaskpassBHBiobaseBiocGenericsBiocParallelBiostringsbitopsblitclicodetoolscpp11crayoncurldata.tableDelayedArraydeldirformatRfutile.loggerfutile.optionsgenericsGenomeInfoDbGenomeInfoDbDataGenomicAlignmentsGenomicRangeshttrhwriterinterpIRangesjpegjsonlitelambda.rlatticelatticeExtraMASSMatrixMatrixGenericsmatrixStatsmimeopensslpngpwalignR6RColorBrewerRcppRcppEigenRhtslibrlangRsamtoolsS4ArraysS4VectorsShortReadsnowSparseArraySummarizedExperimentsysUCSC.utilswithrXVector
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Barcode level signal denoising | blsd |
Extract reads and output from Kraken | extractor extract_kraken_output extract_kraken_reads extract_taxids |
Parse kraken report file | parse_kraken_report |
Prepare kraken report, k-mer statistics, UMI data | prep_dataset read_dataset |
Identifying contaminants and false positives taxa (cell line quantile test) | remove_contaminants |
Sample level signal denoising | slsd |
Quantitation of microbes | taxa_counts |