Package: gimap 1.0.2

Candace Savonen

gimap: Calculate Genetic Interactions for Paired CRISPR Targets

Helps find meaningful patterns in complex genetic experiments. First gimap takes data from paired CRISPR (Clustered regularly interspaced short palindromic repeats) screens that has been pre-processed to counts table of paired gRNA (guide Ribonucleic Acid) reads. The input data will have cell counts for how well cells grow (or don't grow) when different genes or pairs of genes are disabled. The output of the 'gimap' package is genetic interaction scores which are the distance between the observed CRISPR score and the expected CRISPR score. The expected CRISPR scores are what we expect for the CRISPR values to be for two unrelated genes. The further away an observed CRISPR score is from its expected score the more we suspect genetic interaction. The work in this package is based off of original research from the Alice Berger lab at Fred Hutchinson Cancer Center (2021) <doi:10.1016/j.celrep.2021.109597>.

Authors:Candace Savonen [aut, cre], Phoebe Parrish [aut], Kate Isaac [aut], Howard Baek [aut], Daniel Grosso [aut], Siobhan O'Brien [aut], Alice Berger [aut]

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gimap.pdf |gimap.html
gimap/json (API)
NEWS

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

Bug tracker:https://github.com/fredhutch/gimap/issues

On CRAN:

6.32 score 7 scripts 284 downloads 26 exports 79 dependencies

Last updated 2 hours agofrom:6218da3289. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 19 2025
R-4.5-winOKFeb 19 2025
R-4.5-macOKFeb 19 2025
R-4.5-linuxOKFeb 19 2025
R-4.4-winOKFeb 19 2025
R-4.4-macOKFeb 19 2025
R-4.3-winOKFeb 19 2025
R-4.3-macOKFeb 19 2025

Exports:%>%calc_giexample_data_folderget_example_dataget_figsharegimap_annotategimap_filtergimap_normalizegimap_objectplot_crisprplot_exp_v_obs_scatterplot_rank_scatterplot_targets_barplot_themeplot_volcanoqc_cdfqc_constructs_countzero_barqc_cor_heatmapqc_filter_plasmidqc_filter_zerocountsqc_plasmid_histogramqc_sample_histqc_variance_histrun_qcsetup_datasupported_cell_lines

Dependencies:askpassbackportsbase64encbitbit64broombslibcachemclicliprcolorspacecpp11crayoncurldigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtablehighrhmshtmltoolshttrisobandjanitorjquerylibjsonliteknitrlabelinglatticelifecyclelubridatemagrittrMASSMatrixmemoisemgcvmimemunsellnlmeopensslpheatmappillarpkgconfigprettyunitsprogresspurrrR6rappdirsRColorBrewerreadrrlangrmarkdownsassscalessnakecasestringistringrsystibbletidyrtidyselecttimechangetinytextzdbutf8vctrsviridisLitevroomwithrxfunyaml

gimap for Timepoint Experiment

Rendered fromtimepoint-example.Rmdusingknitr::rmarkdownon Feb 19 2025.

Last update: 2025-02-19
Started: 2024-10-24

gimap for Treatment Experiment

Rendered fromtreatment_example.Rmdusingknitr::rmarkdownon Feb 19 2025.

Last update: 2025-02-19
Started: 2024-10-24

Quick Start

Rendered fromquick-start.Rmdusingknitr::rmarkdownon Feb 19 2025.

Last update: 2025-02-19
Started: 2024-10-24

Readme and manuals

Help Manual

Help pageTopics
Calculate Genetic Interaction scorescalc_gi
Download and set up DepMap CNcn_setup
Download and set up control genescrtl_genes
Default creds pathencrypt_creds_path
Get file path to an default credentials RDSexample_data_folder
Returns example data for packageget_example_data
Handler function for GET requests from Figshareget_figshare
Annotate gimap datagimap_annotate
A function to run filteringgimap_filter
Normalize Log fold changesgimap_normalize
Make an empty gimap dataset objectgimap_object
Do tests for each replicate -an internal function used by calc_gi() functiongimap_rep_stats
Get file path to an key encryption RDSkey_encrypt_creds_path
Plot CRISPR scores after normalizationplot_crispr
Expected vs Observed CRISPR Scatterplotplot_exp_v_obs_scatter
Rank plot for target-level GI scoresplot_rank_scatter
Target bar plot for CRISPR scoresplot_targets_bar
Standardized plot themeplot_theme
Volcano plot for GI scoresplot_volcano
Create a CDF for the pgRNA normalized countsqc_cdf
Create a bar graph that shows the number of replicates with a zero count for pgRNA constructs flagged by the zero count filterqc_constructs_countzero_bar
Create a correlation heatmap for the pgRNA CPMsqc_cor_heatmap
Create a filter for pgRNAs which have a low log2 CPM value for the plasmid/Day 0 sample/time pointqc_filter_plasmid
Filter out samples of zero counts Create a filter for pgRNAs which have a raw count of 0 for any sample/time # pointqc_filter_zerocounts
Create a histogram with plasmid log2 CPM values and ascertain a cutoff for low valuesqc_plasmid_histogram
Create a histogram for the pgRNA log2 CPMs, faceted by sampleqc_sample_hist
Create a histogram for the variance within replicates for each pgRNAqc_variance_hist
Run Quality Control Checksrun_qc
Making a new gimap datasetsetup_data
List the supported cell linessupported_cell_lines
Download and set up DepMap TPM datatpm_setup