All functions |
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Tables with amino acid properties |
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Amino acid / codon table |
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Add a new class attribute to the input object. |
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Apply function to each pair of data frames from a list. |
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Nucleotide to amino acid sequence translation |
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Check that distribution is sums up to one. |
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Working with coding and non-coding clonotype sequences |
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Get a column's name using the input alias |
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Information measures |
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Make publication-ready plots |
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Gene usage |
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Analysis of gene usage |
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Gene segments table. |
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WIP |
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Kmer analysis of repertoires. |
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Get a character vector of samples' groups from the input metadata file |
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Check class |
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Immune repertoire dataset |
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Specification of the data format used by immunarch dataframes. |
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Clustering of objects or distance matrices |
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Dimensionality reduction |
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Statistical analysis of groups |
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Incremental counting of repertoire similarity |
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Search for clonotypes in external databases |
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Copy the upper matrix triangle to the lower one |
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Number of shared clonotypes. |
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Various measures for overlapping sets of objects. |
Public repertoire |
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Apply transformations to public repertoires |
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Filter out clonotypes from public repertoires |
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Statistics of number of public clonotypes for each possible combinations of repertoires |
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Get a matrix with public clonotype frequencies |
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Assess clonal proportions of repertoire |
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Estimate diversity of repertoire |
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Explore basics of repertoire |
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Load repertoire files to the workspace |
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Calculate the overlap between repertoires |
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Analysis of overlaps or any distance matrices |
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Sampling of repertoires |
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Save repertoire files to the disk. |
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Set and update progress bars |
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Analyse spectratype of immune repertoires |
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Split all-samples-in-one ImmunoSEQ files by sample |
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Kmers processing. |
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Return a column's name |
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Get the N most abundant clonotypes |
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Clonotype tracking |
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One function to visualise them all |
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Visualise diversity. |
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Visualise clonality |
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Repertoire dynamics |
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Visualise exploratory analysis. |
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Histograms and boxplots (general case / gene usage) |
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Visualisation of hierarchical clustering |
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Visualise incremental overlaps |
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Visualisation of K-means and DBSCAN clustering |
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Most frequent kmers visualisation. |
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PCA / MDS / tSNE visualisation (mainly overlap / gene usage) |
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Overlap / gene usage distance visualisation |
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Public repertoire visualisation |
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Visualise sharing of clonotypes among samples |
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Bar plots |
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Visualisation of distributions using boxplots |
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Visualisation of matrices using circos plots |
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Visualisation of matrices and data frames using ggplot2-based heatmaps |
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Visualisation of matrices using heatmap3-based heatmaps |
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Visualisation of distributions using histograms |
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Visualise kmer profiles |
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Visualisation of public clonotypes |
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Public repertoire visualisation |
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Visualisation of distance matrices with polar area plots |
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Sequence logo plots for amino acid profiles. |
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Visualisation of data frames and matrices using treemaps |