Package index
-
metaXpressmetaXpress-package - metaXpress: End-to-End Bulk RNA-seq Meta-Analysis
-
metaXpressStudy-class - The metaXpressStudy class
-
metaXpressStudy() - Construct a metaXpressStudy
-
mx_from_se() - Convert a SummarizedExperiment to a metaXpressStudy
-
metaXpressResult-class - The metaXpressResult class
-
show(<metaXpressStudy>) - Display a metaXpressStudy object
-
show(<metaXpressResult>) - Display a metaXpressResult object
Module 1: Ingestion & Quality Control
Fetch studies from GEO/SRA, evaluate 10-point QC criteria, and filter datasets.
-
mx_fetch_geo() - Fetch bulk RNA-seq studies from GEO
-
mx_fetch_sra() - Fetch raw RNA-seq data from SRA
-
mx_load_local() - Load user-supplied count matrices as metaXpressStudy objects
-
mx_qc_study() - Score a study against the 10-point QC checklist
-
mx_filter_studies() - Remove studies that fail quality control
-
mx_cluster_samples() - Suggest sample groups from metadata text
-
mx_study_overview() - Study characteristics overview plot
Module 2: Normalization & Cross-Study Harmonization
Reannotate gene IDs, harmonize library types, correct batch effects, and align gene spaces.
-
mx_reannotate() - Reannotate gene IDs to a common namespace
-
mx_normalize() - Normalize counts within a single study
-
mx_correct_library_type() - Correct for library type bias (polyA vs rRNA-depleted)
-
mx_remove_batch() - Remove between-study batch effects for pooled expression analyses
-
mx_align_genes() - Restrict all studies to a common set of genes
Module 3: Per-Study Differential Expression
Perform independent differential expression using DESeq2, edgeR, or limma-voom.
-
mx_de() - Run differential expression analysis on a single study
-
mx_de_all() - Run differential expression on all studies
-
mx_de_summary() - Summarise per-study DE results
Module 4: Meta-Analysis Statistics
Random-effects (REML/PM/DL, HKSJ) and fixed-effect models, directional p-value combination, heterogeneity, concordance and leave-one-out robustness.
-
mx_meta() - Run meta-analysis across per-study DE results
-
mx_study_concordance() - Check fold-change concordance between studies
-
mx_heterogeneity() - Compute per-gene heterogeneity statistics
-
mx_sensitivity() - Leave-one-out sensitivity analysis
-
mx_small_study() - Small-study effects and publication bias tests
Module 5: Missing Gene Handling
Identify missingness patterns across studies and apply imputation or coverage filtering.
-
mx_impute() - Impute missing gene statistics across studies
-
mx_filter_coverage() - Filter genes by minimum study coverage
-
mx_missing_summary() - Summarise gene coverage across studies
Module 6: Pathway Meta-Analysis
fgsea GSEA and ORA on the meta-signature, per-study GSEA combined across studies, consensus and redundancy filtering.
-
mx_gene_sets() - Retrieve gene sets from MSigDB
-
mx_pathway_meta() - Pathway enrichment of meta-analysis results
-
mx_pathway_studies() - Cross-study pathway meta-analysis
-
mx_pathway_consensus() - Find consensus pathways across studies (vote counting)
-
mx_pathway_dedup() - Remove redundant pathways
-
mx_pathway_heatmap() - Cross-study pathway heatmap
Module 7: Visualization
Publication-grade plots including volcano plots, forest plots, heatmaps, and UpSet diagrams.
-
mx_volcano() - Meta-analysis volcano plot
-
mx_forest() - Forest plot for a single gene
-
mx_heatmap() - Heatmap of top DEGs across studies
-
mx_upset() - UpSet plot of DEG overlap across studies
-
mx_heterogeneity_plot() - I-squared distribution plot
-
mx_funnel() - Funnel plot for one gene
Module 8: Reporting & Export
Generate reproducible HTML/PDF reports and export meta-analysis results.
-
mx_report() - Generate a reproducible analysis report
-
mx_export() - Export meta-analysis results to file
-
mx_session_info() - Capture session information for reproducibility
Module 9: Downstream Biology
Turn the meta-signature into biology: TF activity, cell composition, co-expression modules and drug reversal.
-
mx_tf_activity() - Infer transcription factor activity from the meta-signature
-
mx_cell_composition() - Meta-analyse cell-type composition shifts across studies
-
mx_coexpression_modules() - Find consensus co-expression modules across studies
-
mx_drug_connectivity() - Rank drugs by how strongly they reverse the meta-signature
-
mx_read_signatures() - Read up/down drug signatures from a gene set library
-
mx_downstream_plot() - Plot downstream biology results