|
CompareWilcox()
|
CompareWilcox |
|
CompareedgeRGLM()
|
Creates a summary table with the number of genes under- or overexpressed in
each group and outputs several graphical representations |
|
DA_custom()
|
Differential Analysis in 'One vs Rest' mode |
|
DA_one_vs_rest_fun()
|
Differential Analysis in 'One vs Rest' mode |
|
DA_pairwise()
|
Run differential analysis in Pairwise mode |
|
H1proportion()
|
H1proportion |
|
annotToCol2()
|
annotToCol2 |
|
annotation_from_merged_peaks()
|
Find nearest peaks of each gene and return refined annotation |
|
anocol_binary()
|
Helper binary column for anocol function |
|
anocol_categorical()
|
Helper binary column for anocol function |
|
bams_to_matrix_indexes()
|
Count bam files on interval to create count indexes |
|
beds_to_matrix_indexes()
|
Count bed files on interval to create count indexes |
|
calculate_CNA()
|
Estimate copy number alterations in cytobands |
|
calculate_cyto_mat()
|
Calculate Fraction of reads in each cytobands |
|
calculate_gain_or_loss()
|
Estimate the copy gains/loss of tumor vs normal based on log2-ratio of
fraction of reads |
|
calculate_logRatio_CNA()
|
Calculate the log2-ratio of tumor vs normal fraction of reads in
cytobands |
|
call_macs2_merge_peaks()
|
Calling MACS2 peak caller and merging resulting peaks |
|
changeRange()
|
changeRange |
|
check_correct_datamatrix()
|
Check if matrix rownames are well formated and correct if needed |
|
choose_cluster_scExp()
|
Choose a number of clusters |
|
choose_perplexity()
|
Choose perplexity depending on number of cells for Tsne |
|
col2hex()
|
Col2Hex |
|
colors_scExp()
|
Adding colors to cells & features |
|
combine_datamatrix()
|
Combine two matrices and emit warning if no regions are in common |
|
combine_enrichmentTests()
|
Run enrichment tests and combine into list |
|
concatenate_scBed_into_clusters()
|
Concatenate single-cell BED into clusters |
|
consensus_clustering_scExp()
|
Wrapper to apply ConsensusClusterPlus to scExp object |
|
correlation_and_hierarchical_clust_scExp()
|
Correlation and hierarchical clustering |
|
count_coverage()
|
Create a smoothed and normalized coverage track from a BAM file and
given a bin GenomicRanges object (same as deepTools bamCoverage) |
|
create_project_folder()
|
Create ChromSCape project folder |
|
create_sample_name_mat()
|
Create a sample name matrix |
|
create_scDataset_raw()
|
Create a simulated single cell datamatrix & cell annotation |
|
create_scExp()
|
Wrapper to create the single cell experiment from count matrix and feature
dataframe |
|
define_feature()
|
Define the features on which reads will be counted |
|
detect_samples()
|
Heuristic discovery of samples based on cell labels |
|
differential_analysis_scExp()
|
Runs differential analysis between cell clusters |
|
distPearson()
|
distPearson |
|
enrichmentTest()
|
enrichmentTest |
|
exclude_features_scExp()
|
Remove specific features (CNA, repeats) |
|
feature_annotation_scExp()
|
Add gene annotations to features |
|
filter_correlated_cell_scExp()
|
Filter lowly correlated cells |
|
filter_genes_with_refined_peak_annotation()
|
Filter genes based on peak calling refined annotation |
|
filter_scExp()
|
Filter cells and features |
|
find_top_features()
|
Find most covered features |
|
gene_set_enrichment_analysis_scExp()
|
Runs Gene Set Enrichment Analysis on genes associated with differential
features |
|
generate_analysis()
|
Generate a complete ChromSCape analysis |
|
generate_count_matrix()
|
Generate count matrix |
|
generate_coverage_tracks()
|
Generate cell cluster pseudo-bulk coverage tracks |
|
generate_feature_names()
|
Generate feature names |
|
getExperimentNames()
|
Get experiment names from a SingleCellExperiment |
|
getMainExperiment()
|
Get Main experiment of a SingleCellExperiment |
|
get_color_dataframe_from_input()
|
Get color dataframe from shiny::colorInput |
|
get_cyto_features()
|
Map features onto cytobands |
|
get_genomic_coordinates()
|
Get SingleCellExperiment's genomic coordinates |
|
get_most_variable_cyto()
|
Retrieve the cytobands with the most variable fraction of reads |
|
gg_fill_hue()
|
gg_fill_hue |
|
groupMat()
|
groupMat |
|
has_genomic_coordinates()
|
Does SingleCellExperiment has genomic coordinates in features ? |
|
hclustAnnotHeatmapPlot()
|
hclustAnnotHeatmapPlot |
|
hg38.GeneTSS
|
Data.frame of gene TSS - hg38 |
|
hg38.chromosomes
|
Data.frame of chromosome length - hg38 |
|
hg38.cytoBand
|
Data.frame of cytoBandlocation - hg38 |
|
imageCol()
|
imageCol |
|
import_count_input_files()
|
Import and count input files depending on their format |
|
import_scExp()
|
Read single-cell matrix(ces) into scExp |
|
index_peaks_barcodes_to_matrix_indexes()
|
Read index-peaks-barcodes trio files on interval to create count indexes |
|
inter_correlation_scExp()
|
Calculate inter correlation between cluster or samples |
|
intra_correlation_scExp()
|
Calculate intra correlation between cluster or samples |
|
launchApp()
|
Launch ChromSCape |
|
load_MSIGdb()
|
Load and format MSIGdb pathways using msigdbr package |
|
merge_MACS2_peaks()
|
Merge peak files from MACS2 peak caller |
|
mm10.GeneTSS
|
Data.frame of gene TSS - mm10 |
|
mm10.chromosomes
|
Data.frame of chromosome length - mm10 |
|
mm10.cytoBand
|
Data.frame of cytoBandlocation - mm10 |
|
normalize_scExp()
|
Normalize counts |
|
num_cell_after_QC_filt_scExp()
|
Table of cells before / after QC |
|
num_cell_after_cor_filt_scExp()
|
Number of cells before & after correlation filtering |
|
num_cell_before_cor_filt_scExp()
|
Table of number of cells before correlation filtering |
|
num_cell_in_cluster_scExp()
|
Number of cells in each cluster |
|
num_cell_scExp()
|
Table of cells |
|
pca_irlba_for_sparseMatrix()
|
Run sparse PCA using irlba SVD |
|
peaks_to_bins()
|
Transforms a peaks x cells count matrix into a bins x cells count matrix. |
|
plot_cluster_consensus_scExp()
|
Plot cluster consensus |
|
plot_coverage_BigWig()
|
Coverage plot using Sushi |
|
plot_differential_H1_scExp()
|
Differential H1 distribution plot |
|
plot_differential_summary_scExp()
|
Differential summary barplot |
|
plot_differential_volcano_scExp()
|
Volcano plot of differential features |
|
plot_distribution_scExp()
|
Plotting distribution of signal |
|
plot_gain_or_loss_barplots() plot_gain_or_loss_barplots()
|
Plot Gain or Loss of cytobands of the most variables cytobands |
|
plot_heatmap_scExp()
|
Plot cell correlation heatmap with annotations |
|
plot_inter_correlation_scExp()
|
Violin plot of inter-correlation distribution between one or multiple groups
and one reference group |
|
plot_intra_correlation_scExp()
|
Violin plot of intra-correlation distribution |
|
plot_most_contributing_features()
|
Plot Top/Bottom most contributing features to PCA |
|
plot_pie_most_contributing_chr()
|
Pie chart of top contribution of chromosomes in the 100 most contributing
features to PCA
#' |
|
plot_reduced_dim_scExp()
|
Plot reduced dimensions (PCA, TSNE, UMAP) |
|
plot_reduced_dim_scExp_CNA()
|
Plot UMAP colored by Gain or Loss of cytobands |
|
preprocess_CPM()
|
Preprocess scExp - Counts Per Million (CPM) |
|
preprocess_RPKM()
|
Preprocess scExp - Read per Kilobase Per Million (RPKM) |
|
preprocess_TFIDF()
|
Preprocess scExp - TF-IDF |
|
preprocess_TPM()
|
Preprocess scExp - Transcripts per Million (TPM) |
|
preprocess_feature_size_only()
|
Preprocess scExp - size only |
|
raw_counts_to_sparse_matrix()
|
Create a sparse count matrix from various format of input data. |
|
rawfile_ToBigWig()
|
rawfile_ToBigWig : reads in BAM file and write out BigWig coverage file,
normalized and smoothed |
|
read_count_mat_with_separated_chr_start_end()
|
Read a count matrix with three first columns (chr,start,end) |
|
read_sparse_matrix()
|
Read in one or multiple sparse matrices (10X format) |
|
reduce_dim_batch_correction()
|
Reduce dimension with batch corrections |
|
reduce_dims_scExp()
|
Reduce dimensions (PCA, TSNE, UMAP) |
|
remove_chr_M_fun()
|
Remove chromosome M from scExprownames |
|
remove_non_canonical_fun()
|
Remove non canonical chromosomes from scExp |
|
results_enrichmentTest()
|
Resutls of hypergeometric gene set enrichment test |
|
retrieve_top_bot_features_pca()
|
Retrieve Top and Bot most contributing features of PCA |
|
run_pairwise_tests()
|
Run pairwise tests |
|
run_tsne_scExp()
|
Run tsne on single cell experiment |
|
scExp
|
A SingleCellExperiment outputed by ChromSCape |
|
separate_BAM_into_clusters()
|
Separate BAM files into cell cluster BAM files |
|
separator_count_mat()
|
Determine Count matrix separator ("tab" or ",") |
|
smoothBin()
|
Smooth a vector of values with nb_bins left and righ values |
|
subsample_scExp()
|
Subsample scExp |
|
subset_bam_call_peaks()
|
Peak calling on cell clusters |
|
swapAltExp_sameColData()
|
Swap main & alternative Experiments, with fixed colData |
|
table_enriched_genes_scExp()
|
Creates table of enriched genes sets |
|
warning_DA()
|
Warning for differential_analysis_scExp |
|
warning_filter_correlated_cell_scExp()
|
warning_filter_correlated_cell_scExp |
|
warning_plot_reduced_dim_scExp()
|
A warning helper for plot_reduced_dim_scExp |
|
warning_raw_counts_to_sparse_matrix()
|
Warning for raw_counts_to_sparse_matrix |
|
wrapper_Signac_FeatureMatrix()
|
Wrapper around 'FeatureMatrix' function from Signac Package |