On Sat, May 3, 2014 at 10:20 PM, Clara Tang <clara...@gmail.com> wrote:
> Thanks so much for your advice. I have now upgraded the R to the latest
> version and reinstall the aroma libraries. Do I need to rerun all
> procedures, e.g. crmav2, or simply the mscn?

No need to rerun the CRMAv2 pipeline - those results are unaffected by
that bug.  (BTW, by the nature of aroma, if you did, aroma would
quickly skip over already processed parts so in the end of the day it
doesn't matter).

/Henrik

>
> Regards,
> Clara
>
> On Sunday, April 27, 2014 5:35:47 PM UTC+8, Clara Tang wrote:
>>
>> Hi,
>>
>> I am trying to perform cross platform normalization for CytoScan and Omni
>> using MSCN but the program stops after smoothing. I imported the Affymetrix
>> raw intensity data and called the totalCn and Baf using CRMAv2 and CalMate.
>> LogR ratio (log2 scale) and BAF were extracted using GenomeStudio for Omni
>> and imported as 2^LRR*2 and BAF into .total.asb and .fracB.asb respectively.
>> Plotting the CN indicated similar level of mean intensities for both
>> platforms (CN~1) and thereby I proceeded to perform the mscn. Smoothing
>> looks normal but after that, the program seemed to stop while
>> backtransforming.
>>
>> May I know how I can overcome the error of  smooth.spline(sKK, lambda,
>> ...)?? What's wrong in my data?
>>
>> Thanks a lot!!!!!!
>>
>> --Clara
>>
>> P.S. Log file is pasted as below,
>>
>> =====================================================
>> dsNList <- process(mscn, verbose=log)
>> 20140427 17:06:46|Multi-source normalize all samples...
>> 20140427 17:06:46| Number of unique samples in all sets: 8
>>   chr [1:8] "9C" "9C-2" "2C" "2C-2" "4C" ...
>> 20140427 17:06:46| Processing each array...
>> 20140427 17:06:46|  Sample #1 ('9C') of 8...
>> 20140427 17:06:46|   Identifying source data files...
>> 20140427 17:06:46|    Getting list tuple of data files for one sample...
>> 20140427 17:06:46|     Sample name: 9C
>> 20140427 17:06:47|     Number of arrays: 2
>> 20140427 17:06:47|    Getting list tuple of data files for one
>> sample...done
>>     [[1]]
>>     AromaUnitTotalCnBinaryFile:
>>     Name: 9C
>>     Tags: total
>>     Full name: 9C,total
>>     Pathname:
>> totalAndFracBData/Cytoscan,ACC,ra,-XY,BPN,-XY,AVG,FLN,-XY,CMTN,v2/CytoScanHD_Array/9C,total.asb
>>     File size: 10.77 MB (11288937 bytes)
>>     RAM: 0.01 MB
>>     Number of data rows: 2822125
>>     File format: v1
>>     Dimensions: 2822125x1
>>     Column classes: double
>>     Number of bytes per column: 4
>>     Footer: <createdOn>20140421 18:35:53
>> HKT</createdOn><platform>Affymetrix</platform><chipType>CytoScanHD_Array</chipType><srcFile><srcDataSet>Cytoscan,ACC,ra,-XY,BPN,-XY,AVG,FLN,-XY</srcDataSet><srcChipType>CytoScanHD_Array,monocell</srcChipType><srcFullName>9C,chipEffects</srcFullName><srcChecksum>7d70e31c6aa60b7d8664373333ad5452</srcChecksum></srcFile>
>>     Platform: Affymetrix
>>     Chip type: CytoScanHD_Array
>>
>>     [[2]]
>>     AromaUnitTotalCnBinaryFile:
>>     Name: 9C
>>     Tags:9C,ratio,total
>>     Full name: 9C,9C,ratio,total
>>     Pathname: totalAndFracBData/Omni/HumanOmni2.5/9C,9C,ratio,total.asb
>>     File size: 9.08 MB (9519600 bytes)
>>     RAM: 0.01 MB
>>     Number of data rows: 2379855
>>     File format: v1
>>     Dimensions: 2379855x1
>>     Column classes: double
>>     Number of bytes per column: 4
>>     Footer: <createdOn>20140427 16:14:31
>> HKT</createdOn><platform>Illumina</platform><chipType>HumanOmni2.5</chipType>
>>     Platform: Illumina
>>     Chip type: HumanOmni2.5
>>
>> 20140427 17:06:47|   Identifying source data files...done
>> 20140427 17:06:47|   Check if all arrays are already normalized...
>> 20140427 17:06:47|    Is done: FALSE
>> 20140427 17:06:47|   Check if all arrays are already normalized...done
>> 20140427 17:06:47|   Fitting model...
>> 20140427 17:06:47|    Fitting one sample across multiple sources...
>> 20140427 17:06:47|     Number of arrays: 2
>> 20140427 17:06:47|     Sample name: 9C
>>      List of 4
>>       $ subsetToFit    : int [1:28781] 1 2 3 4 5 6 7 8 9 10 ...
>>       $ fitUgp         :Classes 'AromaUgpFile',
>> 'AromaUnitChromosomeTabularBinaryFile', 'AromaUnitTabularBinaryFile',
>> 'UnitAnnotationDataFile', 'AromaMicroarrayTabularBinaryFile',
>> 'AromaPlatformInterface', 'AromaTabularBinaryFile', 'FileCacheKeyInterface',
>> 'CacheKeyInterface', 'GenericTabularFile', 'ColumnNamesInterface',
>> 'GenericDataFile', 'FullNameInterface', 'Object'  atomic [1:1] NA
>>        .. ..- attr(*, ".env")=<environment: 0x3c8f518>
>>       $ align          : chr "byChromosome"
>>       $ targetDimension: int 1
>> 20140427 17:06:47|     Getting list tuple of data files for one sample...
>> 20140427 17:06:47|      Sample name: 9C
>> 20140427 17:06:47|      Number of arrays: 2
>> 20140427 17:06:47|     Getting list tuple of data files for one
>> sample...done
>>      List of 2
>>       $ :Classes 'AromaUnitTotalCnBinaryFile', 'CopyNumberDataFile',
>> 'AromaUnitSignalBinaryFile', 'AromaPlatformInterface',
>> 'AromaTabularBinaryFile', 'FileCacheKeyInterface', 'CacheKeyInterface',
>> 'GenericTabularFile', 'ColumnNamesInterface', 'GenericDataFile',
>> 'FullNameInterface', 'Object'  atomic [1:1] NA
>>        .. ..- attr(*, ".env")=<environment: 0x67be7f0>
>>       $ :Classes 'AromaUnitTotalCnBinaryFile', 'CopyNumberDataFile',
>> 'AromaUnitSignalBinaryFile', 'AromaPlatformInterface',
>> 'AromaTabularBinaryFile', 'FileCacheKeyInterface', 'CacheKeyInterface',
>> 'GenericTabularFile', 'ColumnNamesInterface', 'GenericDataFile',
>> 'FullNameInterface', 'Object'  atomic [1:1] NA
>>        .. ..- attr(*, ".env")=<environment: 0x36d2f48>
>> 20140427 17:06:47|     Extracting data...
>> 20140427 17:06:47|      Subset of units used for fitting:
>>        int [1:28781] 1 2 3 4 5 6 7 8 9 10 ...
>>        num [1:28781, 1:2] 0.561 0.566 0.798 0.861 0.81 ...
>>              V1                V2
>>        Min.   :-0.7285   Min.   :-1.9090
>>        1st Qu.: 0.9677   1st Qu.: 0.9403
>>        Median : 0.9842   Median : 0.9838
>>        Mean   : 0.9805   Mean   : 0.9898
>>        3rd Qu.: 0.9995   3rd Qu.: 1.0340
>>        Max.   : 1.3343   Max.   : 1.9075
>>        NA's   :1865      NA's   :1934
>> 20140427 17:06:48|     Extracting data...done
>> 20140427 17:06:48|     Fitting across-source normalization function...
>> 20140427 17:06:48|      Estimator for principal curves:
>>       function (Y, ...)
>>        - attr(*, "smoother")=function (lambda, xj, ...)
>>        - attr(*, "df")= num 5
>> 20140427 17:07:52|      Fitting time:
>>          user  system elapsed
>>        63.884   0.008  64.062
>> 20140427 17:07:52|      Direction of fitted curve ('lambda') was flipped
>> such that it increases with the signal.
>> 20140427 17:07:52|      Processing time: 64.1 seconds
>>       List of 7
>>        $ s              : num [1:28781, 1:2] 0.652 0.652 0.665 NA 0.836
>> ...
>>        $ tag            : num [1:28781] 15371 15372 7262 NA 15373 ...
>>        $ lambda         : num [1:28781] 1.99 1.99 1.93 NA 1.38 ...
>>        $ dist           : num 31.6
>>        $ converged      : logi TRUE
>>        $ nbrOfIterations: int 6
>>        $ call           : language principal.curve(x = X, smoother = ..1,
>> trace = trace)
>>        - attr(*, "class")= chr [1:2] "PrincipalCurve" "principal.curve"
>>        - attr(*, "processingTime")=Class 'proc_time'  Named num [1:5] 63.8
>> 0.004 63.975 0 0
>>         .. ..- attr(*, "names")= chr [1:5] "user.self" "sys.self"
>> "elapsed" "user.child" ...
>> 20140427 17:07:52|     Fitting across-source normalization function...done
>> 20140427 17:07:52|     Calculating shift for each chromosome...
>> 20140427 17:07:52|      align=byChromosome
>> 20140427 17:07:52|      Chromosomes: 1-25
>> 20140427 17:07:52|      Grouping units by chromosome...
>>        List of 24
>>         $ Chr01: int [1:2472] 1 2 3 4 5 6 7 8 9 10 ...
>>         $ Chr02: int [1:2434] 2473 2474 2475 2476 2477 2478 2479 2480 2481
>> 2482 ...
>>         $ Chr03: int [1:1995] 4907 4908 4909 4910 4911 4912 4913 4914 4915
>> 4916 ...
>>         $ Chr04: int [1:1917] 6902 6903 6904 6905 6906 6907 6908 6909 6910
>> 6911 ...
>>         $ Chr05: int [1:1810] 8819 8820 8821 8822 8823 8824 8825 8826 8827
>> 8828 ...
>>         $ Chr06: int [1:1709] 10629 10630 10631 10632 10633 10634 10635
>> 10636 10637 10638 ...
>>         $ Chr07: int [1:1589] 12338 12339 12340 12341 12342 12343 12344
>> 12345 12346 12347 ...
>>         $ Chr08: int [1:1463] 13927 13928 13929 13930 13931 13932 13933
>> 13934 13935 13936 ...
>>         $ Chr09: int [1:1405] 15390 15391 15392 15393 15394 15395 15396
>> 15397 15398 15399 ...
>>         $ Chr10: int [1:1355] 16795 16796 16797 16798 16799 16800 16801
>> 16802 16803 16804 ...
>>         $ Chr11: int [1:1350] 18150 18151 18152 18153 18154 18155 18156
>> 18157 18158 18159 ...
>>         $ Chr12: int [1:1335] 19500 19501 19502 19503 19504 19505 19506
>> 19507 19508 19509 ...
>>         $ Chr13: int [1:1142] 20835 20836 20837 20838 20839 20840 20841
>> 20842 20843 20844 ...
>>         $ Chr14: int [1:1064] 21977 21978 21979 21980 21981 21982 21983
>> 21984 21985 21986 ...
>>         $ Chr15: int [1:1004] 23041 23042 23043 23044 23045 23046 23047
>> 23048 23049 23050 ...
>>         $ Chr16: int [1:900] 24045 24046 24047 24048 24049 24050 24051
>> 24052 24053 24054 ...
>>         $ Chr17: int [1:817] 24945 24946 24947 24948 24949 24950 24951
>> 24952 24953 24954 ...
>>         $ Chr18: int [1:778] 25762 25763 25764 25765 25766 25767 25768
>> 25769 25770 25771 ...
>>         $ Chr19: int [1:639] 26540 26541 26542 26543 26544 26545 26546
>> 26547 26548 26549 ...
>>         $ Chr20: int [1:637] 27179 27180 27181 27182 27183 27184 27185
>> 27186 27187 27188 ...
>>         $ Chr21: int [1:470] 27816 27817 27818 27819 27820 27821 27822
>> 27823 27824 27825 ...
>>         $ Chr22: int [1:496] 28286 28287 28288 28289 28290 28291 28292
>> 28293 28294 28295 ...
>>         $ Chr23: int [1:1550] 28782 28783 28784 28785 28786 28787 28788
>> 28789 28790 28791 ...
>>         $ Chr24: int [1:578] 30332 30333 30334 30335 30336 30337 30338
>> 30339 30340 30341 ...
>> 20140427 17:07:52|      Grouping units by chromosome...done
>> 20140427 17:07:52|      Allocating matrix for smooth data...
>> 20140427 17:07:52|       RAM: 494760 bytes
>> 20140427 17:07:52|      Allocating matrix for smooth data...done
>> 20140427 17:07:52|      Loading and backtransforming *smoothed* data...
>> 20140427 17:07:52|       Source #1 ('9C,total') of 2...
>> 20140427 17:07:52|        Loading smoothed data...
>>           num [1:30910] 0.561 0.566 0.798 0.861 0.81 ...
>> 20140427 17:07:52|        Loading smoothed data...done
>> 20140427 17:07:52|        Backtransforming smoothed data...
>> Error in smooth.spline(sKK, lambda, ...) :
>>   missing or infinite values in inputs are not allowed
>> 20140427 17:07:52|        Backtransforming smoothed data...done
>> 20140427 17:07:52|       Source #1 ('9C,total') of 2...done
>> 20140427 17:07:52|      Loading and backtransforming *smoothed*
>> data...done
>> 20140427 17:07:52|     Calculating shift for each chromosome...done
>> 20140427 17:07:52|    Fitting one sample across multiple sources...done
>> 20140427 17:07:52|   Fitting model...done
>> 20140427 17:07:52|  Sample #1 ('9C') of 8...done
>> 20140427 17:07:52| Processing each array...done
>> 20140427 17:07:52|Multi-source normalize all samples...done
>>
> --
> --
> When reporting problems on aroma.affymetrix, make sure 1) to run the latest
> version of the package, 2) to report the output of sessionInfo() and
> traceback(), and 3) to post a complete code example.
>
>
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-- 
-- 
When reporting problems on aroma.affymetrix, make sure 1) to run the latest 
version of the package, 2) to report the output of sessionInfo() and 
traceback(), and 3) to post a complete code example.


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