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I'm doing a project for DNA archival storage systems

Is there an open-source dataset used as ground truth for clustering?

E.g

A file containing the ground truth strand sequences, which have been synthesized:

Dataset 1
st1: ATGCGTGC
st2: GCTGATTC
st3: AATGCGTT

And another file containing the sequenced strands, where for each original strand we read multiple 'erroneous' strands:

Dataset 2
st1 cluster:
ATTCTTGC
TTGCGTGC
ATGCGTGT

st2 cluster:
GCTGATTC
GATGAATC
GCAGATTA

st3 cluster:
AATGCGTT
ATTGCTTT
AATATGTT

Where the clusters can then be used for a consensus alignment algorithm.

What I'm aiming to do is to use an algorithm to learn a mapping from dataset1 to dataset2, so that for an arbitrary strand (stx) I can generate a corresponding 'erroneous' cluster (stx cluster)

The two datasets should come from a real synthesis and sequencing pipeline.

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  • $\begingroup$ I could be misunderstanding the question, but shouldn't just about any barcoded multiplexed sequencing run have this property (in the index read)? How many sequences do you want in your dataset 1? how long should they be? what are the sequencing technologies you are targeting? error models vary dramatically from technology to technology. $\endgroup$
    – Maximilian Press
    Oct 21, 2020 at 22:11

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