Holger Frey
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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.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) 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.
- parse_file(path_to_csv_file)
Parses a Sensospot csv file into a pandas data frame and will add some additional
meta data from the file name. Is internally also used by
parse_folder()
CLI
For the (propably) most important function, there is even a cli command
Usage: sensospot_parse [OPTIONS] SOURCE
Arguments:
SOURCE: Folder with Sensospot measurement
Options:
-o, --outfile TEXT Output file name, use a dash '-' for stdout, default:
'collected_data.csv'
-q, --quiet Ignore Sanity Check
-r, --recurse Recurse into folders one level down
--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