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Sorry again Baoqing, I cannot answer this one. I am still working on getting the example from the publication to work, and I am trying to back everything up right now before I finish that.
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Thanks a lot!
I will also keep working on mine and keep this post updated periodically.Comment
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Ok, problem solved.
Two things need to be considered
1 when name your samples "alphabet+ numbers" always help！
2 In case of error, you need to delete cuffData.db in the folder before re-run it.Comment
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What do you mean Baoqing when you say, "2. In case of error, you need to delete cuffData.db in the folder before re-run it."?
I didn't do #1 at first and had problems. So I re-ran the cuffdiff command with alphabet+numbers, and got the error message, "Error in .local(object, x, y, logMode, pseudocount, labels, smooth, ...) :"
What command do I use to "delete the cuffData.db"?
Thank you!Comment
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Are you saying, delete cuffData.db in linux or R?Comment
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Okay. Got it. I needed to delete the cuffData.db in linux before I ran the cuffdiff command again. Thank you.Comment
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sorry for the late response. can you at least load the library?
i found that if you had tried to read your data before the library properly loaded, the generated cuffData.db is going to intervene your next new run. you can just going into the directory and delete it, i was using R in my ubuntu.Comment
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Data variability is still an issue in sequencing technologies despite the advances in reproducibility and accuracy of these platforms. But the problem does not originate in the sequencing itself, but in the previous steps, before the sample reaches the sequencer.
The first step is collection, followed by preservation and sample preparation for analysis. Most scientists overlook those steps, but not being careful might just be skewing the experiment’s results.
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