
Package index
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aggregate_by_de()
- Collapse Replicates by Differential Expression
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compute_chem_descriptors()
- Compute chemical descriptors from SMILES
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compute_de_umap()
- Prepare DE-based umap
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compute_hyper_enrich_bg()
- Calculate enrichment of DE genes in a gene set Internal function
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compute_multi_de()
- Perform DE of multiple samples in a screen vs control
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compute_multi_enrichr()
- Perform enrichR-style analysis on a screen
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compute_multi_screen_profile()
- Find similarities between expression profiles with fgsea. Mitochondrial/ribosomal genes are filtered from the analysis
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compute_multiple_dose_response()
- Model Gene Dose-Response Curves Across Treatments
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compute_normalised_counts()
- Retrieve normalised counts of MAC-seq data
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compute_qc_metrics()
- Calculate QC metrics
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compute_single_de()
- Retrieve normalised counts of MAC-seq data
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compute_single_dose_response()
- Model Gene Dose-Response Curve Using drc
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compute_single_enrichr()
- Pathway enrichment analysis
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compute_smiles()
- Annotate tidyseurat object with SMILES
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convert_human_to_mouse()
- For a given gene set of human symbols return mouse symbols
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download_geneset()
- Title
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filter_genes_by_expression()
- Filter genes by expression and grouping
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find_clusters_de_umap()
- Calculate clusters for umap based on DE analysis
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genesets
- Pathway gene‐sets for PMMSq033
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macpie_colours
- Color palettes used by macpie
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macpie_theme()
- colour theme for macpie plots
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mini_mac
- A small example MACseq plate
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plot_counts()
- Generate a box plot to show gene expression (CPM) This is the function to generate a box plot to show CPM levels of DE genes among selected treatment samples and control samples.
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plot_de_umap()
- Plot UMAP dimensionality reduction on DE genes
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plot_distance()
- Create a distance heatmap
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plot_gene_ranks()
- Generate a knee plot A knee plot to show total number of total read counts for each gene in a given treatment group
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plot_mds()
- Plot MDS dimensionality reduction
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plot_metadata_heatmap()
- Generate Heatmaps of Metadata Function
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plot_multi_de()
- Generate heatmap of DE genes from multiple treatments This is the function to generate a heatmap of DE genes from running compute_multi_DE that shared by more than one treatment group. There are a few options available to help you to extract shared DE genes.
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plot_multi_screen_profile()
- Plot multi-screen profile from fgsea results
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plot_plate_layout()
- Plot MAC-seq data on a plate layout
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plot_qc_metrics()
- Create a lollipop chart
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plot_qc_metrics_heatmap()
- Create a heatmap for multiple QC metrics
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plot_rle()
- Create an RLE Plot
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plot_volcano()
- Volcano plot of differentially expressed genes
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read_metadata()
- Read Metadata from a File
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summarise_de()
- Generate a table to summarise gene numbers from a differential expression test.
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validate_metadata()
- Check and clean the metadata file generated from findmetadata function