Hi Delong,
If you are mapping against a large reference genome and your datasets are large, 8G of memory may simply not be enough, even with omitting this paramater. Also, if you have set other TopHat parameters to be sensitive, then those can also be contributing to memory usage. Splitting the job up is still an option to try, as in the original post: http://gmod.827538.n3.nabble.com/Tophat-Error-segment-based-junction-search-...
On 10/2/13 10:20 AM, Delong, Zhou wrote:
Hello, I don't know why I still have this problem.. I have run tophat2 with different dataset, sometimes it goes well but sometime I have this error.
There are likely content differences between the datasets. A tool such as FastQC is a good one to use to investigate.
I run only one job at a time on a virtual machine with 8G memory without using galaxy plateform. I tried --no-coverage-search option but it changes nothing.
Do you mean that the tool fails on the line command? Then it will also fail in Galaxy using the same resources, this is expected.
If you do not want to split the job up, you could consider a Cloud Galaxy: http://usegalaxy.org/cloud
Best,
Jen Galaxy team
Thanks. Delong
*De :* Delong, Zhou *Envoyé :* 27 août 2013 9:36 *À :* galaxy-user@bx.psu.edu *Objet :* Tophat Error: segment-based junction search failed with err
Hello, I have run several analysis with Tophat 2 on my local instance of galaxy and I get this error for all of them..
segment-based junction search failed with err = 1 or -9
Here is an example of full error report:
Error in tophat:
[2013-08-23 11:56:58] Beginning TopHat run (v2.0.6)
[2013-08-23 11:56:58] Checking for Bowtie Bowtie version: 2.0.2.0 [2013-08-23 11:56:58] Checking for Samtools Samtools version: 0.1.18.0 [2013-08-23 11:56:58] Checking for Bowtie index files [2013-08-23 11:56:58] Checking for reference FASTA file [2013-08-23 11:56:58] Generating SAM header for /usr/local/data/bowtie2/hg19/hg19 format: fastq quality scale: phred33 (default) [2013-08-23 11:58:04] Preparing reads left reads: min. length=50, max. length=50, 145339247 kept reads (34946 discarded) right reads: min. length=50, max. length=50, 145340153 kept reads (34040 discarded) [2013-08-23 14:16:21] Mapping left_kept_reads to genome hg19 with Bowtie2 [2013-08-24 01:04:37] Mapping left_kept_reads_seg1 to genome hg19 with Bowtie2 (1/2) [2013-08-24 03:38:22] Mapping left_kept_reads_seg2 to genome hg19 with Bowtie2 (2/2) [2013-08-24 05:29:58] Mapping right_kept_reads to genome hg19 with Bowtie2 [2013-08-24 19:50:22] Mapping right_kept_reads_seg1 to genome hg19 with Bowtie2 (1/2) [2013-08-24 22:36:38] Mapping right_kept_reads_seg2 to genome hg19 with Bowtie2 (2/2) [2013-08-25 01:40:37] Searching for junctions via segment mapping Coverage-search algorithm is turned on, making this step very slow Please try running TopHat again with the option (--no-coverage-search) if this step takes too much time or memory. [FAILED] Error: segment-based junction search failed with err =-9 Collecting potential splice sites in islands
cp: cannot stat `/home/galaxy/galaxy-dist/database/job_working_directory/000/515/tophat_out/deletions.bed': No such file or directory cp: cannot stat `/home/galaxy/galaxy-dist/database/job_working_directory/000/515/tophat_out/insertions.bed': No such file or directory
I did some research on the internet and it seems to be a memory problem to me, is there any solution other than rerun these jobs on a more powerful machine?
And why has Bowtie/Tophat discard different numbers of reads? What will be the impact? Does it means that if I don't have exact matches between the paired end input, it is still be possible to run the job?
Thanks, Delong
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