<p>I have a fastq file that somehow has a mix of DNA and RNA. It's the sequence data of a DNA sample, but I found one interesting gene that has much higher coverage in exons than in introns. I used STAR to re-perform the alignment, and saw the clear exon-intron-exon pattern in the reads in IGV. So I suspect that there is RNA contamination in this sample.</p>
<p>This is whole-genome sequencing data. We used bwa at the beginning, and then STAR to check the exon-intron pattern. The library was prepared according the common DNA library kit's manual, as this was prepared by a company.</p>
<p>In order to estimate whether it is indeed a whole-genome RNA contamination in this sample and how much contamination there is in this sample, I want to estimate how many genes have RNA sequences aligned. I thought to use a splice-aware mapping tool to do the mapping, and then extract records that have gaps in them by filtering the CIGAR score for N. But I then realized that this may not be accurate, because alignment is performed against the reference genome and not the genome of the individual who was sequenced. If I filter the CIGAR score for N, I would also include the reads that bear large deletions in their own genome compared to the reference genome, even if it's DNA sequences.</p>
<p>So now I can't think of a way to screen the genes which have RNA sequences aligned. Without extracting the RNA reads, I also can't track where the RNA contamination come from, whether it's from our own sample or from the sequencing facility.</p>
<p>Another method I could think of is to filter the genes by their very different coverages of reads. But I also don't have a clear idea on how to do it.</p>
<p>So could anyone help me a bit here how to extract RNA reads or how to screen genes that have RNA reads aligned?</p>

CC BY-SA 4.0
2024-08-26T13:25:25.620Z
Some IGV screenshots would certainly help. Isolating reads from RNA could be tough, any chance you can resequence the sample?
Karthik Nair
CC BY-SA 4.0
2024-08-27T08:28:52.363Z
@KarthikNair We're trying to avoid resequencing, because we actually have a whole population that has similar problems.
jypst2003
CC BY-SA 4.0
2024-08-27T12:09:45.267Z
Couldn't you simply map against the transcriptome and then filter for alignments that are not split reads and of high quality? Essentially, if there is notable RNA contamination (hard to believe since RNA is fragile in the presence of RNases which you have abundantly when you break open a cell using a non RNA-tailored buffer) -- then you should have lots of exon-exon junctions covered.
ATpoint
<ngs><rna-alignment><dna>
Extracting RNA reads alignments from a mix of DNA and RNA alignments
# Extracting RNA reads alignments from a mix of DNA and RNA alignments

(Asked by: username_0 on 2024-08-26)

I have a fastq file that somehow has a mix of DNA and RNA. It's the sequence data of a DNA sample, but I found one interesting gene that has much higher coverage in exons than in introns. I used STAR to re-perform the alignment, and saw the clear exon-intron-exon pattern in the reads in IGV. So I suspect that there is RNA contamination in this sample.

This is whole-genome sequencing data. We used bwa at the beginning, and then STAR to check the exon-intron pattern. The library was prepared according the common DNA library kit's manual, as this was prepared by a company.

In order to estimate whether it is indeed a whole-genome RNA contamination in this sample and how much contamination there is in this sample, I want to estimate how many genes have RNA sequences aligned. I thought to use a splice-aware mapping tool to do the mapping, and then extract records that have gaps in them by filtering the CIGAR score for N. But I then realized that this may not be accurate, because alignment is performed against the reference genome and not the genome of the individual who was sequenced. If I filter the CIGAR score for N, I would also include the reads that bear large deletions in their own genome compared to the reference genome, even if it's DNA sequences.

So now I can't think of a way to screen the genes which have RNA sequences aligned. Without extracting the RNA reads, I also can't track where the RNA contamination come from, whether it's from our own sample or from the sequencing facility.

Another method I could think of is to filter the genes by their very different coverages of reads. But I also don't have a clear idea on how to do it.

So could anyone help me a bit here how to extract RNA reads or how to screen genes that have RNA reads aligned?

**Tags:** ngs, rna-alignment, dna
> **Comments:**
> **username_1**: Some IGV screenshots would certainly help. Isolating reads from RNA could be tough, any chance you can resequence the sample?  
> **username_0**: @KarthikNair We're trying to avoid resequencing, because we actually have a whole population that has similar problems.  
> **username_2**: Couldn't you simply map against the transcriptome and then filter for alignments that are not split reads and of high quality? Essentially, if there is notable RNA contamination (hard to believe since RNA is fragile in the presence of RNases which you have abundantly when you break open a cell using a non RNA-tailored buffer) -- then you should have lots of exon-exon junctions covered.  

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## 0 answers

