In formal use bioOTU to pick OTUs, ahead of reading the follow notes.
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Essential requirements:
(1) Operating system
Linux
(The bioOTU can only be operated on Linux system at present.)
(2) Software
Python2.7
(The bioOTU is mainly developed by python and consisted by python scripts. Therefore, Python2.7 is required and can be downloaded from official website(www.python.org/downloads/). In fact, python2.7 is always pre-installed on linux system. Hence, you can check it by executing terminal command as 'python --version', before you decide to download and install python2.7.)
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download
You can download bioOTU from https://github.com/chengroup/bioOTU and unzip the file. Or you can also download bioOTU by executing the following command:
$ git clone https://github.com/chengroup/bioOTU.git
***Note: specific symbol (especially, minus/'-') should not be included in software and input file path.***
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usage:
(1) dereplication.py
--list/-l (required) the list file (two column separated by tab) for all samples. The first column is the absolute path of sample files, and second column is the specified name of sample.
--index/-n (optional) to select the index ("samplesize" or "abundance") for dividing all unique sequences into both multiple and singleton tags.
--help/-h help
(2) classifier.py
--fasta/-f (required) the input file (in fasta format) that contains all your sequences for taxonomical assignments ("unique_sequences_multiple.fa")
--template/-t (required) the reference database, such as that are retrieved from RDP or SILVA (in fasta format)
--taxonomy/-a (required) the taxonomical file corresponding to your reference sequences
--ksize/-k (optional) to specify the size of kmer, default:8
--iters/-i (optional) to specify the number of iteration, default:1000
--cutoff/-c (optional) to specify bootstrap cutoff for supporting the taxonomical assignment, default:95
--processors/-p (optional) processors, default:1
--help/-h help
(3) taxonomy_guided_OTU_pick.py
--assigned/-a (required) the file containing these taxonomically assigned sequences ("unique_sequences_multiple_assigned.fa")
--unassigned/-u (required) the file containing the sequences failing to be taxonomically assigned ("unique_sequences_multiple_unassigned.fa")
--taxonomy/-t (required) the file of taxonomical information for all multiple sequences ("unique_sequences_multiple.taxonomy")
--singleton/-s (required) the file containing singleton tags ("unique_sequences_singleton.fa")
--threshold/-h (optional) to specify the distance cutoff for OTUs clustering, default:0.03
--kdistance/-k (optional) to specify cutoff of kmer distance, default:0.5
--processors/-p (optional) processors, default:1
--help/-h help
(4) chimera_detection.py
--best_reference/-b (required) input file containing all reference sequences for chimera detection ("taxonomy_guided_OTU.fa")
--pengding_sequence/-s (required) input file containing all candidate sequences subject to chimera detection ("pengding_sequences_multiple.fa")
--sample_size/-r (optional) to specify minimum value of sample size for adding these pengding sequences into reference database
--processors/-p (optional) processors, default:1
--help/-h help
(5) heuristic_search_OTU_pick.py
--pengding_nonchimera/-s (required) input file containing all pengding multiple sequences after chimera detection ("pengding_sequences_multiple.nonchimera")
--pending_singleton/-g (required) input file containing all pengding singleton sequences ("pending_sequence_singleton.fa")
--threshold/-r (optional) to specify the distance cutoff for OTUs clustering, default:0.03
--kdistance/-k (optional) to specify cutoff of kmer distance, default:0.5
--processors/-p (optional) processors, default:1
--help/-h help
(6) create_OTU_table.py
--OTUlist/-u (required) list files (file names are separated by ',') of these constructed OTUs by both taxonomy-guided and heuristic search methods ("taxonomy_guided_OTU.list,heuristic_search_OTU.list")
--table/-t (required) table file containing information of both sample size and abundance for all unique sequences created by module of "dereplication.py" ("unique_sequences.table")
--group/-g (optional) list file provided by user, which contains tab-separated two column: the first column is the specified name of sample, and the second column is group ID.
--help/-h help
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Analysis:
Preliminary files:
(1) samples.list a list file with the fasta files of every samples and sample tags/names.
(2) trainset14_032015.rdp_bacteria.fasta a fasta file with the reference sequences (downloaded from silva、RDP or GreenGene)
(3) strainset14_032015.rdp_bacteria.tax a taxonomy file with the taxonomy information of all reference sequences (downloaded with reference sequences at the same time).
step1:
$ python bioOTU/dereplication.py -l samples.list --index samplesize
step2:
$ python bioOTU/classifier.py --fasta unique_sequences_multiple.fa --template trainset14_032015.rdp_bacteria.fasta --taxonomy strainset14_032015.rdp_bacteria.tax --cutoff 95 -p 8 --iters 1000
step3:
$ python bioOTU/taxonomy_guided_OTU_pick.py --assigned unique_sequences_multiple_assigned.fa --unassigned unique_sequences_multiple_unassigned.fa --taxonomy unique_sequences_multiple.taxonomy --singleton unique_sequences_singleton.fa --threshold 0.03 --kdistance 0.5 --processors 8
step4:
$ python bioOTU/chimera_detection.py --best_reference taxonomy_guided_OTU.fa --pengding_sequence pengding_sequences_multiple.fa --processors 8
step5:
$ python bioOTU/heuristic_search_OTU_pick.py --pengding_nonchimera pengding_sequences_multiple.nonchimera --pending_singleton pending_sequence_singleton.fa --kdistance 0.5 --threshold 0.03 --processors 8
step6:
$ python bioOTU/create_OTU_table.py --OTUlist heuristic_search_OTU.list,taxonomy_guided_OTU.list --table unique_sequences.table
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contact:
Dr. Shi-Yi Chen:
Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu Campus
211# Huimin Road, Wenjiang 611130 Sichuan, China
Fax: 86-28-86290987
Emails: sychensau@gmail.com