Re: [galaxy-user] help for trim sequences

2013-11-25 Thread Geert Vandeweyer
You might also use ( / add to main) the CutAdapt tool, which is 
available in the main toolshed. It takes multiple adapters, allows 
3/5/both side adapters, and is fast.


http://toolshed.g2.bx.psu.edu/repository/view_repository?sort=User.usernameoperation=view_or_manage_repositoryid=f19bc86bac946438

Best,

Geert

On 11/23/2013 03:19 PM, Peter Cock wrote:

On Fri, Nov 22, 2013 at 8:48 PM, Jennifer Jackson j...@bx.psu.edu wrote:

Hi Seung Hee,

I know we discussed this on the other list, but I didn't point you to the
open development ticket to (potentially) extend the functions of the Cut
tool. This is not being actively worked on right now, but you can follow it
for updates if you want.
https://trello.com/c/CbFSHrU5

Others are still welcome to comment about what types of solutions they might
have to offer. There is no specific tool to do this on Main right now (or in
the Tool Shed, from my checks). http://usegalaxy.org/toolshed

This tool of mine might do what Seung Hee wanted,
but I have not tried it on very large Illumina datasets:

http://toolshed.g2.bx.psu.edu/view/peterjc/seq_primer_clip

Regards,

Peter
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--

Geert Vandeweyer, Ph.D.
Department of Medical Genetics
University of Antwerp
Prins Boudewijnlaan 43
2650 Edegem
Belgium
Tel: +32 (0)3 275 97 56
E-mail: geert.vandewe...@ua.ac.be
http://ua.ac.be/cognitivegenetics
http://www.linkedin.com/in/geertvandeweyer

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Re: [galaxy-user] help for trim sequences

2013-11-25 Thread Jennifer Jackson

Thanks Geert,
   This tool was in the back on my mind, but I couldn't find it last 
week for some reason!


Seung Hee - this is a very good choice, for use in a local or or cloud 
Galaxy.

http://getgalaxy.org
http://usegalaxy.org/cloud

I think I will close out the ticket below and point it to CutAdapt as a 
solution. A ticket to ask for this tool to be on Main is a distinct 
subject/issue - if someone wants to submit that request, the community 
can vote, team can priotitize, etc.

http://wiki.galaxyproject.org/Issues

The tool Peter mentions can also be examined. One may fit your needs 
better than the other,


Thanks!!
Jen
Galaxy team

On 11/25/13 6:03 AM, Geert Vandeweyer wrote:
You might also use ( / add to main) the CutAdapt tool, which is 
available in the main toolshed. It takes multiple adapters, allows 
3/5/both side adapters, and is fast.


http://toolshed.g2.bx.psu.edu/repository/view_repository?sort=User.usernameoperation=view_or_manage_repositoryid=f19bc86bac946438

Best,

Geert

On 11/23/2013 03:19 PM, Peter Cock wrote:

On Fri, Nov 22, 2013 at 8:48 PM, Jennifer Jacksonj...@bx.psu.edu  wrote:

Hi Seung Hee,

I know we discussed this on the other list, but I didn't point you to the
open development ticket to (potentially) extend the functions of the Cut
tool. This is not being actively worked on right now, but you can follow it
for updates if you want.
https://trello.com/c/CbFSHrU5

Others are still welcome to comment about what types of solutions they might
have to offer. There is no specific tool to do this on Main right now (or in
the Tool Shed, from my checks).http://usegalaxy.org/toolshed

This tool of mine might do what Seung Hee wanted,
but I have not tried it on very large Illumina datasets:

http://toolshed.g2.bx.psu.edu/view/peterjc/seq_primer_clip

Regards,

Peter
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--

Geert Vandeweyer, Ph.D.
Department of Medical Genetics
University of Antwerp
Prins Boudewijnlaan 43
2650 Edegem
Belgium
Tel: +32 (0)3 275 97 56
E-mail:geert.vandewe...@ua.ac.be
http://ua.ac.be/cognitivegenetics
http://www.linkedin.com/in/geertvandeweyer


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Re: [galaxy-user] help for trim sequences

2013-11-25 Thread Jennifer Jackson

Thanks Peter for another option!

Jen
Galaxy team

On 11/23/13 6:19 AM, Peter Cock wrote:

On Fri, Nov 22, 2013 at 8:48 PM, Jennifer Jackson j...@bx.psu.edu wrote:

Hi Seung Hee,

I know we discussed this on the other list, but I didn't point you to the
open development ticket to (potentially) extend the functions of the Cut
tool. This is not being actively worked on right now, but you can follow it
for updates if you want.
https://trello.com/c/CbFSHrU5

Others are still welcome to comment about what types of solutions they might
have to offer. There is no specific tool to do this on Main right now (or in
the Tool Shed, from my checks). http://usegalaxy.org/toolshed

This tool of mine might do what Seung Hee wanted,
but I have not tried it on very large Illumina datasets:

http://toolshed.g2.bx.psu.edu/view/peterjc/seq_primer_clip

Regards,

Peter


--
Jennifer Hillman-Jackson
http://galaxyproject.org

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[galaxy-user] Identifying Genes

2013-11-25 Thread Loupe, Jacob M.
I am very new to Galaxy. We have performed a comparative analysis between the 
transcriptomes of different samples. We performed the analysis using Galaxy 
software (Tophat; CuffDiff; etc). What my PI has done is compiled a list of all 
the genes differentially expressed between each set, each in a separate excel 
sheet. So what I have is an excel spreadsheet with a list (usually around 300) 
of test id, gene id, and locus (ChrX:1-222). Initially, we have 
been identifying each gene individually, one at a time, by pasting the locus 
into the UCSC browser. This works, but is incredibly tedious. There has to be a 
better way in Galaxy. I have tried making BED files out of the loci, but so far 
I have been unable to identify genes using galaxy.

Can someone please explain how I can take my long list of loci and get gene 
names, ID, function, and possibly some downstream comparative ontologies to 
begin analyzing.
Like I said, very new to Galaxy and genomics.

Thanks very much

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[galaxy-user] How to know callable loci after variant calling in GATK ?

2013-11-25 Thread Fabrice Besnard
Hi all,

Would someone know how to get the information
on which areas of the genome are considered callable after a call with
Unified genotyper from GATK (as a .bed or pileup file)?

Thanks for your help/advice,

Fabrice

-- 
Fabrice Besnard
Institute of Biology of the Ecole Normale Supérieure (IBENS)
46 rue d'Ulm, 75230 Paris cedex 05, France
8th floor. Office: Room 802. Lab: Room 817.
mail: fbesn...@biologie.ens.fr
Tel: +33-1-44-32-39-31
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Re: [galaxy-user] Identifying Genes

2013-11-25 Thread Jennifer Jackson

Hi Jacob,

Using the tool Get Data - UCSC Main table browser, data can be 
retrieved directly using either gene symbols or locus positions.


A good track to go against is UCSC Genes, if available for your 
genome. RefSeq Genes is another good choice. But really any track in 
the group Gene and Gene Prediction Tracks is worth a look to see if it 
is fit for what you are interested in, as the content can vary between 
genomes and even builds. The specifics can be reviewed at UCSC by 
clicking into the describe table schema area (button next to table 
selection, start with default table).


To search multiple gene symbols, enter the list in the form under 
identifiers. To search multiple loci, enter the list under region 
(define regions). These both accept a text file, so download the 
information, cut out of the original file, formatted how the UCSC form 
states from Galaxy as text (tabular). Or, export as text from the Excel 
spreadsheet. 300 should be fine at once, I believe the limits are around 
1000 per query for each of these.


At this point in the query, the extract would just pull basic data from 
the single primary table. To also pull out related information, change 
the output file type to be selected fields from primary and related 
tables and then click on get output.


The next form is where you can link in additional tables of data. The 
general idea is to add the table, then select the specific fields that 
you want to include. Again, any of these can be reviewed before the 
final query is made using the first main form and then the describe 
table schema button, or once in that describe view, by clicking on 
related tables to navigate. When doing the query this way, the Table 
browser takes care of the relational joins for you, just as an SQL query 
would.


For more help about using the UCSC table browser, these links are good 
places to start, and for detailed questions about a specific piece of 
data that you cannot locate, the support team for the browser can almost 
certainly help. The Table browser is not your only option (flat text 
files and a mySQL database are available), but this is a web-based 
access point to the information, easily imported into Galaxy or 
downloaded for further analysis. There are also other types of queries 
possible, at UCSC and in Galaxy, this is just the most direct I know of, 
for your question and original data:

https://genome.ucsc.edu/goldenPath/help/hgTablesHelp.html
https://genome.ucsc.edu/FAQ/FAQmaillist.html

One note: you have the locus position with a chromosome identifier in 
the format Chr1 in your email. I am not sure if this was intentional 
or not - but you will need to format the identifiers to match those in 
the target reference genome, just as they were in the original analysis. 
In general, this would mean the format would be chrX instead (case 
matters). So, check/adjust the case/format to avoid problems, these 
really do have to be an exact match. The same is true for gene 
names/symbols - you can always search in the browser to see what the 
format is if something is missing and adjust. Also make sure that Excel 
does not output any hidden characters (line wraps) - stick with plain 
text cells for best results if you plan to output/use the data with 
external tools. You probably know most of this, but just in case I 
wanted to point out where the gotchas could be. Even if using gene names 
for this, you may want to use the position later on, and identifiers in 
the correct format from the start are a good idea.


Hopefully this gets you started!

Jen
Galaxy team

On 11/25/13 8:40 AM, Loupe, Jacob M. wrote:
I am very new to Galaxy. We have performed a comparative analysis 
between the transcriptomes of different samples. We performed the 
analysis using Galaxy software (Tophat; CuffDiff; etc). What my PI has 
done is compiled a list of all the genes differentially expressed 
between each set, each in a separate excel sheet. So what I have is an 
excel spreadsheet with a list (usually around 300) of test id, gene 
id, and locus (ChrX:1-222). Initially, we have been 
identifying each gene individually, one at a time, by pasting the 
locus into the UCSC browser. This works, but is incredibly tedious. 
There has to be a better way in Galaxy. I have tried making BED files 
out of the loci, but so far I have been unable to identify genes using 
galaxy.


Can someone please explain how I can take my long list of loci and get 
gene names, ID, function, and possibly some downstream comparative 
ontologies to begin analyzing.

Like I said, very new to Galaxy and genomics.

Thanks very much




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Re: [galaxy-user] help for trim sequences

2013-11-25 Thread Jennifer Jackson

Hi Seung Hee,

You can request that this tool be added to the public Main server at 
usegalaxy.org through Trello and the team will consider it. For right 
now, the options are local or cloud. (as in my other reply)


Or, you can look around the the other public servers hosted by our 
community - each is run by a distinct group with their own 
contact/help/public-use criteria: 
http://wiki.galaxyproject.org/PublicGalaxyServers


It may be simplest to see if a local will do the job, then upload the 
results to the public server for downstream analysis. Just do the very 
basics of a production server install and then add the tool to test it 
out. This will take some line commands to set up, but shouldn't be too 
much of an investment. The links are:

http://getgalaxy.org
http://usegalaxy.org/toolshed
http://wiki.galaxyproject.org/Tool%20Shed#Installing.2C_maintaining_and_uninstalling_tool_shed_repositories_within_a_Galaxy_instance
Local install help/discussion: galaxy-...@bx.psu.edu
Subscribe or search prior Q/A: http://wiki.galaxyproject.org/MailingLists

Take care,

Jen
Galaxy team

On 11/25/13 11:29 AM, Seung Hee Cho wrote:

Thank you for much  for your great help!
I am trying to use this tool but I am wondering if I can use this 
CutAdapt tools on the public server. I was working on my job on the 
public server, so if not I need download it for use.

I truly appreciate your help!

Best,

*Seung Hee Cho*
Contreras Research Group, CPE 5.416
The University of Texas at Austin
Department of Chemical Engineering
200 E Dean Keeton St. Stop C0400
Austin, TX 78712-1589


On Mon, Nov 25, 2013 at 10:08 AM, Jennifer Jackson j...@bx.psu.edu 
mailto:j...@bx.psu.edu wrote:


Thanks Peter for another option!

Jen
Galaxy team


On 11/23/13 6:19 AM, Peter Cock wrote:

On Fri, Nov 22, 2013 at 8:48 PM, Jennifer Jackson
j...@bx.psu.edu mailto:j...@bx.psu.edu wrote:

Hi Seung Hee,

I know we discussed this on the other list, but I didn't
point you to the
open development ticket to (potentially) extend the
functions of the Cut
tool. This is not being actively worked on right now, but
you can follow it
for updates if you want.
https://trello.com/c/CbFSHrU5

Others are still welcome to comment about what types of
solutions they might
have to offer. There is no specific tool to do this on
Main right now (or in
the Tool Shed, from my checks). http://usegalaxy.org/toolshed

This tool of mine might do what Seung Hee wanted,
but I have not tried it on very large Illumina datasets:

http://toolshed.g2.bx.psu.edu/view/peterjc/seq_primer_clip

Regards,

Peter


-- 
Jennifer Hillman-Jackson

http://galaxyproject.org




--
Jennifer Hillman-Jackson
http://galaxyproject.org

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[galaxy-user] Transcriptome Hypericum perforatum

2013-11-25 Thread miroslav.sotak


To whom it may concern

I would like to kindly ask you if you do have any experience in de-novo 
transcriptomic analysis (no reference genome available) who might give 
us some advice.
Our main question is how to create the best set of cDNA contigs, on 
which we can map our RNAseq reads for the analysis of differential 
expression. Currently 4 larger sets of of RNAseq reads are available 
from different genotypes as well as draft genome assembly for one of the 
genotypes. We worry about the SNPs in different genotypes affecting the 
assembly, if we combine all the RNAseq datasets and using assemblers 
such as Trinity, Oases, Velvet. Might it be better to use the draft 
genomic assembly to obtain cDNA contigs using Tophat/cufflinks via all 
available RNAseq data or only using the RNAseq data from the same 
genotype as the genome draft?


Thank you in advance
Best wishes
Miro Sotak
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Re: [galaxy-user] Transcriptome Hypericum perforatum

2013-11-25 Thread Martin Čech
Hello Miro,

for these kind of general questions I would recommend you to ask in the
bioinformatics forum at http://www.biostars.org/ as it is somewhat
unrelated to Galaxy.

Nevertheless some of the tools you mentioned are installed and available on
the main instance (usegalaxy.org) and some you can install on your own
Galaxy via the Toolshed (http://toolshed.g2.bx.psu.edu/).

best

Martin, Galaxy Team


On Mon, Nov 25, 2013 at 4:16 PM, miroslav.sotak miroslav.so...@upjs.skwrote:


 To whom it may concern

 I would like to kindly ask you if you do have any experience in de-novo
 transcriptomic analysis (no reference genome available) who might give us
 some advice.
 Our main question is how to create the best set of cDNA contigs, on which
 we can map our RNAseq reads for the analysis of differential expression.
 Currently 4 larger sets of of RNAseq reads are available from different
 genotypes as well as draft genome assembly for one of the genotypes. We
 worry about the SNPs in different genotypes affecting the assembly, if we
 combine all the RNAseq datasets and using assemblers such as Trinity,
 Oases, Velvet. Might it be better to use the draft genomic assembly to
 obtain cDNA contigs using Tophat/cufflinks via all available RNAseq data or
 only using the RNAseq data from the same genotype as the genome draft?

 Thank you in advance
 Best wishes
 Miro Sotak
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Re: [galaxy-user] Transcriptome Hypericum perforatum

2013-11-25 Thread Jennifer Jackson

Hello,

Interesting genome. I see that SRA has some RNA-seq public data, but 
there isn't much else going on. And you goal is to characterize the 
expression for observed phenotypes (linked to known genotypes)? If you 
use the Tuxedo suite after assembly (Trinity or other), differential 
expression of alternative splicing is one of the discovery outputs.


From my experience (and other are welcome to add comments), most SNP 
differences (_single_ base polymorphisms) do not in general impact the 
global assembly of whole genome data. Larger insertions/deletions are 
where you will observe differences. But that is DNA.


For transcription assembly, including RNA-seq, novel isoforms per sample 
and in particular rare events like SNPs, can become diluted when 
multiple samples are directly combined and assembled together straight 
de-novo. Still, obtaining full length cDNAs is certainly possible. And 
it has been done just about the same way, with various types of RNA 
data, for a very long time (most of RefSeq started out that way). The 
downside here is that the most common variant can overwhelm, but with 
a plant you might have that issue anyway depending on ploidy. So, test 
for yourself. Genomes can vary and the tools are so interesting - same 
way is a gross generalization on my part, in specifics the tools are 
very sophisticated.


And, most importantly, as you do have a reference genome to use as a 
guide (and that is really an invaluable tool not to be ignored) be sure 
to incorporate it unless it is from a sample that is known to be 
significantly, unacceptably, different from the wildtype. It sounds like 
the quality has been assessed to be unacceptable to use directly as a 
reference genome for some reason (correct? Or, you just want to build up 
the cDNA set -great project!). But the genome can still be utilized. 
Specifically - using it as an early stage assembly guide will give you a 
huge advantage, in my opinion (some assemblers cluster the data first by 
mapping - you want this if possible). But again, you could try it both 
ways and check out a few genes to see how the transcript profile worked 
out (vs any knowns - comparative OK, I always used these when I did this 
type of work), plus use the truth metrics (to me) of transcription 
assembly: how many singletons did you end up with (and what do they map 
to! can they really be ignored?)  how many over-clustered genes did 
you get (interesting, sparcer genes gobbled up by abundant 
housekeeping). Under-clustered genes/transcripts or incomplete 
transcripts are other factors, but depending on how you set the 
parameters in Cufflinks, this may be less important, if it isn't a 
pathological problem.


Many people will have advice about this, so ask, but also test. Looking 
at the results will inform you if the path is right. I hope this helps a 
little bit!


Jen
Galaxy team


On 11/25/13 1:16 PM, miroslav.sotak wrote:


To whom it may concern

I would like to kindly ask you if you do have any experience in 
de-novo transcriptomic analysis (no reference genome available) who 
might give us some advice.
Our main question is how to create the best set of cDNA contigs, on 
which we can map our RNAseq reads for the analysis of differential 
expression. Currently 4 larger sets of of RNAseq reads are available 
from different genotypes as well as draft genome assembly for one of 
the genotypes. We worry about the SNPs in different genotypes 
affecting the assembly, if we combine all the RNAseq datasets and 
using assemblers such as Trinity, Oases, Velvet. Might it be better to 
use the draft genomic assembly to obtain cDNA contigs using 
Tophat/cufflinks via all available RNAseq data or only using the 
RNAseq data from the same genotype as the genome draft?


Thank you in advance
Best wishes
Miro Sotak
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