Problems with choosing reference sequences

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nawo...@gmail.com

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Jul 5, 2017, 10:34:35 PM7/5/17
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Dear all. 


Hello, 
I'm new in this field, having some problems with my first analysis.
 Could you help me to solve the problems of reference? 


I'm doing my works with 16S rRNA sequences. 

My problems are, 

1. Reference sequences: RDP

  - I want to use RDP reference sequence, but I have no idea which RDP data should I use for analysis; training set, unaligned, aligned.
  - I want to know the meaning of "RDP Training set". What is RDP Training set? Is this using when the taxonomy assignment method is 'RDP classifyer'? 


2. Error in Taxonomy assignment with RDP reference data

  I got error when 'assign_taxonomy.py' with unaligned RDP data as reference sequence.


Clustering was:

pick_open_reference_otus.py -i seqs_chimera_filtered.fna -o w_rdp_otus/ -r unaligned_rdp.fa -f -a --suppress_taxonomy_assignment

Then I tried to assignment with unaligned rdp reference sequence but I failed.

Here is the command: 

assign_taxonomy.py -i rep_set.fna -r Trimmed_reads/unaligned_rdp.fa -t Trimmed_reads/trainset16_022016.rdp/trainset16_022016.rdp.tax -o unaligned_rdp_assignment

Traceback (most recent call last):
  File "/qiime/qiime/build/scripts-2.7/assign_taxonomy.py", line 417, in <module>
    main()
  File "/qiime/qiime/build/scripts-2.7/assign_taxonomy.py", line 394, in main
    log_path=log_path)
  File "/qiime/python/python2/lib/python2.7/site-packages/qiime-1.9.1.dev0-py2.7.egg/qiime/assign_taxonomy.py", line 1306, in __call__
    result = self._uc_to_assignments(app_result['ClusterFile'])
  File "/qiime/python/python2/lib/python2.7/site-packages/qiime-1.9.1.dev0-py2.7.egg/qiime/assign_taxonomy.py", line 1364, in _uc_to_assignments
    tax = self.id_to_taxonomy[subject_id].split(';')
KeyError: 'S003990863'

But, when I use greengenes as reference, there's no error. What should I do for solve this problem? 

I need some help to understand how to use the right reference sequence in each process. 
Thank you!

2017. 07. 06. THU.
- Hyojung Kim 

Se Jin Song

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Jul 7, 2017, 2:32:11 PM7/7/17
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