Skip to contents
bambamR 0.1.0
New features
- Initial release of bambamR.
-
Data import:
bb_read_fastq() and bb_read_bam() with ShortRead/Rsamtools or base-R/system-samtools fallback.
-
Quality control:
bb_qc(), bb_qc_summary(), and bb_plot_qc() for per-read quality, GC content, and read-length distributions.
-
Alignment:
bb_align() wrapping STAR, HISAT2, and minimap2.
-
Read counting:
bb_count_reads() via GenomicAlignments or featureCounts.
-
Normalization:
bb_normalize() supporting CPM, TPM (base R), TMM (edgeR), and RLE (DESeq2).
-
Differential expression:
bb_deseq2(), bb_edger(), and bb_limma_voom() returning standardized result data.frames.
-
Visualization:
bb_oncoplot(), bb_volcano(), bb_heatmap(), bb_pca(), bb_ma_plot() — all return ggplot2 objects.
-
Pipeline orchestrator:
bb_pipeline() runs the full analysis from FASTQ, BAM, or count matrix to plots in a single call.
-
Export:
bb_export_csv(), bb_export_tsv(), bb_export_rds().
-
Shiny app:
bb_run_app() launches an interactive analysis dashboard.
-
Example data:
bb_example_counts(), bb_example_mutations(), and bb_example_de() provide bundled datasets for exploring all features.
- Two operating modes: minimal (CRAN-only) and full (+ Bioconductor). All Bioconductor dependencies are optional and checked at runtime.
