gimap1.1.2 package

Calculate Genetic Interactions for Paired CRISPR Targets

calc_gi

Calculate Genetic Interaction scores

check_internet_available

Check if internet/URL is available

cn_setup

Download and set up DepMap CN

ctrl_genes

Download and set up control genes

delete_annotation

Refresh the annotation files by redownloading them

delete_example_data

Refresh the example data files by redownloading them

encrypt_creds_path

Default creds path

example_data_folder

Get file path to an default credentials RDS

get_example_data

Returns example data for package

get_figshare

Handler function for GET requests from Figshare

gimap_annotate

Annotate gimap data

gimap_filter

A function to run filtering

gimap_normalize

Normalize Log fold changes

gimap_object

Make an empty gimap dataset object

gimap_stats

Do tests --an internal function used by calc_gi() function

key_encrypt_creds_path

Get file path to an key encryption RDS

pipe

Pipe operator

plot_crispr

Plot CRISPR scores after normalization

plot_exp_v_obs_scatter

Expected vs Observed CRISPR Scatterplot

plot_rank_scatter

Rank plot for target-level GI scores

plot_targets

Target bar plot for CRISPR scores

plot_theme

Standardized plot theme

plot_volcano

Volcano plot for GI scores

qc_cdf

Create a CDF for the pgRNA normalized counts

qc_constructs_countzero_bar

Create a bar graph that shows the number of replicates with a zero cou...

qc_cor_heatmap

Create a correlation heatmap for the pgRNA CPMs

qc_filter_plasmid

Create a filter for pgRNAs which have a low log2 CPM value for the pla...

qc_filter_zerocounts

Filter out samples of zero counts Create a filter for pgRNAs which hav...

qc_plasmid_histogram

Create a histogram with plasmid log2 CPM values and ascertain a cutoff...

qc_sample_hist

Create a histogram for the pgRNA log2 CPMs, faceted by sample

qc_variance_hist

Create a histogram for the variance within replicates for each pgRNA

run_qc

Run Quality Control Checks

save_example_timepoint_data

Set up example count data

save_example_treatment_data

Set up example count data

setup_data

Making a new gimap dataset

supported_cell_lines

List the supported cell lines

tpm_setup

Download and set up DepMap TPM data

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>.

  • Maintainer: Candace Savonen
  • License: GPL-3
  • Last published: 2026-02-05