path / save_path / output.dir is
provided.eset_distribution(),
find_outlier_samples(), iobr_cor_plot(),
sig_pheatmap(), sig_box_batch(),
plotPurity(), IPS_calculation(),
find_mutations(), sig_gsea(),
get_cor(), batch_sig_surv_plot(),
format_signatures(), and creat_folder().tempdir() when file writing is
demonstrated.find_mutations(): Fixed semantic
naming error where file_name variable was used to store
directory paths. Renamed to output_dir for clarity. Fixed
ggsave() parameter order issues.iobr_cor_plot(): Fixed
ggsave() parameter order issues. The correct order is
filename first, then plot.surv_group(): Fixed
ggsave() parameter order issues.roc_time(): Fixed
ggsave() parameter order issues.batch_sig_surv_plot(): Changed default
save_path from
file.path(tempdir(), "Multiple-KM-plot") to
NULL to prevent automatic directory creation.format_signatures(): Changed parameter
name from output_name to output_path for
consistency. Added validation requiring output_path when
save_signature = TRUE.find_outlier_samples(): Added
validation requiring project when
save = TRUE.plotPurity(): Changed default
output.dir from "estimated_purity_plots" to
NULL.R/sysdata.rda and data/ to GitHub
Releases to meet CRAN package size requirements. Data is now downloaded
on-demand and cached locally.load_data() function for unified data access
(supports sysdata, exported data, and GitHub-hosted datasets)download_iobr_data() with multiple mirror support
(GitHub, ghproxy.vip, gh-proxy.org, ghfast.top)add_iobr_mirror() for custom mirror
configurationlist_github_datasets() to show available remote
datasetsclear_iobr_cache() to manage downloaded datacount2tpm() to handle symbol-based gene IDs more
robustly.The following datasets are now hosted on GitHub and downloaded on
first use: - Reference matrices: BRef, TRef,
lm22 - Annotations: anno_gc_vm32,
anno_grch38, anno_hug133plus2,
anno_illumina, anno_rnaseq - Example datasets:
tcga_stad_sig, imvigor210_sig,
eset_stad, sig_stad,
eset_gse62254, etc. - Gene sets: hallmark,
kegg, go_bp, go_cc,
go_mf, reactome, msig_immune,
msig_sc - Cell markers: cancer_type_genes,
cellmarkers, common_genes,
immuneCuratedData, ips_gene_set,
SI_geneset, mRNA_cell_default,
mus_human_gene_symbol, onco_sig,
PurityDataAffy - Reference data: xCell.data,
quantiseq_data - Signatures:
signature_collection_citation,
signature_metabolism, signature_sc,
signature_tumor
load_data() instead of
direct object references for migrated datasetsglobalVariables.R to reflect data
migrationghcr.io/iobr/iobr). The image is
based on rocker/tidyverse and includes IOBR with all
dependencies pre-installed (#Docker).iobr_cor_plot() to support multi-group (3+)
comparisons using Kruskal-Wallis test, in addition to the existing
two-group Wilcoxon test (#28).generateRef_DEseq2() to handle sparse single-cell
RNA-seq data by using type = "poscounts" for size factor
estimation, preventing errors when all genes contain at least one
zero.batch_kruskal() output format to correctly
display mean-centered values for all groups.count2tpm() computation results to align with
previous correct versions.count2tpm() documentation to clarify that gene
identifiers are converted to gene symbols in the output regardless of
input ID type.\dontrun{} and
\donttest{} to comply with CRAN check time limits.count2tpm.R for
better code organization and maintainability.load_data() documentation to include additional
available datasets.