Holger Frey
6f5fe4831f
|
2 years ago | |
---|---|---|
docs | 2 years ago | |
example_data | 2 years ago | |
src/sensospot_parser | 2 years ago | |
tests | 2 years ago | |
.gitignore | 2 years ago | |
.pre-commit-config.yaml | 2 years ago | |
CHANGES.md | 2 years ago | |
CONTRIBUTING.md | 5 years ago | |
LICENSE | 5 years ago | |
Makefile | 2 years ago | |
README.md | 2 years ago | |
mkdocs.yml | 2 years ago | |
pyproject.toml | 2 years ago | |
tox.ini | 2 years ago |
README.md
Sensospot Data Parser
Parsing the numerical output from SensoSpot microarray analysis.
The SensoSpot microarray analyzer is an automated fluorescence microscope with an image analysis software for detecting and measuring microarrays. The original name of the product was "FLAIR" by the company Sensovation, that was later acquired by Miltenyi.
There is no affiliation on my side regarding Sensovation or Miltenyi, I just use the product and needed a way to make the data available for further analysis.
Example:
import sensospot_parser
# read the raw data of a folder
raw_data = sensospot_parser.parse_folder(<path to results directory>)
sorted(raw_data.columns) == [
'Analysis.Datetime', 'Analysis.Image', 'Analysis.Name',
'Bkg.Area', 'Bkg.Mean', 'Bkg.Median', 'Bkg.StdDev', 'Bkg.Sum',
'Exposure.Id',
'Parameters.Channel', 'Parameters.Time',
'Pos.Id', 'Pos.Nom.X', 'Pos.Nom.Y', 'Pos.X', 'Pos.Y',
'Spot.Area', 'Spot.Diameter', 'Spot.Found', 'Spot.Mean', 'Spot.Median',
'Spot.Saturation', 'Spot.StdDev', 'Spot.Sum',
'Well.Column', 'Well.Name', 'Well.Row'
]
Constants
There is a columns
module available, providing constans that define the column names.
import sensospot_parser
sensospot_parser.columns.ANALYSIS_NAME == "Analysis.Name"
Avaliable public functions:
- parse_folder(path_to_folder)
Tries the
parse_xml_folder()
function first and if an error occurs, it falls back to theparse_csv_folder()
- parse_xml_folder(path_to_folder) Searches the folder for a parsable Sensospot XML result file and parses it into a pandas data frame. It will add additional meta data from parameters folder, if it is present.
- parse_csv_folder(path_to_folder) Searches the folder for parsable Sensospot .csv files, parses them into one big pandas data frame and will add additional meta data from parameters folder, if it is present.
CLI
For the (propably) most important function, there is a cli command
Usage: sensospot_parse [OPTIONS] SOURCES
Arguments:
SOURCES: One or more folders with Sensospot measurements
Options:
-o, --output FILE Output file path, defaults to 'collected_data.csv'
-q, --quiet Ignore sanity check for csv file parsing
--help Show this message and exit.
Development
To install the development version of Sensovation Data Parser:
git clone https://git.cpi.imtek.uni-freiburg.de/holgi/sensospot_data.git
# create a virtual environment and install all required dev dependencies
cd sensospot_data
make devenv
To run the tests, use make tests
(failing on first error) or make coverage
for a complete report.
To generate the documentation pages use make docs
or make serve-docs
for
starting a webserver with the generated documentation