Originally posted by beajorrin
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Advanced SeqMonk course
After promising to do this for ages I've finally finished writing an Advanced SeqMonk Course. It won't get its first official outing for a couple of weeks, but I've released the course material onto our web site so everyone can have a look.
There are a couple of things in the course which require features which won't be released until v0.21.0 - but that should be coming fairly soon now.
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Originally posted by simonandrews View PostAfter promising to do this for ages I've finally finished writing an Advanced SeqMonk Course. It won't get its first official outing for a couple of weeks, but I've released the course material onto our web site so everyone can have a look.
There are a couple of things in the course which require features which won't be released until v0.21.0 - but that should be coming fairly soon now.
That advanced course is really helpful, thanks! Do you know when use difference filter to identify differentially expressed genes, what is the appropriate interval for RNA-Seq experiments? I have four KO samples and four WT and I have calculated RPKM for all the samples. Thank you in advance!
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Originally posted by mediator View PostHi Simon,
That advanced course is really helpful, thanks! Do you know when use difference filter to identify differentially expressed genes, what is the appropriate interval for RNA-Seq experiments? I have four KO samples and four WT and I have calculated RPKM for all the samples. Thank you in advance!
In your case as you have 4 x 4 replicates you could use a combination of the replicate stats filter for a conventional statistical analysis and the intensity difference filter between the two replicate groups to determine the significant deviations from a difference from 0. Do the intensity difference filter first though since this relies on seeing the whole distribution of points.
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Originally posted by simonandrews View PostFor this type of experiment we'd recommend using the intensity difference filter rather than a straight difference filter. The intensity difference filter is a statistical filter where cutoffs are set as p-values, and we'd normally go with the default 0.05 cutoff. Details of how the filter works are in the advanced course.
In your case as you have 4 x 4 replicates you could use a combination of the replicate stats filter for a conventional statistical analysis and the intensity difference filter between the two replicate groups to determine the significant deviations from a difference from 0. Do the intensity difference filter first though since this relies on seeing the whole distribution of points.
Do you know if SeqMonk can show the exact base pairs for each reads? It will be very helpful for detecting indels and de novo mutation. Thank you!
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Originally posted by mediator View PostHi Simon,
Do you know if SeqMonk can show the exact base pairs for each reads? It will be very helpful for detecting indels and de novo mutation. Thank you!
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Originally posted by aggp11 View PostHello Simon,
Can we use SeqMonk to visualize CNVs? I know there are several tools for predicting copy number changes, but am just wondering if there is a way of visualizing these Copy Number changes using SeqMonk from NGS data.
SeqMonk should certainly be able to do this. You'd probably want to do a simple read count over tiled probes which are large enough to contain enough data to get a reliable measure of the read depth, but small enough to catch smaller deletions. There are then a number of different tools to allow you to compare different samples and find differences between samples, or outliers from the normal coverage distribution in a single sample.
This isn't something our group works on much, but we've certainly used the program to confirm targeted knockouts that we've made, so the same principles could be used to find novel deletions or duplications.
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Hi Simon,
first again lots of compliments for seqmonk, I don't feel like I can fully grasp a new RNA-seq experiment until I've viewed it in seqmonk. !
This told, I have a question, maybe trivial: is there a way to load a custom set of genes (let's say a particular class of genes) for, e.g. getting a chromosome overview of their expression and mapping over chromosomes ?
If I also can suggest an improvement, I' d like to be able to resize the sample window (e.g: If have lots of samples, I may like to focus on only one interesting sample to let also visualize fully the mapped reads; with more than 5-6 samples is hard to visualize everything and so it's better to select one or few samples (e.g. for deciphering alternative splicing claims) ... I know I can delete a sample but resizing / hiding one or more samples maybe a better solution?
thanks a lot for considering those notes !
pbseq
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Originally posted by pbseq View PostHi Simon,
first again lots of compliments for seqmonk, I don't feel like I can fully grasp a new RNA-seq experiment until I've viewed it in seqmonk. !
Originally posted by pbseq View PostThis told, I have a question, maybe trivial: is there a way to load a custom set of genes (let's say a particular class of genes) for, e.g. getting a chromosome overview of their expression and mapping over chromosomes ?
Originally posted by pbseq View PostIf I also can suggest an improvement, I' d like to be able to resize the sample window (e.g: If have lots of samples, I may like to focus on only one interesting sample to let also visualize fully the mapped reads; with more than 5-6 samples is hard to visualize everything and so it's better to select one or few samples (e.g. for deciphering alternative splicing claims) ... I know I can delete a sample but resizing / hiding one or more samples maybe a better solution?
I suspect I may be missing the point you're making though.
If you're interested in looking at alternative splicing then if you haven't seen this already then a really neat option is to import just the spliced introns into your project. If you have a spliced mapped SAM/BAM file (eg from TopHat), then if you import this and select "Split Spliced Reads" and "Import Introns rather than exons" then you'll see just the splices which you've observed. You can quantitatively analyse these by using the Read Position Probe Generator followed by the Exact Overlap Count Quantitation. We've found this way of looking at the data to be really helpful in deciding if there really is a change in the splicing pattern between samples.
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Hi Simon,
For bed file (generated by Scripture, from RNA-Seq data), which quantification pipeline would you recommend? I am trying to compare bed files between patients and healthy controls in order to find splice variants unique to patients. Thank you!
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Originally posted by mediator View PostHi Simon,
For bed file (generated by Scripture, from RNA-Seq data), which quantification pipeline would you recommend? I am trying to compare bed files between patients and healthy controls in order to find splice variants unique to patients. Thank you!
From what I can see scripture tries to create assembled transcripts from your raw data, so I guess the best way to handle this would be to import it as an annotation track rather than a data track. If the features it produces are spliced then you'd need to import them as GTF or GFFv3 files since none of the other annotation formats supported by SeqMonk can handle multi-location features.
Once you have these elements in place then you could quantitate the various scripture transcripts in your datasets and then compare these. You could use the standard RNA-Seq quantitation pipeline and follow the basic RNA-Seq methodology (I'm actually in the process of producing an improved RNA-Seq guide since we have a pretty solid way of dealing with this data now).
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