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This pipeline is a copy of the pipeline on bitbucket with additions about how to use this pipelines for human cells. based on the following: https://bitbucket.org/tychoCanterCremers/batch-ge_pipeline/src/master/

What is this repository for?

  • Genotyping SNPpanel using MIPS pipeline Nijmegen
  • Input needed:
    • Illumins SampleSheet.csv: samples with "smMIPS" as Sample_project will be used, rest will be ignored
    • Design 70mer file
    • SNPpanel in VCF format

How do I set it up and run it?

  • Copy 'localconfiguration.example.xml' to 'localconfiguration.xml' inside the repo and fill in the necessary info
  • Then run the main script: perl run.MIPS.pl
  • Dependencies (defined in mainconfiguration.xml):
    • bwa, cutadapt v.1.15, java, GATK v3.5, Python3.6 (installed on cluster)
  • Set up to run as cronjob

Missense mutation = desired edit:

Example:

Human (GRCh38.p13): CACNA1Cc.989C>T

  • Transcript: CACNA1C-204 ENST00000347598.9

  • Chr12 2493262 = mutation site

Adapted Batch-GE “zebrafish script”

  • To provide:

    • Genome for reference

      • e.g.: “GRCh38/hg38”
  • Genomic Region Of Interest (ROI) – unique per sgRNA

    • mutation site in the middle

    • add 10-15nt down- or upstream from cut site (related to sgRNA)

    • add 10-15nt down- or upstream from mutation site

    • Total length = max 40nt

    • e.g.: chr12 2493244 - 2493277

  • Repair sequence:

    • = desired mutation; presence is required to count as knock-in (KI) read

    • ( ) = silent mutations; presence is optional to count as KI read

    • | = cut site (as example): CAGTGCCAGAA(T)G|G(A)A[T]GGTGTGCAAGCC

    • Final repair sequence e.g.: CAGTGCCAGAA(T)GG(A)A[T]GGTGTGCAAGCC

  • When script is finished => output_mail.txt

    • Each row contains: Sample_ID; total_reads; InDel reads; KI reads

Small insertion or deletion (max 50bp) = desired edit:

After Batch_GE “zebrafish_script” use "Variants.INS.Seq.annotated" and "output_mail.txt" to run cardio_zebrafishpipeline/BATCH-GE_intended_INS_finder/src/BATCH-GE_INS_finder.py, more information and a README about this script can be found in the same directory.

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This pipeline is a copy of the pipeline on bitbucket with additions about how to use this pipelines for human cells.

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