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Originally posted by gconcepcion View PostIt seems as though pulse features were not added into your *.cmp.h5
What was the process you used to generate your cmp.h5. Did you use pbalign with the --forQuiver option?Code:tofu_wrap.py --nfl_fa isoseq_nfl.fasta --ccs_fofn reads_of_insert.fofn --bas_fofn input.fofn -d clusterOut --quiver --gmap_db /zs32/data-analysis/liucy_group/llhuang/Reflib/gmapdb --gmap_name gmapdb_h19 --output_seqid_prefix human isoseq_flnc.fasta final.consensus.fa
Last edited by GenoMax; 07-28-2016, 09:18 AM.
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Originally posted by bowhan View Post
reads_of_insert.fofn
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Originally posted by bowhan View Post
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Originally posted by lingling huang View PostI am sure that the fofn files are correct. I try it again, Just as expected, error occurred I can't understand the cause of the error displayed on screen, as usual, I attach them at below. As you can see, the code has been running for half.Could you explain why this is the case? Thank you!
[ATTACH]4447[/ATTACH]
[ATTACH]4448[/ATTACH]
[ATTACH]4449[/ATTACH]
This one is on DALIGNER itself. The version shipped within ToFU is pretty outdated. Several bugs have been found and fixed since then.
Please obtain the more recently version from https://github.com/PacificBiosciences/DALIGNER/, compile it and replace the ones under your virtualenv/bin directory.
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Originally posted by lingling huang View Postinput.fofn
[ATTACH]4445[/ATTACH]
reads_of_insert.fofn
[ATTACH]4446[/ATTACH]
Try removing the blank lines at the end and re-running.Last edited by gconcepcion; 07-29-2016, 12:36 PM.
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Originally posted by bowhan View PostTo me this is a different error from the one described originally.
This one is on DALIGNER itself. The version shipped within ToFU is pretty outdated. Several bugs have been found and fixed since then.
Please obtain the more recently version from https://github.com/PacificBiosciences/DALIGNER/, compile it and replace the ones under your virtualenv/bin directory.
error:
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Originally posted by lingling huang View PostHi, bowhan . I have updated DALIGNER files, and ran again. Finally, I obtain the 'combined' folder in the directory 'clusterOut' . It seems that I basically got the result, but I found it was lack of "all_sizes.quivered_hq.fastq.5merge.collapsed.XXX " files. Disappointed, I failed again. I guess there is a problem in the step of 'collapse_isoforms_by_sam.py‘ command or in the process of mapping to the reference genome, right? How can I fix it up?
Please try the method described in this thread. If the error remains, re-install ToFU under a new directory. Make sure you follow the instructions (https://github.com/PacificBioscience...ranscript-tofu) strictly.
Additionally, I remember that you had issues with outdated Cython. Consider upgrading that BEFORE installing ToFU.
Originally posted by lingling huang View PostAnother question is why I can't find 'final.consensus.fa' in current pathway since I wrote it in my command. As usual, I attach there pictures at below. I am looking forward to your help, thank you very much!
https://github.com/PacificBioscience...ICE-and-Quiver)
BTW, I wouldn't use the default bin size, which is 1kb. Reads in different bins are not seeing each other during the clustering process. Use something like `--bin_manual "(0,2,4,6,8,99)"`.
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Originally posted by bowhan View PostThe error message indicates a (solved) issue described here:
Please try the method described in this thread. If the error remains, re-install ToFU under a new directory. Make sure you follow the instructions (https://github.com/PacificBioscience...ranscript-tofu) strictly.
Additionally, I remember that you had issues with outdated Cython. Consider upgrading that BEFORE installing ToFU.
That's fine. `final.consensus.fa` is the output of `pbtranscript.py cluster` but not ToFU. You should be expecting a file named `all_sizes.quivered_hq.fastq` under the `combined` folder. For more information, please read this:
https://github.com/PacificBioscience...ICE-and-Quiver)
BTW, I wouldn't use the default bin size, which is 1kb. Reads in different bins are not seeing each other during the clustering process. Use something like `--bin_manual "(0,2,4,6,8,99)"`.
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