Genome-Wide CRISPR Library Screening Service

Can: which genes, among thousands, change a phenotype you can select or sort on.

Cannot: the mechanism for any individual hit, whether a hit is on-target in your cell type, or whether the effect holds at physiological expression.

Most disappointing screens are disappointing because the question was mechanistic and the method was discovery.

The second and third rows decide everything downstream. A subtle phenotype with a distant readout will return noise no matter how large the library.

We report the measured MOI and the fraction of singly integrated cells rather than nominal values.

• • Ranked gene list with guide-level statistics, not only gene-level scores
• • Per-gene guide concordance and a flag for genes with inconsistent guides
• • Library and day-0 QC: guide distribution, missing-guide fraction, coverage at each bottleneck
• • Positive-control performance, so the screen's sensitivity is visible
• • A validation plan for the top hits, with recommended individual assays

The last item matters: a hit list without a validation path is a hypothesis catalogue.

Longer selection windows increase sensitivity for subtle growth effects and increase the risk of adaptation artefacts.

• • Essential genes are detected as dropout; their mechanism is not.
• • Subtle phenotypes require more cells, not more guides.
• • Non-proliferative phenotypes need a sorting or reporter readout, which changes the design and the timeline.
• • Hits are hypotheses until individually validated — we recommend budgeting for that step from the start.

Genome-wide or focused library?Genome-wide for discovery when the readout is strong; focused when the phenotype is subtle or when budget supports depth over breadth. A focused library at high coverage usually outperforms a genome-wide one at the margin.

How many hits will validate?That depends on the readout, not on the library. Screens with a strong, mechanism-adjacent readout validate most top hits; screens with a distal phenotype validate few. We state which kind of screen yours is before starting.

Do you validate the hits?Optionally, as a second phase. We recommend budgeting for it, because the validation is what converts a list into a finding.

Tell us the cell type, the phenotype and how you would measure it in a single cell or well. We will tell you whether a pooled screen is the right instrument, and if not, what is.

Contact EDITGENE to request a project consultation or quote.

Screen performance depends on cell type, doubling time, readout distance, and library quality; parameter ranges here are planning guidance.

Screen hits require individual validation before any mechanistic claim, and guide-level data should be reported alongside gene-level scores.

• • Shalem O, et al. Genome-scale CRISPR-Cas9 knockout screening in human cells. Science. 2014;343:84–87.
• • Hart T, et al. Evaluation and design of genome-wide CRISPR/SpCas9 knockout screens. G3. 2017;7:2719–2727.
• • Doench JG. Am I ready for CRISPR? A user's guide to genetic screens. Nature Reviews Genetics. 2018;19:67–80.