Package: ISAnalytics 1.23.1

Francesco Gazzo

ISAnalytics: Analyze gene therapy vector insertion sites data identified from genomics next generation sequencing reads for clonal tracking studies

In gene therapy, stem cells are modified using viral vectors to deliver the therapeutic transgene and replace functional properties since the genetic modification is stable and inherited in all cell progeny. The retrieval and mapping of the sequences flanking the virus-host DNA junctions allows the identification of insertion sites (IS), essential for monitoring the evolution of genetically modified cells in vivo. A comprehensive toolkit for the analysis of IS is required to foster clonal trackign studies and supporting the assessment of safety and long term efficacy in vivo. This package is aimed at (1) supporting automation of IS workflow, (2) performing base and advance analysis for IS tracking (clonal abundance, clonal expansions and statistics for insertional mutagenesis, etc.), (3) providing basic biology insights of transduced stem cells in vivo.

Authors:Francesco Gazzo [cre], Giulia Pais [aut], Andrea Calabria [aut], Giulio Spinozzi [aut]

ISAnalytics_1.23.1.tar.gz
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ISAnalytics_1.23.1.tgz(r-4.6-any)ISAnalytics_1.23.1.tgz(r-4.5-any)
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manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
ISAnalytics/json (API)

# Install 'ISAnalytics' in R:
install.packages('ISAnalytics', repos = c('https://bioc.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/calabrialab/isanalytics/issues

Pkgdown/docs site:https://calabrialab.github.io

Datasets:

On BioConductor:ISAnalytics-1.23.0(bioc 3.24)ISAnalytics-1.22.0(bioc 3.23)

biomedicalinformaticssequencingsinglecellcellbiologyfunctionalgenomicsdataimport

6.30 score 3 stars 22 scripts 363 downloads 83 exports 109 dependencies

Last updated from:95bfaf0d66. Checks:1 WARNING, 9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
bioc-checksWARNING209
linux-devel-x86_64OK537
source / vignettesOK353
linux-release-x86_64OK526
macos-release-arm64OK401
macos-oldrel-arm64OK253
windows-develOK523
windows-releaseOK519
windows-oldrelOK488
wasm-releaseOK195

Exports:aggregate_metadataaggregate_values_by_keyannotation_IS_varsannotation_issuesas_sparse_matrixassociation_file_columnsavailable_outlier_testsavailable_tagsblood_lineages_defaultcircos_genomic_densityCIS_grubbsCIS_grubbs_overtimeCIS_volcano_plotclinical_relevant_suspicious_genescomparison_matrixcompute_abundancecompute_near_integrationscumulative_count_unioncumulative_isdate_formatsdefault_af_transformdefault_iss_file_prefixesdefault_meta_aggdefault_rec_agg_lambdasdefault_report_pathdefault_statsenable_progress_barsexport_ISA_settingsfisher_scatterplotgene_frequency_fishergenerate_blank_association_filegenerate_default_folder_structuregenerate_Vispa2_launch_AFHSC_population_plotHSC_population_size_estimateimport_association_fileimport_ISA_settingsimport_parallel_Vispa2Matricesimport_parallel_Vispa2Matrices_autoimport_parallel_Vispa2Matrices_interactiveimport_single_Vispa2Matriximport_Vispa2_statsinspect_tagsintegration_alluvial_plotis_sharingiss_sourceiss_stats_specsknown_clinical_oncogenesmandatory_IS_varsmatching_optionsmatrix_file_suffixesNGSdataExploreroutlier_filteroutliers_by_pool_fragmentspcr_id_columnpurity_filterquantification_typesrealign_after_collisionsreduced_AF_columnsrefGene_table_colsremove_collisionsreset_af_columns_defreset_annotation_IS_varsreset_dyn_vars_configreset_iss_stats_specsreset_mandatory_IS_varsreset_matrix_file_suffixessample_statisticsseparate_quant_matricesset_af_columns_defset_annotation_IS_varsset_iss_stats_specsset_mandatory_IS_varsset_matrix_file_suffixessharing_heatmapsharing_vennthreshold_filtertop_abund_tableGrobtop_cis_overtime_heatmaptop_integrationstop_targeted_genestransform_columnsunzip_file_system

Dependencies:base64encbitbit64bslibcachemcellrangerclassclassIntclicliprclustercommonmarkcpp11crayoncrosstalkcurldata.tabledatamodsdigestdplyrDTe1071evaluatefarverfastmapfontawesomeforcatsforeignfsgenericsggplot2ggrepelgluegtablehavenhighrhmshtmltoolshtmlwidgetshttpuvisobandjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelazyevallifecyclelubridatemagrittrMASSMatrixmemoisemgcvmimenlmeotelpermutephosphoriconspillarpkgconfigprettyunitsprogresspromisesproxypurrrR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppreactablereactRreadrreadxlrematchriorlangrmarkdownS7sassscalesshinyshinybusyshinyWidgetssourcetoolsstringistringrtibbletidyrtidyselecttimechangetinytextoastuitzdbutf8vctrsveganviridisLitevroomwithrwritexlxfunxtableyaml

Setting up the workflow and first steps
Introduction | Setting up your workflow with dynamic vars | General approach | Tags | Mandatory IS vars | Annotation IS vars | Association file columns | VISPA2 stats specs | Customizing dynamic vars | FAQs | Do I have to do this every time the package loads? | Reporting progress | Introduction to ISAnalytics import functions family | Designed to work with VISPA2 pipeline | File system structure generated | Notation | Importing metadata | Function arguments | Importing VISPA2 stats files | Importing a single integration matrix | Automated integration matrices import | association_file argument | quantification_type argument | matrix_type argument | workers argument | multi_quant_matrix argument | report_path argument | mode argument | patterns argument | matching_opt argument | ... argument | Notes | Data cleaning and pre-processing | Removing collisions | What is a collision and why should you care? | The logic behind the function | Identifying the collisions | Re-assign vs remove | Usage | Re-align other matrices | Performing data and metadata aggregation | Aggregating metadata | Typical workflow | Aggregation of values by key | Changing parameters to obtain different results | Analysis use-case example: shared integration sites | Automated sharing counts | SCENARIO 1: single input data frame and single grouping key | Changing the number of comparisons | A case when it is useful to set minimal = FALSE | SCENARIO 2: single input data frame and multiple grouping keys | SCENARIO 3: multiple input data frame and single grouping key | SCENARIO 4: multiple input data frame and multiple grouping keys | Plotting sharing results | Reproducibility | Bibliography
Rendered fromworkflow_start.Rmdusingknitr::rmarkdown

Last update: 2026-07-16
Started: 2022-04-21

Getting started with ISAnalytics
Introduction | Installation and options | Installation from bioconductor | Installation from GitHub | Setting options | Setting up the workflow | The first steps | Data cleaning and pre-processing | Answering biological questions | Working with other kinds of data | Using the Shiny interface | Ensuring reproducibility of results | Browse documentation online and keep updated | Problems? | Reproducibility | Bibliography
Rendered fromISAnalytics.Rmdusingknitr::rmarkdown

Last update: 2025-07-21
Started: 2022-04-20

Readme and manuals

Help Manual

Help pageTopics
Performs aggregation on metadata contained in the association file.aggregate_metadata
Aggregates matrices values based on specified key.aggregate_values_by_key
Check for genomic annotation problems in IS matrices.annotation_issues
Converts tidy integration matrices in the original sparse matrix form.as_sparse_matrix
Example of association file.association_file
A character vector containing all the names of the currently supported outliers tests that can be called in the function outlier_filter.available_outlier_tests
All available tags for dynamic vars look-up tables.available_tags
Default blood lineages infoblood_lineages_default
Trace a circos plot of genomic densities.circos_genomic_density
Grubbs test for Common Insertion Sites (CIS).CIS_grubbs
Compute CIS and Grubbs test over different time points and groups.CIS_grubbs_overtime
Trace volcano plot for computed CIS data.CIS_volcano_plot
Clinical relevant suspicious genes (for mouse and human).clinical_relevant_suspicious_genes
Obtain a single integration matrix from individual quantification matrices.comparison_matrix
Computes the abundance for every integration event in the input data frame.compute_abundance
Scans input matrix to find and merge near integration sites.compute_near_integrations
Expands integration matrix with the cumulative IS union over time.cumulative_is
Possible choices for the 'dates_format' parameter in 'import_association_file', 'import_parallel_vispa2Matrices_interactive' and 'import_parallel_vispa2Matrices_auto'.date_formats
Default transformations to apply to association file columns.default_af_transform
Default regex prefixes for Vispa2 stats files.default_iss_file_prefixes
Default metadata aggregation function tabledefault_meta_agg
Defaults for column aggregations in 'compute_near_integrations()'.default_rec_agg_lambdas
Default folder for saving ISAnalytics reports. Supplied as default argument for several functions.default_report_path
A set of pre-defined functions for 'sample_statistics'.default_stats
Enable global progress bars for ISAnalytics functions.enable_progress_bars
Export a dynamic vars settings profile.export_ISA_settings
Plot results of gene frequency Fisher's exact test.fisher_scatterplot
Compute Fisher's exact test on gene frequencies.gene_frequency_fisher
Create a blank association file.generate_blank_association_file
Generate a default folder structure, following VISPA2 standardsgenerate_default_folder_structure
Creates a reduced association file for a VISPA2 run, given project and poolgenerate_Vispa2_launch_AF
Plot of the estimated HSC population size for each patient.HSC_population_plot
Hematopoietic stem cells population size estimate.HSC_population_size_estimate
Import the association file from diskimport_association_file
Import a dynamic vars settings profile.import_ISA_settings
Import integration matrices from paths in the association file.import_parallel_Vispa2Matrices
Import a single integration matrix from fileimport_single_Vispa2Matrix
Import Vispa2 stats given the aligned association file.import_Vispa2_stats
Retrieve description of a tag by name.inspect_tags
Alluvial plots for IS distribution in time.integration_alluvial_plot
Example of imported multi-quantification integration matrices.integration_matrices
Sharing of integration sites between given groups.is_sharing
Find the source of IS by evaluating sharing.iss_source
Known clinical oncogenes (for mouse and human).known_clinical_oncogenes
Current dynamic vars specifications getters.annotation_IS_vars association_file_columns iss_stats_specs mandatory_IS_vars matrix_file_suffixes vars_getters
Possible choices for the 'matching_opt' parameter.matching_options
Launch the shiny application NGSdataExplorer.NGSdataExplorer
Filter out outliers in metadata, identified by the chosen outlier test.outlier_filter
Identify and flag outliers based on pool fragments.outliers_by_pool_fragments
Easily retrieve the name of the pcr id column.pcr_id_column
Data frames for proto-oncogenes (human and mouse) and tumor-suppressor genes from UniProt.proto_oncogenes tumor_suppressors
Filter integration sites based on purity.purity_filter
Possible choices for the 'quantification_type' parameter.quantification_types
Re-aligns matrices of other quantification types based on the processed sequence count matrix.realign_after_collisions
Names of the columns of the association file to consider for Vispa2 launch.reduced_AF_columns
Required columns for refGene file.refGene_table_cols
Gene annotation files for hg19, mm9.refGenes_hg19 refGenes_mm9
Reference gene annotation for hg38 or mm10.refGenes_hg38 refGenes_mm10
Identifies and removes collisionsremove_collisions
Resets dynamic vars to the default values.reset_af_columns_def reset_annotation_IS_vars reset_dyn_vars_config reset_iss_stats_specs reset_mandatory_IS_vars reset_matrix_file_suffixes vars_resetters
Computes user specified functions on numerical columns and updates the metadata data frame accordingly.sample_statistics
Separate a multiple-quantification matrix into single quantification matrices.separate_quant_matrices
Define custom dynamic vars.set_af_columns_def set_annotation_IS_vars set_iss_stats_specs set_mandatory_IS_vars vars_setters
Sets the look-up table for matrix file suffixes.set_matrix_file_suffixes
Plot IS sharing heatmaps.sharing_heatmap
Produce tables to plot sharing venn or euler diagrams.sharing_venn
Summary top abundant tableGrobs for plots.top_abund_tableGrob
Heatmaps for the top N common insertion sites over time.top_cis_overtime_heatmap
Sorts and keeps the top n integration sites based on the values in a given column.top_integrations
Top n targeted genes based on number of IS.top_targeted_genes
Apply transformations to an arbitrary number of columns.transform_columns