Sorting screen tutorial without reporter edits

Screens without editing outcome, where each gRNA is assigned to a target.

Library design Each guide RNA (or other perturbation such as ORF) has a specified target.
Selection Cells are sorted based on FACS signal quantiles
sorting_bins



Here, we consider an example where BEAN uses the external count without reporter, gRNA and sample information to infer the per-target effect sizes.

Example workflow

screen_id=var_mini_screen_noedit
working_dir=tests/data/

# 1. Given that we have gRNA count for each sample, generate ReporterScreen (.h5ad) object for downstream analysis.
bean create-screen ${working_dir}/gRNA_info.csv ${working_dir}/sample_list.csv ${working_dir}/var_mini_counts.csv -o ${working_dir}/${screen_id}

# 2. QC samples & guides
bean qc \
  ${working_dir}/${screen_id}.h5ad             `# Input ReporterScreen .h5ad file path` \
  -o ${working_dir}/${screen_id}_masked.h5ad   `# Output ReporterScreen .h5ad file path` \
  -r ${working_dir}/qc_report_${screen_id}     `# Prefix for QC report` \
  -b                                           ` # Remove replicates with no good samples.

# 3. Quantify variant effect
bean run sorting variant \
    ${working_dir}/${screen_id}_masked.h5ad \
    -o ${working_dir}/ \
    --uniform-edit --ignore-bcmatch            `# As we have no edit/reporter information.` \
    [--fit-negctrl [--negctrl-col target_group --negctrl-col-value NegCtrl]]                                      `# If you have the negative control gRNAs.`

Input file spec

See the example input files here.

See Subcommands for the full details.