I'm experiencing some issues with RAMPART and I'm wondering if there is a solution available. I would like to know if anyone has been able to resolve similar problems.
In our laboratory, we have been using RAMPART for some time and it has always worked well. Now, we are trying to perform amplicon sequencing of specific regions of interest, but we are unsure how to prepare the files for proper analysis and visualization.
Here are a series of images and the desired outcomes that we would like to achieve. We would like to confirm if it is possible or if we need to perform separate analyses.
The first step we took was to create the genome.json and references file containing the sequences of our target amplicons. We represented it as a continuous fasta-like sequence with Ns separating both sequences.
Looking at the output, we can see that it nicely distinguishes the two amplicons as separate peaks, separated by the manually introduced Ns. However, in the "References matches" section, it shows the total percentage with only the single fasta sequence we inputted.
I decided to modify the genome.json and references.fasta files as follows:
However, the result was not as expected. Now I only see a continuous peak without distinguishing the different amplicons. Although the "references matches" section provided exactly what I needed, merging the files by using the genome.json from the first step and the references.fasta from the second step did not change the result.
Even with the inclusion of Ns in the genome.json file to manually separate the two amplicons, it still didn't work as expected. The manual separation attempt did not produce the desired result.
Could anyone let me know if they have achieved the desired outcome or have any ideas on how to accomplish it?
Thank you very much in advance, any help or idea is welcome.
Hello!
I'm experiencing some issues with RAMPART and I'm wondering if there is a solution available. I would like to know if anyone has been able to resolve similar problems.
In our laboratory, we have been using RAMPART for some time and it has always worked well. Now, we are trying to perform amplicon sequencing of specific regions of interest, but we are unsure how to prepare the files for proper analysis and visualization.
Here are a series of images and the desired outcomes that we would like to achieve. We would like to confirm if it is possible or if we need to perform separate analyses.
The first step we took was to create the genome.json and references file containing the sequences of our target amplicons. We represented it as a continuous fasta-like sequence with Ns separating both sequences.
Genome.json: { "label": "Amplicon Set", "length": XXX, "reference": { "label": "Amplicons", "accession": "Amplicons", "sequence": "sequence1NNNNNNNNNNNNNNNNNNNNsequence2" } }
References.fasta:
Looking at the output, we can see that it nicely distinguishes the two amplicons as separate peaks, separated by the manually introduced Ns. However, in the "References matches" section, it shows the total percentage with only the single fasta sequence we inputted.
I decided to modify the genome.json and references.fasta files as follows:
Genome.json:
{ "label": "Amplicons Abscessus/Chimaera", "length": (length_sequence1 + length_sequence2), "Amplicon1": { "label": "sequence1", "accession": "sequence1", "sequence": "CAAGTAGCCGTCAACGACATCGGCTCGGCCGAGGATTTTCTCGCCGCTATCGACAAGACGATCAAGTACTTCAACGATGGCGACATCGTCGAAGGGACCATCGTCAAGGTTGACCGCGACGAAGTTCTTCTTGACATCGGTTACAAGACCGAAGGTGTCATCCCGTCCCGCGAGCTCTCGATCAAGCACGA" }, "Amplicon2": { "label": "sequence2", "accession": "sequence2", "sequence": "CAAGTAGCCGTCAACGACATTGGCTCCAGCGAGGACTTTCTCGCCGCAATAGACAAAACGATCAAGTACTTCAACGATGGCGACATCGTCGAGGGCACGATCGTCAAAGTGGACCGGGACGAGGTGCTCCTCGACATCGGCTACAAGACCGAGGGGGTCATCCCCGCCCGCGAGCTCTCGATCAAGCACGA" } }
References.fasta:
However, the result was not as expected. Now I only see a continuous peak without distinguishing the different amplicons. Although the "references matches" section provided exactly what I needed, merging the files by using the genome.json from the first step and the references.fasta from the second step did not change the result.
Even with the inclusion of Ns in the genome.json file to manually separate the two amplicons, it still didn't work as expected. The manual separation attempt did not produce the desired result.
Could anyone let me know if they have achieved the desired outcome or have any ideas on how to accomplish it?
Thank you very much in advance, any help or idea is welcome.