SeqMonk: Visualisation and analysis for large mapped data sets

[mathew]

I am using seq monk for RNA-seq analysis and am looking for following question:

1. in Version 24 when I go to feature probe generator-feature to design around attenuator, what is this related to?
2. I see mRNA option is not there, so now if I have to design probes for mRNA what should be equivalent.
3. I am working on RNA-seq of bacteria do I need to still import as split reads?


Thanks

[simonandrews]

Originally Posted by mathew

I am using seq monk for RNA-seq analysis and am looking for following question:

1. in Version 24 when I go to feature probe generator-feature to design around attenuator, what is this related to?
2. I see mRNA option is not there, so now if I have to design probes for mRNA what should be equivalent.
3. I am working on RNA-seq of bacteria do I need to still import as split reads?

Hi Matthew,

The RNA-Seq quantitation pipeline tries to guess which of your annotation tracks is appropriate to use for RNA analysis. If there is an mRNA track available then it will suggest that, but if there isn't one (which is what it sounds like in your case) then it will just use the first track (which I guess would be attenuator). This wouldn't be an appropriate track to use so you'd need to select something more suitable.

It's odd that there isn't an mRNA track in your genome. Is this one of our core genomes or something you've imported yourself? If it's a bacterium you might need to use ORF, CDS or maybe something like operon as the basis for your analysis.

When you import your data you should always use the split reads option, even if you're working on bacterial data. You won't have any splice sites, but selecting this option will also set other options which ensure that your imported data is formatted appropriately for RNA-Seq quantitation.

Hope this helps

Simon.

[mathew]

Can Seqmonk map probes in intergenic region. To be more precise Can it help me in giving read counts in noncoding RNA directly/ indirectly?
Thanks.

[simonandrews]

Originally Posted by mathew

Can Seqmonk map probes in intergenic region. To be more precise Can it help me in giving read counts in noncoding RNA directly/ indirectly?
Thanks.

Yes, it can put probes wherever you need them, either by using one of the existing feature tracks or you can import your own set of positions.

For intergenic regions for example you could put probes over genes and then use the interstitial probe generator to make intergenic probes.

You could go one step further and put probes over all exons (select mRNA and split into subfeatures). You could then make interstitial probes from these to get a mixed set of introns and intergenic. You could then separate these by selecting for an overlap with genes to select the subgroup you want.

For noncoding RNA there are a number of tracks already available which might be of use (miRNA, snoRNA etc) or if you want a set of coordinates you want to use you can import these into a new feature track and then use these as the basis for probe design.

If you can let me know more specifically what you're trying to do I can try to give you more exact suggestions.

[mathew]

Thanks Simon,

Will it include specifically long noncoding RNA?

[simonandrews]

Originally Posted by mathew

Will it include specifically long noncoding RNA?

The linc RNAs aren't split out into a separate track in the current genomes, but they are annotated so you can make up a custom track containing just these features.

In the feature search tool (Edit > Find Feature) do a search for 'lincRNA' in all of mRNA features which should bring up a list of all of these features. You can then use the option to save all of these hits as a new annotation track which will give you a specific track you can use for quantitation, or you can quantitate everything and then filter against these features later on.

[honey]

I sit possible to bring rpkm values calculated outside seqmonk and import in as txt file. Will it allow me to use the downstream analysis steps like clustering etc. or not. Another question I have if i am importing as txt file I dont see which column I can specify RPKM values?
Thanks

[simonandrews]

Originally Posted by honey

I sit possible to bring rpkm values calculated outside seqmonk and import in as txt file. Will it allow me to use the downstream analysis steps like clustering etc. or not. Another question I have if i am importing as txt file I dont see which column I can specify RPKM values?
Thanks

You can't import pre-quantitated data into SeqMonk. It's designed to take in raw mapped data and do the quantitation within the program. If you really want to you can calculate RPKM values within the program - but generally you really don't want to do that - simply normalising per million reads of input is often not very good measure of total data and leaves systematic differences between samples. Likewise, correcting for transcript length is OK if you need to compare expression levels between genes in the same sample, but if you're comparing between samples you normally don't want to do this.

[mathew]

I have a RNA seq data from a bacteria. I was wondering if I can design (quantitate) probes for intergenic regions? Or is there an alternative way of extracting that information from seqmonk?

Thanks

[simonandrews]

Originally Posted by mathew

I have a RNA seq data from a bacteria. I was wondering if I can design (quantitate) probes for intergenic regions?

You can do this fairly easily. Firstly use the feature probe generator to make probes over genes. Then go back and use the interstitial probe generator to make probes between the current probe set. This should give you a set of intergenic probes which you can then take forward for whatever quantitation you want to do.

[crazyhottommy]

Hi Simon,

I got a problem when I imported the bam file into SeqMonk, after reading all the lines, and saying caching...
the Data sets did not show up in the "Data Sets" panel on the left menu.

I tried another bam file, and it worked fine for me. Apparently, it was my bam file somehow not recognized by Seqmonk.

I downloaded the sra file from NCBI sequence read archive, and then converted it to bam file by
using sam-dump in the sra tool kit combined with samtools :

sam-dump SRR390728 | samtools view -bS -o my_bam.bam -

one error I got is
[samopen] no @SQ lines in the header.
[sam_read1] missing header? Abort!

So, I first just converted the sra file to sam file and took a look by "head", and it does lack the header
like:
@SQ SN:chr1 LN:249250621
@SQ SN:chr2 LN:243199373


So, I just cut the headers from a sam file that contain them and "cat" it with my sam file.

But SeqMonk still can not cache the data.

Do you have an idea why?

Thanks!

[simonandrews]

If SeqMonk is not showing a newly imported track at all then that's because it wasn't able to import any data from the file. This could either be because it hit a fatal error which stopped the import, or because it found no valid reads in the file (either it was empty, or every read had a non-fatal error which meant it was skipped).

In either case you should get either an error window, or a set of warnings which say why the import failed. If you can say what error (if any) you get then we can try to figure out why it's not importing.

If it's easier, if you can put your BAM file somewhere I can see it I can try to import it and see exactly what's happening.

[crazyhottommy]

Originally Posted by simonandrews

If SeqMonk is not showing a newly imported track at all then that's because it wasn't able to import any data from the file. This could either be because it hit a fatal error which stopped the import, or because it found no valid reads in the file (either it was empty, or every read had a non-fatal error which meant it was skipped).

In either case you should get either an error window, or a set of warnings which say why the import failed. If you can say what error (if any) you get then we can try to figure out why it's not importing.

If it's easier, if you can put your BAM file somewhere I can see it I can try to import it and see exactly what's happening.

Hi Simon,

Thanks so much.
I figured it out by myself. it is simply just because the SRA file is not mapped. It looks
like the sra files contain raw unmapped sequences, I used fastq-dump in sra toolkit to
convert it to fastq file first. After I run bowtie and generated a SAM file with header, it then can be loaded into SeqMonk.

Thanks!!

[crazyhottommy]

Hi Simon,

I got another question about the probe list.

It looks like Seqmonk can not have multiple probe lists in the same project. when I define a new probe set, the old one will be deleted.

I know you can convert the probe list to the annotation track.
but if I want to compare ChIP-seq signal in two different probe sets, how can I do it?
say, I have a set of TSS of active genes and another set of TSS of inactive genes.


Thanks

[mathew]

I have a chipseq data where mouse mitochondria fractions are enriched However, I think mitochondrial Chr is not there in the genome when we download the genome with in Seqmonk. How can I have M genome? Is there a specific site/ M chr of mice which seqmonk can accept?
Thanks

I initially thought of starting a new link for the post but then realized all sort of question are compiled here which are relevant to Seqmonk

[honey]

I am uploading a GTF file for annotation downloaded from Encode/ Broad but when I put search term as have been mentioned in Simon's post I dont find any of search term how I would add as custom annotation from GTF file in Seqmonk.

Thanks

[simonandrews]

Originally Posted by mathew

I have a chipseq data where mouse mitochondria fractions are enriched However, I think mitochondrial Chr is not there in the genome when we download the genome with in Seqmonk. How can I have M genome? Is there a specific site/ M chr of mice which seqmonk can accept?
Thanks

I initially thought of starting a new link for the post but then realized all sort of question are compiled here which are relevant to Seqmonk

The mitochondrion is present in all of the mouse assemblies in SeqMonk (you should be able to see it in the genome view). What you might find is happening is that the mitochondrial sequences aren't being recognised because there are two different names used for the mitochrondrion (either M or MT depending on whether you're using an NCBI or Ensembl derived genome).

The Ensembl genomes (which seqmonk uses) use MT as the mitochondrion name then you'll get a warning from any M chromosome names in your BAM files and they won't import. If you want to fix this you'll need to install an aliases file so the program knows how to translate between the two names. Instructions for doing this can be found here.

Hope this helps

[simonandrews]

Originally Posted by honey

I am uploading a GTF file for annotation downloaded from Encode/ Broad but when I put search term as have been mentioned in Simon's post I dont find any of search term how I would add as custom annotation from GTF file in Seqmonk.

Importing annotation from a GTF file should be as simple as doing File > Import Annotation > GFF/GTF. You'll be asked for a prefix for the features you import so if you import genes or mRNA you can turn them into something like custom_gene or custom_mRNA so you can tell them apart from the core features for the assembly you're using.

Once the features are in you can query them and visualise them the same as any other feature track. If you're not sure which features are associated with which imported file you can right click on the annotation set in the data view and select "properties" to see a summary of the features which were imported.

If there's something more specific which isn't working then let me know some more details and we can try to figure it out.

[crazyhottommy]

Hi Simon,

I am wandering whether seqmonk supports the bed12 format?

I have a bed12 file resulted from ChIA-PET like this:
chr14 69441719 69522938 chr14:69441719..69443220-chr14:69520758..69522938,2 200 . 69441719 69522938 255,0,0 2 1501,2180 0,79039

How can I visualize it in seqmonk?

[mathew]

I am using Seqmonk for analysis of RNAseq PE reads. When I run pipeline will use option of getting raw rpkm, will it give me fpkm values if I use PE reads. Thanks.