usage: plantqc.py [-h] (--file INPUT_FILE | --lib LIBRARY_NAME) [--output OUTPUT] [--verbose] [--grouping] [--transpose] [--excel] [--markdown] [--html] [--pdf] [--seq_unit]
                  [--ccs {0,1,2}] [--jira JIRA_TICKET] [--user JIRA_USER] [--password JIRA_PASSWORD] [--log {debug,critical,error,warning,info}] --config CONFIG

create table of metrics for pacbio or illumina libraries

optional arguments:
  -h, --help                                 show this help message and exit
  --file INPUT_FILE, -f INPUT_FILE           text file with library names, one per line
  --lib LIBRARY_NAME, -l LIBRARY_NAME        name of library
  --output OUTPUT, -o OUTPUT                 output filename (default: plantqc.tsv)
  --verbose, -v                              modify output verbosity (default: False)
  --grouping, -g                             format numbers (default: True)
  --transpose, -t                            transpose output file (default: True)
  --excel, -e                                add excel file output (default: False)
  --markdown, -m                             add markdown file output (default: True)
  --html, -w                                 add html file output (default: False)
  --pdf, -p                                  add pdf file output (default: False)
  --seq_unit, -u                             file output per seq_unit (default: False)
  --ccs {0,1,2}, -c {0,1,2}                  for pacbio libraries: only ccs (0), subreads (1), both (3) (default: 0)
  --jira JIRA_TICKET, -j JIRA_TICKET         name of jira ticket
  --user JIRA_USER                           jira user name
  --password JIRA_PASSWORD                   jira user password
  --log {debug,critical,error,warning,info}  set log level (default: error)
  --config CONFIG                            Configuration file


Example usage:

1) 
>JIRA=SEQQC-17323
>LIB=HXXPO
>docker run --rm -v $PWD:/mnt -w /mnt dbest/plantqc:v7.2 plantqc.py -l $LIB -o $LIB.tsv --config Constants.config --user <your JIRA user id> --password '<your JIRA password>' -j $JIRA

Alternatively, you can run the python script in a conda environment:
>plantqc.py -l $LIB -o $LIB.tsv --config Constants.config --user <your JIRA user id> --password '<your JIRA password>' -j $JIRA

2) paste plantqc.tsv file into https://rqc.jgi-psf.org/sow_qc/page/HWPSS/2-4835625
3) copy CLA value from platnqc.tsv file into "Logical Amount (CLA)" data entry box
4) from pull down menu "Data usable" choose "Usable"


Troubleshooting:
1) ask Bryce


Version History:

v1.0:
first version working for pacbio ccs reads

v2.0:
add number of bases via web interface

v3.0:
- use web interface to get pacbio information
- use web location for sketch file,
- no need to run on CORI anymore, works from anywhere, laptop etc.
- new parser for sketch files using pandas
- use local to format numbers, add --grouping option to turn on this feature
- write output tsv file using pandas

v4.0:
- add transpose option
- add excel output option
- add illumina plant qc: illumina_metrics
- rename script to plantqc.py
- move loop over libraries outside of metrics code to main
- move code to write to output from metrics code to main

v5.0:
- add rest calls to get TLA, estimated-genome-size, sow-item-type etc.
- illumina_metric: estimated-genome-size now taken from database
- revamp grouping of numbers
- add markdown output
- add html output
- add pdf output
- streamlining code

v6.0:
- add ccs option
- add pacbio_stats_hash
- remove system option and get sequencing platform from database

v7.0:
- add interaction with JIRA
- automatically add comment
- automatically complete ticket
- add logger

v7.1:
- add option to read from config file
- v1.0:
first version working for pacbio ccs reads

v2.0:
add number of bases via web interface

v3.0:
- use web interface to get pacbio information
- use web location for sketch file,
- no need to run on CORI anymore, works from anywhere, laptop etc.
- new parser for sketch files using pandas
- use local to format numbers, add --grouping option to turn on this feature
- write output tsv file using pandas

v4.0:
- add transpose option
- add excel output option
- add illumina plant qc: illumina_metrics
- rename script to plantqc.py
- move loop over libraries outside of metrics code to main
- move code to write to output from metrics code to main

v5.0:
- add rest calls to get TLA, estimated-genome-size, sow-item-type etc.
- illumina_metric: estimated-genome-size now taken from database
- revamp grouping of numbers
- add markdown output
- add html output
- add pdf output
- streamlining code

v6.0:
- add ccs option
- add pacbio_stats_hash
- remove system option and get sequencing platform from database

v7.0:
- add interaction with JIRA
- automatically add comment
- automatically complete ticket
- add logger

v7.1:
- add option to read from config file
- pass/fail conditions not hardcoded anymore, read from config file
- update pass/fail conditions
- add "% reads filtered" to pass/fail conditions

v7.2:
- config file optional, use defaults of no config file provided
- make transpose, grouping, markdown creation default