Find a workflow by the comparison, measurements and study structure you have. Each route states what it accepts and which claims it can support; the design determines eligibility.
Treatment versus control in two independent groups. Student’s t-test runs from input matching to the supported claim and a shareable Record—or Welch’s t-test when you don’t want to assume equal variances, with its approximation shown separately.
Check workflow conditions for Compare two group means. →The same animals or samples measured at two time points. Pairs are matched by ID, never by row order, and the differences are computed from the original values before a paired t-test.
Check workflow conditions for Compare before and after. →Control plus several treatments in one study. A one-way ANOVA answers “is there any difference?” and pre-specified comparisons, with a correction for making several of them, answer “which planned comparisons differ?”.
Check workflow conditions for Compare three or more groups. →When the question is about ranks rather than means, the Mann–Whitney U test compares two independent groups and states exactly which hypothesis it tested.
Check workflow conditions for Compare groups using ranks. →Test all your planned outcomes together with a pre-specified correction, so one lucky result can’t pass as a finding. Every outcome stays in the report, significant or not.
Check workflow conditions for Evaluate several measurements. →From a gene-level count table and sample sheet to differential-expression results through one fixed pipeline. Filtering, normalization, testing, and false-discovery control stay traceable—and are rechecked after a correction.
Check workflow conditions for Analyze bulk RNA‑seq expression. →Keep the planned samples and failure reasons on record and analyze the values actually measured, with the sample count handled correctly.
Check workflow conditions for Account for measurements lost to equipment failure. →Estimate one treatment effect across three experiment days, each day counting equally, with every day-by-group cell visible.
Check workflow conditions for Compare treatment and control across three fixed batches. →Compare a published summary—for example, values read from a figure—with your replication’s individual data, keeping each source’s type and precision.
Check workflow conditions for Compare an original study with a replication. →Run a two-stage study with one pre-fixed interim decision while keeping the overall false-positive rate under control.
Check workflow conditions for Plan two opportunities to continue or stop. →Explore freely, lock in one candidate, and test it on independent confirmation data.
Check workflow conditions for Explore, then confirm. →| Your study | Look for |
|---|---|
| Different individuals in two groups | An independent-group comparison. |
| The same individuals measured twice | An ID-matched paired comparison. |
| Several groups or planned outcomes | The relevant group comparison and multiplicity rules. |
| Counts, batches, replication or staged decisions | The corresponding fixed workflow and its input conditions. |
This is a route-finding guide. Eligibility still depends on the complete design and inputs; a familiar test name is not enough.
