[BioC] CGHcall error
Daniel Rico
drico at cnio.es
Tue Feb 5 12:44:38 CET 2008
hits=-2.6 tests=BAYES_00
X-USF-Spam-Flag: NO
Dear List,
I am trying to use CGHcall function from CGHcall package, trying to use
my own normalized and segmented dataframes (Agilent oligo Human 44A,
data normalized with MANOR and segmented with GLAD), buy I get this error:
EM algorithm started ...
Error en regionsdat[k, 1]:regionsdat[k, 2] : Argumento NA/NaN
Which I don't get when I use Wilting data from the vignette example, so
it could be a problem with the format of my data (although I can't find
any...). I wondered if maybe the dataframes were too large, but I also
get (another) error if I only run CGHcall with 1 chromosome:
EM algorithm done ...
Error en (posteriorfin2[profile == k, ])[, -1] :
número incorreto de dimensiones # Incorrect dimension number
I would appreciate any suggestion.
Best,
Daniel
Details:
> load("norm3.RData")
> load("seg3.RData")
> library(CGHcall)
Loading required package: impute
Loading required package: DNAcopy
> ls()
[1] "norm3" "seg3"
> head(norm3)
BAC.clone Chromosome bp.position X13713 X13819 X13820 X13821 X13822 X13859
1 1:604268 1 604268 0.05 0.10 0.40 -0.05 0.24 0.27
2 1:801796 1 801796 0.17 -0.15 0.03 -0.12 -0.05 0.05
3 1:827354 1 827354 0.13 0.15 0.11 0.17 0.01 -0.17
4 1:1059676 1 1059676 0.03 -0.18 0.00 -0.11 -0.10 -0.29
5 1:1089934 1 1089934 -0.23 -0.02 0.47 0.07 0.14 0.13
6 1:1139597 1 1139597 0.11 -0.05 0.03 0.03 0.08 0.06
X13860 X13862 X15740 X16421 X16422 X16578 X16579 X17264 X17274 X17278
X17279
1 -0.07 0.64 0.31 0.39 0.10 0.39 0.47 -0.08 -0.08
0.07 0.10
2 0.19 -0.23 0.12 0.09 -0.17 0.01 -0.09 -0.07 -0.07
0.07 0.24
3 -0.05 -0.17 0.32 0.03 -0.16 0.02 0.02 0.00 0.00
0.25 0.04
4 0.01 -0.33 -0.19 -0.10 -0.02 -0.17 -0.13 -0.30 -0.30 -0.03
-0.13
5 -0.02 0.18 -0.08 -0.92 -0.94 -0.02 0.12 0.16 0.16
-0.02 0.09
6 0.07 0.19 0.09 0.18 0.11 -0.03 0.04 0.16 0.16
0.01 0.01
X17385 X17386 X17388 X17446 X17447 X17448
1 0.52 -0.63 -0.50 0.24 0.05 0.60
2 -0.19 -0.26 0.08 -0.01 0.17 0.05
3 -0.12 -0.01 0.20 -0.15 -0.04 0.00
4 -0.08 -0.12 -0.05 -0.01 -0.01 0.07
5 -0.09 0.17 0.17 0.25 0.33 0.42
6 0.17 0.48 0.19 0.24 0.39 0.36
> head(seg3)
BAC.clone Chromosome bp.position X13713 X13819 X13820 X13821 X13822 X13859
1 1:604268 1 604268 0.02 0 0.01 0.01 0.01 -0.01
2 1:801796 1 801796 0.02 0 0.01 0.01 0.01 -0.01
3 1:827354 1 827354 0.02 0 0.01 0.01 0.01 -0.01
4 1:1059676 1 1059676 0.02 0 0.01 0.01 0.01 -0.01
5 1:1089934 1 1089934 0.02 0 0.01 0.01 0.01 -0.01
6 1:1139597 1 1139597 0.02 0 0.01 0.01 0.01 -0.01
X13860 X13862 X15740 X16421 X16422 X16578 X16579 X17264 X17274 X17278
X17279
1 0 0.01 -0.01 0 -0.01 0.01 0.02 0.03 0.03 0.03
-0.01
2 0 0.01 -0.01 0 -0.01 0.01 0.02 0.03 0.03 0.03
-0.01
3 0 0.01 -0.01 0 -0.01 0.01 0.02 0.03 0.03 0.03
-0.01
4 0 0.01 -0.01 0 -0.01 0.01 0.02 0.03 0.03 0.03
-0.01
5 0 0.01 -0.01 0 -0.01 0.01 0.02 0.03 0.03 0.03
-0.01
6 0 0.01 -0.01 0 -0.01 0.01 0.02 0.03 0.03 0.03
-0.01
X17385 X17386 X17388 X17446 X17447 X17448
1 -0.08 -0.43 0.02 0.01 0.01 -0.01
2 -0.08 -0.43 0.02 0.01 0.01 -0.01
3 -0.08 0.02 0.02 0.01 0.01 -0.01
4 -0.08 0.02 0.02 0.01 0.01 -0.01
5 -0.08 0.02 0.02 0.01 0.01 -0.01
6 -0.08 0.02 0.02 0.01 0.01 -0.01
> dim(norm3)
[1] 37203 26
> dim(seg3)
[1] 37203 26
> args(CGHcall)
function (inputNormalized, inputSegmented, typeNormalized = "dataframe",
typeSegmented = "dataframe", prior = "auto", nclass = 3,
organism = "human")
NULL
> Result <- CGHcall(norm3, seg3, organism="human")
Dividing chromosomes into arms:
New chromosome: 1 Arm: 1
Centromere found: 122356957 Arm: 2
New chromosome: 2 Arm: 3
Centromere found: 93189898 Arm: 4
New chromosome: 3 Arm: 5
Centromere found: 92037544 Arm: 6
New chromosome: 4 Arm: 7
Centromere found: 50854874 Arm: 8
New chromosome: 5 Arm: 9
Centromere found: 47941398 Arm: 10
New chromosome: 6 Arm: 11
Centromere found: 60438125 Arm: 12
New chromosome: 7 Arm: 13
Centromere found: 59558273 Arm: 14
New chromosome: 8 Arm: 15
Centromere found: 45458052 Arm: 16
New chromosome: 9 Arm: 17
Centromere found: 48607499 Arm: 18
New chromosome: 10 Arm: 19
Centromere found: 40434941 Arm: 20
New chromosome: 11 Arm: 21
Centromere found: 52950781 Arm: 22
New chromosome: 12 Arm: 23
Centromere found: 35445461 Arm: 24
New chromosome: 13 Arm: 25
Centromere found: 16934000 Arm: 26
New chromosome: 14 Arm: 27
Centromere found: 16570000 Arm: 28
New chromosome: 15 Arm: 29
Centromere found: 16760000 Arm: 30
New chromosome: 16 Arm: 31
Centromere found: 36043302 Arm: 32
New chromosome: 17 Arm: 33
Centromere found: 22237133 Arm: 34
New chromosome: 18 Arm: 35
Centromere found: 16082897 Arm: 36
New chromosome: 19 Arm: 37
Centromere found: 28423622 Arm: 38
New chromosome: 20 Arm: 39
Centromere found: 27150400 Arm: 40
New chromosome: 21 Arm: 41
Centromere found: 11760000 Arm: 42
New chromosome: 22 Arm: 43
Centromere found: 12830000 Arm: 44
EM algorithm started ...
Error en regionsdat[k, 1]:regionsdat[k, 2] : Argumento NA/NaN
# I also tried with just one chromosome, but:
> Result <- CGHcall(norm3[norm3$Chromosome=="1",],
seg3[norm3$Chromosome=="1",], organism="human")
Dividing chromosomes into arms:
New chromosome: 1 Arm: 1
Centromere found: 122356957 Arm: 2
EM algorithm started ...
Calling iteration 1 :
[1] 2.300000e+01 -4.372806e+04 -1.367577e+00 -4.412366e-01 -2.586618e-03
[6] 4.344142e-01 1.170159e+00 3.031326e-01 1.226376e-01 3.581388e-02
[11] 2.452344e-01 -2.338149e-03
Calling iteration 2 :
[1] 2.300000e+01 -4.372728e+04 -1.433100e+00 -4.457681e-01 -2.129149e-03
[6] 4.289389e-01 1.159208e+00 2.682406e-01 1.340851e-01 3.530604e-02
[11] 2.503167e-01 -5.316184e-04
EM algorithm done ...
Error en (posteriorfin2[profile == k, ])[, -1] :
número incorreto de dimensiones #Incorrect dimen
When I used the Wilting data following the vignette:
> result <- CGHcall(norm.cghdata, seg.cghdata)
EM algorithm started ...
Calling iteration 1 :
[1] 2.000000e+00 -4.244272e+03 -5.832847e-01 -2.831586e-01 5.078766e-03
[6] 3.289769e-01 1.157954e+00 -4.264512e-04 1.257185e-01 6.996470e-02
[11] 4.429449e-02 1.000000e-04
Calling iteration 2 :
[1] 2.000000e+00 -4.243597e+03 -5.762129e-01 -2.760868e-01 7.852040e-03
[6] 3.283777e-01 1.156755e+00 -2.940006e-04 1.215480e-01 6.854895e-02
[11] 3.598413e-02 1.000000e-04
EM algorithm done ...
FINISHED!
Total time: 1 minutes
> head(norm.cghdata)
BAC.clone Chromosome bp.position AdCA10 SCC27
1 RP11-465B22 1 1082138 -0.1804618 0.5999086
3 RP4-785P20 1 3318085 -0.1137811 0.7727828
4 RP1-37J18 1 4552927 0.4363701 0.6400294
6 RP4-706A17 1 6371642 0.5338766 0.1358740
7 RP3-438L4 1 7134999 0.4395028 0.6378606
8 RP11-338N10 1 7754212 0.2839457 0.5351469
> head(seg.cghdata)
BAC.clone Chromosome bp.position AdCA10 SCC27
1 RP11-465B22 1 1082138 0.3214 0.5804
3 RP4-785P20 1 3318085 0.3214 0.5804
4 RP1-37J18 1 4552927 0.3214 0.5804
6 RP4-706A17 1 6371642 0.3214 0.5804
7 RP3-438L4 1 7134999 0.3214 0.5804
8 RP11-338N10 1 7754212 0.3214 0.5804
> sessionInfo()
R version 2.6.0 (2007-10-03)
x86_64-unknown-linux-gnu
locale:
LC_CTYPE=es_ES at euro;LC_NUMERIC=C;LC_TIME=es_ES at euro;LC_COLLATE=es_ES at euro;LC_MONETARY=es_ES at euro;LC_MESSAGES=es_ES at euro;LC_PAPER=es_ES at euro;LC_NAME=C;LC_ADDRESS=C;LC_TELEPHONE=C;LC_MEASUREMENT=es_ES at euro;LC_IDENTIFICATION=C
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] CGHcall_1.0.0 DNAcopy_1.12.0 impute_1.10.0
loaded via a namespace (and not attached):
[1] rcompgen_0.1-15
--
********************************************
Daniel Rico Rodriguez, PhD.
Structural Computational Biology Group
Spanish National Cancer Research Center, CNIO
Melchor Fernandez Almagro, 3.
28029 Madrid, Spain.
Phone: +34 91 224 69 00 #2256
drico at cnio.es
http://www.cnio.es
********************************************
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