User: graeme.thorn
graeme.thorn • 40
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- 3 years, 12 months ago
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Posts by graeme.thorn
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... Do you want to put that in an answer? I've come to the same conclusion: col4 is read name, col5 is strand (there's about ~5m '+' and ~5m '-' in this file), which is meaningless for ChIP-seq. ...
written 6 weeks ago by
graeme.thorn • 40
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Comment:
C: Consensus reads from UMIs
... Of course, I will have to modify slightly, but this does look like the most consistent way of doing it, particularly given I need high sensitivity, and low false positives for my purposes. ...
written 7 weeks ago by
graeme.thorn • 40
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... I have DNA-seq data from a 30-gene capture panel, with UMIs in the FASTQ header for each read. This panel is for variant detection in tissue and cell-free DNA samples with a high coverage (>1000X) and the UMIs will help in removing duplicates from sequencing the same fragment of DNA multiple time ...
written 9 weeks ago by
graeme.thorn • 40
• updated
9 weeks ago by
finswimmer ♦ 12k
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... I am getting (target) mapping rates of between 13% (from a particularly degraded sample) and 40%. Is this normal for such an experiment? I have no experience in this (previous work being on whole genome, whole exome or RNA sequencing) so I have no intuition as to whether this is a good rate or not ...
written 12 weeks ago by
graeme.thorn • 40
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... Except that with short reads (70bp) and few sequences (30), there are many more locations in the genome that they can map to which is not part of the target, so that answer really does not apply. If I were doing all exons captured or >10K as in that previous answer, then I would do whole genome m ...
written 12 weeks ago by
graeme.thorn • 40
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... I want to map samples (70bp paired-end) to a 30-gene panel using BWA (mem). They were generated using a capture kit so should have few if any off-target reads.
Should I map the reads to the whole genome and just filter on the gene panel, or just restrict mapping to those genes (+- some margin, say ...
written 12 weeks ago by
graeme.thorn • 40
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... It was more whether to run through varscan (or equivalent) all at once, leading to calls I think are incorrect like the one above, or whether to run the (single) normal v each serial plasma sample in pairs, so N v P1, N v P2, N v P3, N v P4 etc... then join the variants together as you suggest. ...
written 3 months ago by
graeme.thorn • 40
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... It was more whether to run through varscan (or equivalent) all at once, leading to calls I think are incorrect like the one above, or whether to run the (single) normal v each serial plasma sample in pairs, so N v P1, N v P2, N v P3, N v P4 etc... then join the variants together as you suggest. ...
written 3 months ago by
graeme.thorn • 40
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... I'm wondering what the best procedure for calling serial plasma samples from the same patients with a single normal sample would be.
For instance, running the samtools-mpileup-varscan2 pipeline with the normal sample first and the serial samples after gives genotype calls of 0/0 when I'd expect a ...
written 3 months ago by
graeme.thorn • 40
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... I am analysing some cell-free DNA samples (in the hope of finding variants from circulating tumour DNA) and I am aware of the problems with trying to call variants on such fragmentary DNA data. However, this paper: https://www.nature.com/articles/nature12065 (Murtaza et al, 2013, Non-invasive analy ...
written 4 months ago by
graeme.thorn • 40
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