Skip to main content

image image image image image

fcsy: Python package for processing FCS

fcsy is developed based on Data File Standard for Flow Cytometry Version FCS 3.1

Installation

$ pip install fcsy

for working with s3:

$ pip install fcsy[s3]

Usage

Write and read fcs based on Dataframe

>>> import pandas as pd
>>> from fcsy import DataFrame

>>> data = [[1.0,2.0,3.0],[4.0,5.0,6.0]]
>>> columns = pd.MultiIndex.from_tuples(list(zip('abc', 'ABC')), names=["short", "long"])
>>> df = DataFrame(data, columns=columns)
>>> df
short    a    b    c
long     A    B    C
0      1.0  2.0  3.0
1      4.0  5.0  6.0

>>> df.to_fcs('sample.fcs')
>>> df = DataFrame.from_fcs('sample.fcs', channel_type='multi')
>>> df
short    a    b    c
long     A    B    C
0      1.0  2.0  3.0
1      4.0  5.0  6.0

Work with fcs metadata

Read fcs channels

>>> from fcsy import read_channels

>>> read_channels('sample.fcs', channel_type='multi')
MultiIndex([('a', 'A'),
            ('b', 'B'),
            ('c', 'C')],
           names=['short', 'long'])

Rename channels

>>> from fcsy import rename_channels, read_channels

>>> rename_channels('sample.fcs', {'a': 'a_1', 'b': 'b_1'}, channel_type='short')
>>> read_channels('sample.fcs', channel_type='multi')
MultiIndex([('a_1', 'A'),
            ('b_1', 'B'),
            (  'c', 'C')],
           names=['short', 'long'])


>>> rename_channels('sample.fcs', {'A': 'A_1', 'C': 'C_1'}, channel_type='long')
>>> read_channels('sample.fcs', channel_type='multi')
MultiIndex([('a_1', 'A_1'),
            ('b_1',   'B'),
            (  'c', 'C_1')],
           names=['short', 'long'])

Read events number

>>> from fcsy import read_events_num

>>> read_events_num('sample.fcs')
2

Work with files on aws s3

All apis support s3 url with the format: s3://{bucket}/{key}.

Write and read

>>> df.to_fcs('s3://sample-bucket/sample.fcs')
>>> df.from_fcs('s3://sample-bucket/sample.fcs', channel_type='multi')
short    a    b    c
long     A    B    C
0      1.0  2.0  3.0
1      4.0  5.0  6.0

Read channels

>>> read_channels('s3://sample-bucket/sample.fcs', channel_type='multi')
MultiIndex([('a', 'A'),
            ('b', 'B'),
            ('c', 'C')],
           names=['short', 'long'])

Read events number

>>> read_events_num('s3://sample-bucket/sample.fcs')
2

Documentation

The documentation is available on https://fcsy.readthedocs.io/

License

  • Free software: MIT license

History

Consult the Releases page for fixes and enhancements of each version.

Metadata

Release files for fcsy 0.10.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for fcsy 0.10.0
File Size Uploaded
fcsy-0.10.0.tar.gz 22.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for fcsy 0.10.0
File Interpreter ABI Platform
fcsy-0.10.0-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 33.5 kB

Release files / fcsy-0.10.0.tar.gz

Download URL fcsy-0.10.0.tar.gz
Size 22.4 kB
Tags Source
SHA-256 checksum
How to use checksums
4604002c44acc793cb2ef9842cb85698366c57c1a507d5acc7a196a728a9607e
BLAKE2b-256 checksum
How to use checksums
579fa2dd7d248d3703d8ec1b07da541de5173510b22c4fe053974d37e4d320e0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.10.4

Release files / fcsy-0.10.0-py2.py3-none-any.whl

Download URL fcsy-0.10.0-py2.py3-none-any.whl
Size 11.0 kB
Tags Python 2 Python 3
SHA-256 checksum
How to use checksums
5af3803071d35a32f6875878e0a6cb96bb8a33b61bac21569683b7e687f7f390
BLAKE2b-256 checksum
How to use checksums
09b4922a1c851f41b1ed011b5a4a63e5690012395409b7f845d20ed8be65fe04
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/4.0.0 CPython/3.10.4

Release history Release notifications | RSS feed

This release

0.10.0 This release

2 release files

0.9.0

2 release files

0.8.0

2 release files

0.7.0

2 release files

0.6.0

2 release files

0.5.0

2 release files

0.4.0

2 release files

0.3.1

2 release files

0.3.0

2 release files

0.2.1

2 release files

0.2.0

2 release files

0.1.0

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page