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Standalone scripts

Repository to store standalone scripts that do not belong to any bigger package or repository.

compute_undet_index_stats.py

used to fetch stats about undermined indexes. This scripts queries statusdb x_flowcell_db and fetch informaiton about runs. The following operations are supported:

  • check_undet_index: given a specific index checks all FCs and prints all FC and lanes where the indx appears as undetermined
  • most_undet: outputs a summary about undetermiend indexes, printing the most 20 most occurring indexes for each instrument type
  • single_sample_lanes: prints stats about HiSeqX lanes run with a single sample in it
  • workset_undet: prints for each workset the FC, lanes and samples where the specified index has been found in undet. For each sample the plate position is printed.
  • fetch_pooled_projects: returns pooled projects, that is projects that have been run in a pool.

Usage

Examples:

  • compute for each workset the FC that contain a lane with index CTTGTAAT present in undet at least 0.5M times:
    • python compute_undet_index_stats.py --config couch_db.yaml --index CTTGTAAT --mode workset_undet --min_occurences 500000
  • Compute a list of the most occurring undetemriend indexes for HiSeqX runs:
    • python compute_undet_index_stats.py --config couch_db.yaml -- mode most_undet --instrument-type HiSeqX

compute_undet_index_stats.py

used to fetch stats about undermined indexes. This scripts queries statusdb x_flowcell_db and fetch informaiton about runs. The following operations are supported:

  • check_undet_index: given a specific index checks all FCs and prints all FC and lanes where the indx appears as undetermined
  • most_undet: outputs a summary about undetermiend indexes, printing the most 20 most occurring indexes for each instrument type
  • single_sample_lanes: prints stats about HiSeqX lanes run with a single sample in it
  • workset_undet: prints for each workset the FC, lanes and samples where the specified index has been found in undet. For each sample the plate position is printed.
  • fetch_pooled_projects: returns pooled projects, that is projects that have been run in a pool.

Usage

Examples:

  • compute for each workset the FC that contain a lane with index CTTGTAAT present in undet at least 0.5M times:
    • python compute_undet_index_stats.py --config couch_db.yaml --index CTTGTAAT --mode workset_undet --min_occurences 500000
  • Compute a list of the most occurring undetemriend indexes for HiSeqX runs:
    • python compute_undet_index_stats.py --config couch_db.yaml -- mode most_undet --instrument-type HiSeqX

runs_per_week.sh

Run on Irma prints a three columns:

  • first column is the week number
  • second column number of HiSeqX runs in that week
  • seconf column number of HiSeq2500 runs in that week

Usage

Examp runs_per_week.sh

compute_production_stats.py

This scripts queries statusdb x_flowcelldb and project database and fetches informations useful to plot trands and aggregated data. It can be run in three modalities:

     - production-stats: for each instrument type it prints number of FCs, number of lanes, etc. It then prints a summary of all stats
     - instrument-usage: for each instrument type and year it prints different run set-ups and samples run with that set-up
     - year-stats: cumulative data production by month
Usage

Example: compute_production_stats.py --config couchdb.yaml --mode year-stats

Usage: compute_production_stats.py --config couchdb.yam

Options:
    --config CONFIG  configuration file

Configuration

Requires a config file to access statusdb

statusdb:
    url: path_to_tool
    username: Username
    password: *********

backup_zendesk_tickets.py

Used to automatically back up tickets from zendesk

Usage

Example: backup_zendesk_tickets.py --config-file ~/config_files/backup_zendesk_tickets.yaml --days 30

Usage: backup_zendesk_tickets.py [OPTIONS]

Options:
  --config-file PATH  Path to the config file  [required]
  --days INTEGER      Since how many days ago to backup tickets
  --help              Show this message and exit.

Dependencies

  • zendesk
  • click
  • yaml
  • requests

Configuration

Requires a config file:

url: https://ngisweden.zendesk.com
username: mattias.ormestad@scilifelab.se
token: <ask Mattias to get token>
output_path: /Users/kate/Dropbox/dropbox_work/zendesk/output

backup_github.py

Performs a backup of all the repositories in user's GitHub account.

Dependencies
  • logbook
  • pygithub3

couchdb_replication.py

handles the replication of the couchdb instance

Dependencies
  • couchdb
  • logbook
  • pycrypto
  • yaml

data_to_ftp.py

Used to transfer data to user's ftp server maintaing the directory tree structure. Main intention is to get the data to user outside Sweden.

db_sync.sh

Script used to mirror (completely) Clarity LIMS database from production to staging server

get_sample_names.py

Prints a list of analyzed samples with user_id and ngi_id

Usage:

get_sample_names.py P1234

index_fixer.py

Takes in a SampleSheet.csv and generates a new one with swapped or reverse complimented indexes.

Dependencies
  • click
  • Flowcell_Parser: SampleSheetParser

merge_and_rename_NGI_fastq_files.py

Merges all fastq_files from a sample into one file.

merge_and_rename_NGI_fastq_files.py path/to/dir/with/inputfiles/ path/to/output/directory

project_status_extended.py

Collects information about specified project from the filesystem of irma. Without any arguments prints statistics for each sample, such as:

  • Number of reads
  • Coverage
  • Duplication rate
  • Mapping rate

Usage

python project_status_extended.py P4601

To remove headers from the output, use option --skip-header

The script can take additional arguments:

--sequenced           List of all the sequenced samples
--resequenced         List of samples that have been sequenced more than
once, and flowcells
--organized           List of all the organized flowcells
--to-organize         List of all the not-organized flowcells
--analyzed            List of all the analysed samples
--to-analyze          List of samples that are ready to be analyzed
--analysis-failed     List of all the samples with failed analysis
--under-analysis      List of the samples under analysis
--under-qc            List of samples under qc. Use for projects
without BP
--incoherent          Project-status but only for samples which have
incoherent number of sequenced/organized/analyzed
--low-coverage        List of analyzed samples with coverage below 28.5X
--undetermined        List of the samples which use undetermined  
--low-mapping         List of all the samples with mapping below 97 percent
--flowcells           List of flowcells where each sample has been sequenced

repooler.py

Calculates a decent way to re-pool samples in the case that the amount of clusters from each sample doesn't reach the required threshold due to mismeasurements in concentration.

Dependencies
  • couchdb
  • click
  • Genologics: lims, config, entities

quota_log.py

DO NOT USE THIS SCRIPT!

Use taca server_status uppmax instead!

Returns a summary of quota usage in Uppmax

Dependencies
  • couchdb
  • pprint

Samplesheet_converter.py

For the purpose of converting Illumina samplesheet that contains Chromium 10X indexes for demultiplexing. Headers and lines with ordinary indexes will be passed without any change. Lines with Chromium 10X indexes will be expanded into 4 lines, with 1 index in each line, and suffix 'Sx' will be added at the end of sample names.

Usage

python main.py -i <inputfile> -o <outputfile> -x <indexlibrary>

set_bioinforesponsible.py

Calls up the genologics LIMS directly in order to more quickly set a bioinformatics responsible.

Dependencies
  • Genologics: lims, config

use_undetermined.sh

Creates softlinks of undetermined for specified flowcell and lane to be used in the analysis. To be run on irma.

Usage

Usage: use_undetermined.sh  <flowcell> <lane> <sample>
Example: use_undetermined.sh 160901_ST-E00214_0087_BH33GHALXX 1 P4601_273

Important

After running the script, don't forget to (re-)ORGANIZE FLOWCELL. And then analysis can be started.

ZenDesk Attachments Backup

Takes a ZenDesk XML dump backup file and searches for attachment URLs that match specified filename patterns. These are then downloaded to a local directory.

This script should be run manually on tools when the manual ZenDesk backup zip files are saved.

Usage

Run with a typical ZenDesk backup zip file (will look for tickets.xml inside the zip file):

zendesk_attachment_backup.py -i xml-export-yyyy-mm-dd-tttt-xml.zip

Alternatively, run directly on tickets.xml:

zendesk_attachment_backup.py -i ngisweden-yyyymmdd/tickets.xml
Usage

The scripts are compatible with Python 2.7+ and Python 3.

The instructions in below show how to get a copy of Python 2.7. You only need to do this once:

  1. Download & install Miniconda
wget https://repo.continuum.io/miniconda/Miniconda2-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh
  1. Tell the installer to prepend itself to your .bashrc file
  2. Log out and log in again, check that conda is in your path
  3. Create an environment for Python 2.7
conda create --name tools_py2.7 python pip
  1. Add it to your .bashrc file so it always loads
echo source activate tools_py2.7 >> .bashrc

Now Python 2.7 is installed, the zendesk attachment backup script should work. You can run it by going to the Zendesk backup directory and running it on any new downloads:

zendesk_attachment_backup.py <latest_backup>.zip
Dependencies
  • argparse
  • os
  • urllib2
  • re
  • sys
  • zipfile

SNIC API UTILS

snic_util.py is a python wrapper for SNIC API, to address most common/frequent purpose here at NGI. The subcommands available now are listed below.

Sub-commands
  • create_project - Create a GRUS delivery project with given information
  • extend_project - Extend the end date of GRUS project for given 'days'
  • project_info - Get information for specified GRUS project
  • user_info - Get SNIC information for specified user
  • change_pi - Change PI of mentioned GRUS project to given PI
  • change_sensitive - Change sensitivity of GRUS project

The script itself is more self explanatory, so python snic_util.py -h will give more info on Usage.

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