Documentation / Cohort Analysis / Creating a Study

Creating and Maintaining a Study

Create a Study when multiple samples need to be interpreted as one defined cohort. The initial setup fixes the Study name, sequencing type, and clinical scope; sample membership can continue to change afterward.

Initial Setup

Enter a clear Study name. When an XLSX manifest is selected, Folklore can derive an initial name from the filename, which you can edit.

Select WES, WGS, or CES to describe the sequencing data in the Study.

Choose the clinical profile and screening panel, or add explicitly scoped genes where supported.

Review the manifest before starting the linked batch. A Study can exist even if subsequent batch ingestion fails, so verify the Study sample list after processing.

A Gene Scope Is Required for Analysis

The production analysis resolves genes from the Study screening panel unless an explicit gene list is supplied. A Study without either cannot start cohort analysis. Select the intended panel during setup and review it whenever the Study question changes.

Ways to Add Samples

Method	When to Use It	What Happens Next
Study manifest	Create a new Study and linked processing batch from the Folklore XLSX manifest.	Samples are uploaded and processed through the linked batch workflow.
Upload Files	Add VCF files from your computer to an existing Study.	Each uploaded sample runs through Variant Analysis and screening with the Study panel.
Import from MEGA	Select sample folders or files from configured MEGA storage.	Files are downloaded and processed through Variant Analysis and Study screening.
Import Sessions	Reuse compatible completed Folklore analyses.	Existing classification is retained and the sample is re-screened with the Study panel.
Upload Manifest	Register sample metadata from CSV or TSV using sample_id and vcf_filename columns.	The manifest maps samples to their expected VCF filenames; it does not itself upload the VCF files.

Sample Metadata

Every sample requires a unique sample ID. Import flows can also record sex, age, and clinical subgroup. The CSV or TSV metadata manifest requires sample_id and vcf_filename; optional values include sex, age, and subgroup.

Use pseudonymous identifiers and include only metadata necessary for the Study. Clinical subgroup labels should be defined consistently before analysis rather than inferred after inspecting results.

Keep Samples Comparable

Use the same reference genome and compatible contig naming across samples.

Avoid combining materially different capture designs, calling pipelines, or quality filters without accounting for the technical batch.

Check that sample IDs match the intended individuals and are not duplicated.

Define case, control, and clinical-subgroup membership before interpreting cohort differences.

Review per-sample processing and QC status before treating the matrix as complete.

Living-Cohort Behavior

Samples can be added while the Study is active, failed samples can be retried, and samples can be removed from the active cohort. Because carrier counts, allele frequencies, outlier statistics, and gene-level results depend on membership, rerun the analysis after a membership change before using the results clinically.

Removing a sample marks it as removed from the Study workflow. Deleting the entire Study is a separate operation and can be blocked while linked batch processing is still running.