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Getting started

Quick start

Create an account and run one first analysis all the way through.

What you need

  • One contextBio account (single sign-on)
  • A browser. There is nothing to install.
  • To use AURORA the raw data must already be on the server. You cannot upload FASTQ from the screen — see step 3 below.

1. Sign in

Sign in at contextbio.ai/login. One account covers all four services — you do not register separately for each one.

After registering, you have to click the link in the verification email. Without verifying you can still sign in, but analysis and document generation are blocked.

2. Check your permissions

Signing in and permission to run are separate. If you have just created the account, ask an administrator for run permission. Without it the screens open but you are blocked at the run button.

3. Your first analysis in AURORA

Go to AURORA. If you are signed in it opens straight away.

The raw data has to be in your own account folder under the AURORA data folder on the server. If it is not there yet, ask an administrator to move the data underneath it. Then:

  1. In 새 분석 (New analysis), create a folder with 프로젝트 만들기 (Create project) and drill down to the folder holding the raw data
  2. When the samples are detected automatically, fill in the comparison group (group) in the sample metadata table
  3. Choose the data type and a pipeline preset
  4. When 실행 계획 (Run plan) in the right-hand column has no errors and 환경 점검 (Environment check) is all green, 분석 시작 (Start analysis) becomes available

If you only want to check your settings, leave the run mode on 명령어 미리보기 (Command preview). It records the commands that would run without actually running them.

The analysis keeps running if you close the window. You can find it again under 작업 현황 (Job status).

4. Read the results

Under 결과 · 리포트 (Results and reports), the first thing to look at is the 품질 검사 (QC) tab. Reading your results sets out which numbers to look at and in what order.

The report is produced even when the pipeline fails — the point is to show you how far it got.

Next

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