In R with FlowCore, the file 100715.fcs has sensible

Clarify parsing of examples/fcs_files/100715.fcs about flowio HOT 4 CLOSED

whitews commented on June 15, 2024

Clarify parsing of examples/fcs_files/100715.fcs

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whitews commented on June 15, 2024

Hi Benjamin,

I'm not seeing the same output for that file. Using the script:

from flowio import FlowData, __version__
import numpy as np
import pandas as pd

flow_data = FlowData('../examples/fcs_files/100715.fcs')

np_events_reshaped = np.reshape(flow_data.events, (-1, flow_data.channel_count))
df_events = pd.DataFrame(np_events_reshaped)
df_events_describe = df_events.describe()

pd.set_option('display.max_columns', None)
print(df_events_describe)

print(__version__)

I get the output:

                  0              1             2              3   \
count   65016.000000   65016.000000  65016.000000   65016.000000   
mean    44672.320312   43189.898438    331.918762    3203.209473   
std     16795.664062   12862.360352    555.111084    6042.640625   
min     23406.000000   27008.500000     -8.014621     -67.282539   
25%     34158.000000   33993.687500    168.284748    1988.901764   
50%     41644.250000   40842.875000    219.902458    2851.754395   
75%     50878.937500   49323.500000    278.990265    3344.790100   
max    262143.500000  256543.750000  46248.464844  261572.656250   

                  4              5              6              7   \
count   65016.000000   65016.000000   65016.000000   65016.000000   
mean     1253.388184    2342.416016    1507.453735    2668.065430   
std      3056.480957    4014.197021    5344.309082    5278.330078   
min       -67.119034     -44.558552     -79.819801    -110.409325   
25%       528.528076    1127.267487     738.003311    1302.372589   
50%       898.317688    1732.623718    1100.638245    1879.138245   
75%      1515.642242    2637.698792    1521.934418    2623.603210   
max    261566.531250  261455.734375  261584.765625  261410.890625   

                  8              9              10             11  \
count   65016.000000   65016.000000   65016.000000   65016.000000   
mean     2587.166504    4795.202148    2889.029785    4140.847656   
std      9648.791016    9937.980469    3198.799072    6172.310059   
min       -66.276711    -110.472748     -28.876564    -110.527817   
25%      1136.139801    2360.606567    1785.755310    2011.960175   
50%      1725.221863    3601.517822    2450.640381    3073.307739   
75%      2211.242126    4681.368652    3266.696472    4898.110107   
max    261585.406250  261586.531250  253481.906250  261539.921875   

                  12             13             14             15  
count   65016.000000   65016.000000   65016.000000   65016.000000  
mean     2629.491943    3336.955566    2536.822998    3581.059082  
std      4276.859863    7223.131348    4542.974121    6306.551758  
min       -89.503387     -51.957710     -61.939350     -33.256630  
25%      1462.618042    1812.386444    1411.367889    1940.519623  
50%      2159.566162    2705.184937    2117.235474    2812.368774  
75%      2993.534851    3459.337158    2751.399902    4092.057434  
max    261563.796875  261581.218750  261537.015625  261576.218750  
1.0.1

These values seem inline with what you report for flowCore. What version of FlowIO are you using? What python version and OS?

It should also be noted that FlowIO does not do any type of preprocessing on the event data (e.g. applying gain). It is meant as a low level input/output library for reading the exact contents of the FCS file. For analysis, flow data should be pre-processed and the related FlowKit library will do this automatically in the Sample class.

Thanks,
Scott

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berombau commented on June 15, 2024

Hi Scott,

Thank you for the quick reply. It seems to be a problem on my end. Depending on the package installation or environment, the weird values show up both on version 1.0.1 and Python 3.10 with my Mac M1 Pro laptop and CentOS 7 workstation. With a clean install, I can get the nice values on my laptop, but they still remain on the workstation. I'll try to debug some more later this week to reproduce the issue.

Thanks a lot already!

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whitews commented on June 15, 2024

Hmm, that is troubling. If you still have an environment where you see the odd values can you post the pip freeze requirements output here? My suspicion is that it may have something to do with NumPy dtypes during a conversion from the regular flat event data array to a NumPy array. You could also examine the values in the FlowData events array without using / converting to NumPy on those machines that exhibit the behavior. This would be very helpful in narrowing down where the issue is happening.

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berombau commented on June 15, 2024

I can't seem to reproduce it, so I think I just messed up two different files, the 100715.fcs one from FlowIO here and the example.fcs from readfcs here. The comment says it's originally the same, but they have different file sizes. Sorry for the trouble!

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Clarify parsing of examples/fcs_files/100715.fcs about flowio HOT 4 CLOSED

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