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Old 01-01-2017, 08:52 AM   #1
wylde3161
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Default amount of reads

How does lowering the amount of reads in RNA-seq or in resequencing experiment different in the way it effects the results? Does it affect these two application in the same way
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Old 01-01-2017, 08:58 AM   #2
wylde3161
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Default many reads are enough to sequence per sample

i have the following question and i really need help with it:

A researcher is about to sequence 50 tomato mRNA samples in order to understand the developmental process of the young plant. The researcher wants to have a good estimate on how many reads she needs to sequence in each sample in order to get a good measure of the gene expression in each sample. The researcher has a limited budget and so she want to sequence the minimal amount of reads that will give her meaningful results. She has a set of 10 genes she expects to see expressed in all samples in a moderate expression level.
Suggest an experiment/ experiments that will help a researcher decide how many reads are enough to sequence per sample. You can assume you have unlimited amounts of each sample.
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Old 01-01-2017, 09:02 AM   #3
Brian Bushnell
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When you post a homework question, please note that it is for homework.
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Old 01-02-2017, 11:13 PM   #4
gringer
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Quote:
Suggest an experiment/ experiments that will help a researcher decide how many reads are enough to sequence per sample. You can assume you have unlimited amounts of each sample.
Said no researchers ever.

Anyway, my recommendation would be to do a low coverage pilot run on all 50 samples on a single lane of a HiSeq (assuming samples can be normalised to be sufficiently equally distributed for sequencing), then re-run those samples that don't have sufficient depth in the target genes. The pilot run will give an idea of what proportion of the next run each sample will need to be for sufficient depth.
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Old 01-03-2017, 05:19 AM   #5
avierstr
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This publication investigated the correlation between sequencing depth and outcome accuracy:

Gene. 2015 Feb 15;557(1):82-7. doi: 10.1016/j.gene.2014.12.013. Epub 2014 Dec 10.
Diminishing returns in next-generation sequencing (NGS) transcriptome data.
Lei, Ye, Gu, Sun.
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