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Working with the fcs parser

ATTENTION The parser returns the data exactly as recorded in the file. This means that no transformations or compensation have been applied to this data. It is up to you to transform the data from this point for doing analysis and visualization.





In [1]:



    


%pylab inline



    


















    






Populating the interactive namespace from numpy and matplotlib

















In [2]:



    


import fcsparser

path = fcsparser.test_sample_path # path to a test data file that is included with the package

Unpack meta only





In [3]:



    


meta = fcsparser.parse(path, meta_data_only=True)
print type(meta)
print meta.keys()



    


















    






<type 'dict'>
[u'SAMPLE ID', u'$P7N', u'$ETIM', u'$P7E', u'$P7G', u'P8DISPLAY', u'SampleID', u'$P7B', u'FSC ASF', u'CYTNUM', u'$ENDDATA', u'P2DISPLAY', u'EXPORT USER NAME', u'$P7V', u'$ENDSTEXT', u'$P7R', u'LASER2NAME', u'CREATOR', u'LASER1DELAY', u'$P3V', u'$P11R', u'P4DISPLAY', u'$P11N', u'P2MS', u'THRESHOLD', u'$P11E', u'$SYS', u'$P11B', u'$P6B', u'$INST', u'$P6G', u'$P6E', u'APPLY COMPENSATION', u'$PAR', u'EXPORT TIME', u'$P6N', u'$P6R', u'$P6V', u'P9MS', u'$ENDANALYSIS', u'LASER4DELAY', u'$CYT', u'$BTIM', u'$P3E', u'$OP', u'$P1N', u'P1DISPLAY', u'$P1B', u'$P1G', u'$P1E', u'P7BS', u'$P1R', u'P3MS', u'P9BS', u'$P1V', u'PLATE NAME', u'$P9B', u'$P9G', u'$P9E', u'SPILL', u'$FIL', u'$P9R', u'$P9V', u'$DATE', u'WELL ID', u'P10BS', u'P6MS', u'LASER1ASF', u'P1BS', u'P2BS', u'LASER2ASF', u'$P8B', u'$P8E', u'P6BS', u'$P8V', u'$P10R', u'$P8N', u'P5BS', u'LASER4NAME', u'LASER4ASF', u'$P10N', u'$P10B', u'$P10E', u'$P10G', u'$P3R', u'P11MS', u'$SRC', u'$P3B', u'P4MS', u'$P3G', u'$BYTEORD', u'$P3N', u'P5DISPLAY', u'$TOT', u'P8MS', u'P11BS', u'EXPERIMENT NAME', u'$P2V', u'$P9N', u'WINDOW EXTENSION', u'$P2R', u'$BEGINSTEXT', u'LASER3DELAY', u'$P2G', u'$P2E', u'$P2B', u'$P2N', u'LASER3NAME', u'P7MS', u'$P5V', u'$P8G', '__header__', u'P7DISPLAY', u'$BEGINDATA', u'$DATATYPE', u'$TIMESTEP', u'P10MS', u'$P5R', u'$P5G', u'P10DISPLAY', u'$P5E', u'$P5B', u'$P5N', u'$BEGINANALYSIS', u'LASER1NAME', u'P5MS', u'$P10V', u'P8BS', u'GUID', u'P9DISPLAY', u'$P11G', u'$P8R', u'LASER3ASF', u'AUTOBS', u'P1MS', u'$MODE', u'$P4E', u'$P4G', u'P3BS', u'$P4B', u'$P4N', u'PLATE ID', u'$NEXTDATA', u'$P4V', u'$P4R', u'P4BS', u'TUBE NAME', u'LASER2DELAY']

Unpack meta and reformat





In [4]:



    


meta = fcsparser.parse(path, meta_data_only=True, reformat_meta=True)
meta['_channels_']



    


















    
Out[4]:










  
    

      
      $PnN
      $PnB
      $PnG
      $PnE
      $PnR
      $PnV
    

    

      Channel Number
      
      
      
      
      
      
    

  
  
    

      1
      FSC-A
      32
      1.0
      [0, 0]
      262144
      611
    

    

      2
      FSC-H
      32
      1.0
      [0, 0]
      262144
      611
    

    

      3
      FSC-W
      32
      1.0
      [0, 0]
      262144
      611
    

    

      4
      SSC-A
      32
      1.0
      [0, 0]
      262144
      210
    

    

      5
      SSC-H
      32
      1.0
      [0, 0]
      262144
      210
    

    

      6
      SSC-W
      32
      1.0
      [0, 0]
      262144
      210
    

    

      7
      FITC-A
      32
      1.0
      [0, 0]
      262144
      580
    

    

      8
      PerCP-Cy5-5-A
      32
      1.0
      [0, 0]
      262144
      580
    

    

      9
      AmCyan-A
      32
      1.0
      [0, 0]
      262144
      550
    

    

      10
      PE-TxRed YG-A
      32
      1.0
      [0, 0]
      262144
      500
    

    

      11
      Time
      32
      0.01
      [0, 0]
      262144
      None

Unpack meta and data





In [5]:



    


meta, data = fcsparser.parse(path, meta_data_only=False, reformat_meta=True)



    











In [6]:



    


print type(meta)
print type(data)



    


















    






<type 'dict'>
<class 'pandas.core.frame.DataFrame'>

















In [7]:



    


data



    


















    
Out[7]:










  
    

      
      FSC-A
      FSC-H
      FSC-W
      SSC-A
      SSC-H
      SSC-W
      FITC-A
      PerCP-Cy5-5-A
      AmCyan-A
      PE-TxRed YG-A
      Time
    

  
  
    

      0
      -28531.250000
      10
      0.000
      700.149963
      1656
      27708.351562
      98.799995
      54.149998
      164.220001
      120.360001
      0.200000
    

    

      1
      -49414.878906
      8
      0.000
      1275.849976
      2278
      36705.050781
      155.800003
      13.300000
      161.840012
      94.860001
      0.400000
    

    

      2
      -58684.320312
      14
      0.000
      -512.049988
      472
      0.000000
      22.799999
      8.550000
      172.550003
      85.680000
      0.500000
    

    

      3
      -3857.839844
      432
      0.000
      276.449982
      1339
      13530.564453
      -49.399998
      34.200001
      157.080002
      89.759995
      0.700000
    

    

      4
      22825.830078
      4606
      262143.000
      -505.399994
      472
      0.000000
      90.250000
      9.500000
      330.820007
      76.500000
      0.700000
    

    

      5
      17345.339844
      3708
      262143.000
      -341.049988
      586
      0.000000
      63.649998
      30.400000
      241.570007
      76.500000
      1.100000
    

    

      6
      -66212.421875
      5
      0.000
      1134.299927
      2062
      36051.152344
      180.500000
      -3.800000
      216.580017
      76.500000
      1.300000
    

    

      7
      -59752.527344
      1
      0.000
      -436.049988
      554
      0.000000
      -11.400000
      -7.600000
      151.130005
      68.339996
      1.300000
    

    

      8
      -17016.660156
      11
      0.000
      -209.000000
      749
      0.000000
      -91.199997
      0.950000
      252.280014
      44.879997
      1.500000
    

    

      9
      28728.789062
      5717
      262143.000
      -453.149994
      558
      0.000000
      76.949997
      23.750000
      133.279999
      56.099998
      1.600000
    

    

      10
      17430.000000
      3568
      262143.000
      -468.350006
      475
      0.000000
      66.500000
      -19.000000
      99.960007
      59.160000
      1.700000
    

    

      11
      24527.330078
      4681
      262143.000
      -76.949997
      931
      0.000000
      189.050003
      3.800000
      320.110016
      75.479996
      2.000000
    

    

      12
      -42823.847656
      2
      0.000
      -410.399994
      548
      0.000000
      19.000000
      5.700000
      199.920013
      26.520000
      2.300000
    

    

      13
      -61499.679688
      4
      0.000
      -91.199997
      882
      0.000000
      12.349999
      23.750000
      127.330009
      23.459999
      3.000000
    

    

      14
      -61684.769531
      4
      0.000
      -240.349991
      774
      0.000000
      98.799995
      -14.250000
      51.170002
      -17.340000
      3.000000
    

    

      15
      -62284.859375
      9
      0.000
      94.049995
      1139
      5411.466309
      30.400000
      49.399998
      173.740005
      -21.420000
      3.100000
    

    

      16
      -57402.800781
      4
      0.000
      -438.899994
      463
      0.000000
      131.099991
      -39.899998
      139.230011
      28.559999
      3.100000
    

    

      17
      44351.050781
      8240
      262143.000
      103.549995
      1179
      5755.939453
      -50.349998
      -26.600000
      60.690002
      10.200000
      3.400000
    

    

      18
      52054.277344
      9440
      262143.000
      314.449982
      1179
      17479.044922
      -178.599991
      -14.250000
      59.500004
      -6.120000
      3.500000
    

    

      19
      54260.417969
      9800
      262143.000
      -29.449999
      950
      0.000000
      208.050003
      -38.950001
      153.510010
      24.480000
      3.500000
    

    

      20
      33469.750000
      6408
      262143.000
      -299.250000
      606
      0.000000
      -34.200001
      -13.300000
      57.120003
      -23.459999
      3.600000
    

    

      21
      15418.080078
      3030
      262143.000
      -190.949997
      804
      0.000000
      47.500000
      -41.799999
      58.310001
      -31.619999
      3.700000
    

    

      22
      -29567.089844
      12
      0.000
      1451.599976
      2406
      39539.507812
      228.949997
      -16.150000
      160.650009
      12.240000
      3.800000
    

    

      23
      5559.339844
      1384
      262143.000
      -434.149994
      418
      0.000000
      -104.500000
      -3.800000
      95.200005
      -6.120000
      3.900000
    

    

      24
      5126.909668
      1428
      235292.125
      -134.899994
      854
      0.000000
      24.699999
      18.049999
      133.279999
      12.240000
      3.900000
    

    

      25
      34302.238281
      23089
      97363.750
      1101.049927
      1726
      41806.730469
      50.349998
      -38.000000
      114.240005
      45.899998
      4.100000
    

    

      26
      -52817.878906
      9
      0.000
      334.399994
      1279
      17134.666016
      -133.949997
      0.950000
      -48.790001
      13.260000
      4.200000
    

    

      27
      -47389.679688
      8
      0.000
      -144.399994
      710
      0.000000
      33.250000
      -4.750000
      17.850000
      -8.160000
      4.200000
    

    

      28
      -42845.429688
      5
      0.000
      1240.699951
      2238
      36331.777344
      20.900000
      18.049999
      120.190002
      24.480000
      4.200000
    

    

      29
      -19319.080078
      8
      0.000
      296.399994
      1266
      15343.499023
      -69.349998
      -15.200000
      33.320000
      17.340000
      4.200000
    

    

      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
      ...
    

    

      14915
      -22298.779297
      12
      0.000
      901.549988
      870
      67912.625000
      -165.300003
      23.750000
      16.660000
      18.360001
      1001.000000
    

    

      14916
      -26106.820312
      10
      0.000
      981.349976
      984
      65359.507812
      42.750000
      19.000000
      -1.190000
      7.140000
      1001.000000
    

    

      14917
      -19690.919922
      15
      0.000
      2438.649902
      2301
      69456.484375
      2530.800049
      -2.850000
      29.750002
      -1.020000
      1001.000000
    

    

      14918
      34640.878906
      7101
      262143.000
      1294.849976
      1279
      66348.156250
      184.300003
      320.149994
      1087.660034
      3080.399902
      1001.000000
    

    

      14919
      37935.148438
      7260
      262143.000
      481.649994
      450
      70145.367188
      68.400002
      -1.900000
      21.420002
      -24.480000
      1001.099976
    

    

      14920
      -47467.699219
      13
      0.000
      1153.299927
      1139
      66358.789062
      94.049995
      -8.550000
      -23.800001
      37.739998
      1001.599976
    

    

      14921
      -42225.417969
      13
      0.000
      1374.650024
      1303
      69139.734375
      -46.549999
      -19.000000
      52.360001
      19.379999
      1001.599976
    

    

      14922
      -39570.250000
      8
      0.000
      2337.000000
      2214
      69176.890625
      2817.699951
      26.600000
      222.530014
      10.200000
      1001.599976
    

    

      14923
      -55350.207031
      0
      262143.000
      591.849976
      566
      68529.109375
      48.450001
      59.849998
      -1.190000
      20.400000
      1001.799988
    

    

      14924
      -35747.269531
      9
      0.000
      2230.599854
      2115
      69118.007812
      3297.449951
      -6.650000
      64.260002
      -22.439999
      1001.799988
    

    

      14925
      -25881.888672
      4
      0.000
      1066.849976
      991
      70552.054688
      104.500000
      -3.800000
      -32.130001
      42.840000
      1001.900024
    

    

      14926
      -12305.580078
      5
      0.000
      724.849976
      686
      69247.476562
      96.900002
      -13.300000
      24.990002
      -13.260000
      1001.900024
    

    

      14927
      -3449.479980
      13
      0.000
      1695.750000
      1527
      72778.437500
      -63.649998
      7.600000
      10.710001
      18.360001
      1002.000000
    

    

      14928
      37962.539062
      6384
      262143.000
      1679.599976
      1627
      67654.742188
      -92.150002
      8.550000
      35.700001
      -6.120000
      1002.099976
    

    

      14929
      56014.207031
      10781
      262143.000
      2150.800049
      2027
      69538.648438
      377.149994
      474.049988
      1669.570068
      4133.040039
      1002.099976
    

    

      14930
      68764.671875
      11966
      262143.000
      3408.599854
      3240
      68946.304688
      1238.799927
      28.500000
      121.380005
      -1.020000
      1002.200012
    

    

      14931
      42695.199219
      7835
      262143.000
      1944.650024
      1389
      91752.765625
      1368.000000
      17.100000
      217.770004
      -8.160000
      1002.200012
    

    

      14932
      28975.298828
      5532
      262143.000
      707.750000
      646
      71800.468750
      -0.950000
      -8.550000
      32.130001
      32.639999
      1002.200012
    

    

      14933
      31328.349609
      5532
      262143.000
      1510.500000
      1498
      66082.859375
      53.200001
      7.600000
      34.510002
      14.280000
      1002.200012
    

    

      14934
      -27985.939453
      9
      0.000
      859.750000
      759
      74235.281250
      187.149994
      9.500000
      29.750002
      41.820000
      1002.299988
    

    

      14935
      -41983.058594
      12
      0.000
      2090.000000
      1938
      70676.085938
      455.049988
      407.549988
      1264.970093
      4071.839844
      1002.400024
    

    

      14936
      -40131.328125
      5
      0.000
      589.000000
      558
      69176.890625
      28.500000
      -6.650000
      10.710001
      16.320000
      1002.400024
    

    

      14937
      -44740.320312
      8
      0.000
      442.699982
      418
      69408.570312
      -111.150002
      13.300000
      45.220001
      27.539999
      1002.400024
    

    

      14938
      -43414.808594
      0
      262143.000
      496.850006
      475
      68550.664062
      -64.599998
      5.700000
      -35.700001
      32.639999
      1002.500000
    

    

      14939
      -52364.699219
      5
      0.000
      1444.000000
      1335
      70886.882812
      55.099998
      -5.700000
      -23.800001
      -27.539999
      1002.599976
    

    

      14940
      -28177.669922
      4
      0.000
      1650.150024
      1551
      69725.484375
      157.699997
      398.049988
      1391.110107
      2730.540039
      1002.700012
    

    

      14941
      -19354.769531
      7
      0.000
      1086.799927
      1073
      66378.867188
      56.049999
      -12.349999
      -15.470001
      -14.280000
      1002.700012
    

    

      14942
      12428.419922
      2658
      262143.000
      496.850006
      496
      65648.312500
      -24.699999
      -9.500000
      10.710001
      -7.140000
      1002.700012
    

    

      14943
      21995.000000
      4392
      262143.000
      558.599976
      514
      71222.585938
      67.449997
      -12.349999
      14.280001
      -5.100000
      1002.700012
    

    

      14944
      68924.859375
      12210
      262143.000
      690.649963
      564
      80252.546875
      32.299999
      -37.049999
      10.710001
      -5.100000
      1002.900024
    

  



14945 rows × 11 columns

Untransformed data

The plot below is a plot of the raw data as recorded in the file. Specifically, no compensation or transformation has been applied to this data.

To better visualize this data you might want to take a look at either hlog or logicle transformations.





In [8]:



    


scatter(data['FITC-A'], data['AmCyan-A'], alpha=0.8, color='gray')



    


















    
Out[8]:








<matplotlib.collections.PathCollection at 0x7fb3c34d7f50>

Content source: eyurtsev/fcsparser

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