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Old 05-19-2014, 06:47 AM   #21
ntn12
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Originally Posted by ecSeq Bioinformatics View Post
Dear ntn12,

I herewith take notice of your assumption that the segemehl developers wrote some statements which are confusing for you, so you will use SOAPfuse.
That is not an assumption. It is a fact.
Indeed the authors of "Hoffmann et al. A multi-split mapping algorithm for circular RNA, splicing, trans-splicing, and FUSION DETECTION, Genome Biol. 2014. http://www.ncbi.nlm.nih.gov/pubmed/24512684"

clearly state in their article that:

"Implemented in the segemehl mapping tool, it readily identifies conventional splice junctions, collinear and non-collinear fusion transcripts, and trans-spliced RNAs, without the need for separate post-processing or an extensive computational overhead."

I did not write that. The authors wrote that! Anybody can check this! Please, check here:
http://www.ncbi.nlm.nih.gov/pubmed/24512684

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Originally Posted by ecSeq Bioinformatics View Post
I herewith take notice of your assumption that the segemehl developers wrote some statements which are confusing for you, so you will use SOAPfuse.
I am not the only one who got confused about SEGEMEHL. There are at least two others who are confused about SEGEMEHL and finding fusion genes here:
https://www.biostars.org/p/45986/

Last edited by ntn12; 05-19-2014 at 06:54 AM.
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Old 05-19-2014, 07:34 AM   #22
Paul Newport
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Originally Posted by ntn12 View Post
I am not the only one who got confused about SEGEMEHL. There are at least two others who are confused about SEGEMEHL and finding fusion genes here:
https://www.biostars.org/p/45986/
Oh, please! Give me a break! Same statements, same time stamp! Too obvious, man!
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Old 05-19-2014, 07:40 AM   #23
ntn12
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Oh, please! Give me a break! Same statements, same time stamp! Too obvious, man!
???
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Old 05-19-2014, 11:45 PM   #24
ecSeq Bioinformatics
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As already mentioned before in this thread:

If any of you is interested in learning how to use segemehl to detect fusion transcripts and/or circularized RNAs, I can recommend you the following hands-on course:

Discovering standard and non-standard RNA transcripts - How to detect canonical splicing, circular RNAs, trans-splicing, and fusion transcripts

Developers of the algorithm will explain you step-by-step how you can use segemehl to detect standard and non-standard transcripts. They will assure that all of you understand the difference between 'fusion-junctions' and 'fusion-genes' and what exactly you can do with segemehl and all its downstream analysis tools like (lack or haarz). You will understand the implications of splicing or fusion events and the concept of split-reads, how to detect splice sites using split-read information and in the end be able to find circularized RNAs or fusion-stranscripts.

The cool thing with this course: You will not just use (and trust) a tool with pre-defined parameters (like SOAPfuse, etc.), but understand everything from scratch!
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Last edited by ecSeq Bioinformatics; 05-20-2014 at 12:14 AM.
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Old 09-11-2014, 11:16 AM   #25
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I'm interested in giving segemehl a shot, but so far it's taking prohibitively long to run. In my cluster-computer environment I reserved 60 nodes for 24 hours to run:

segemehl.x -q 8Gb_single_end.fastq -t 60 -d chromosome1.fa -i chr1.idx -S -s -o chr1.sam

took over 24hours without completing. There were no errors reported, it did create a sam file, however incomplete. Do you have any tips to make the software run more quickly?
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Old 10-29-2014, 01:17 AM   #26
ecSeq Bioinformatics
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Originally Posted by NKAkers View Post
I'm interested in giving segemehl a shot, but so far it's taking prohibitively long to run. In my cluster-computer environment I reserved 60 nodes for 24 hours to run:

segemehl.x -q 8Gb_single_end.fastq -t 60 -d chromosome1.fa -i chr1.idx -S -s -o chr1.sam

took over 24hours without completing. There were no errors reported, it did create a sam file, however incomplete. Do you have any tips to make the software run more quickly?
This extensively long runtime of segemehl is probably owed to the common mapping strategy of RNA aligners which first attempt to map reads contiguously (i.e. without split) and then use the unmapped ones for a more expensive split-read mapping strategy. By mapping your data only to one chromosome instead of the entire genome, most of your data cannot be mapped but are attempted to be split-mapped, resulting in this huge runtime.

Thus, we would recommend to use the entire genome as database, resulting in faster runtime and moreover more reliable hits since by default segemehl reports only the best ones.
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Old 01-04-2016, 12:05 AM   #27
ninni
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I do not know. We have not used yet FusionCatcher. We have been testing TopHat-fusion, FusionMap, ChimeraScan, and FusionFinder. We found puzzling that all these four give thousands of candidate fusion genes per sample (some even hundred of thousands) when we know from the medical literature that there should not be more than 1-3 fusion genes per sample!!! Therefore one has here 99% false positives.

UPDATE: We started testing SOAPfuse and we start to like it!
Hi!
Is it possible to use SOAPfuse with hg38? If so, how would I do this? I am a bit lost.

Thanks in advance!
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