Question: CGHcall error
0
gravatar for Daniel Rico
11.5 years ago by
Daniel Rico110
Daniel Rico110 wrote:
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] : n?mero 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] : n?mero 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 ******************************************** **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, y ...{{dropped:3}}
ADD COMMENTlink modified 11.5 years ago by Henrik Bengtsson2.4k • written 11.5 years ago by Daniel Rico110
Answer: CGHcall error
0
gravatar for Henrik Bengtsson
11.5 years ago by
United States
Henrik Bengtsson2.4k wrote:
On Feb 5, 2008 3:44 AM, Daniel Rico <drico at="" cnio.es=""> wrote: > 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] : > n?mero incorreto de dimensiones # Incorrect dimension number Without looking at the code itself, that looks like a classical mistake. When writing posteriorfin2[profile == k, ] without an explicit 'drop=FALSE', the developer assumes that 'profile == k' will match two or more rows in the 'posteriorfin2' matrix/data.frame. I suspect that in your case 'profile == k' is only TRUE in one case, which makes 'posteriorfin2[profile == k, ]' return a vector and not a matrix/data.frame. This will cause the next subsetting '[,-1]' to fail, because there are no columns in a plain vector ("Incorrect dimension number"). If the code would have said posteriorfin2[profile == k,,drop=FALSE] the particular error would not show up. However, in the end of the day, the real question might be why you end up with only a single case for which 'profile == k' is TRUE. That's my $0.02 Henrik > > 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] : > n?mero 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 > > ******************************************** > > > **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, y ...{{dropped:3}} > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor >
ADD COMMENTlink written 11.5 years ago by Henrik Bengtsson2.4k
hits=-2.6 tests=BAYES_00 X-USF-Spam-Flag: NO Hi Henrik, Sjoerd Vosse, developer of CGHcall, is having a look at my data. Thanks to both! Daniel Henrik Bengtsson wrote: > On Feb 5, 2008 3:44 AM, Daniel Rico <drico at="" cnio.es=""> wrote: > >> 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] : >> n?mero incorreto de dimensiones # Incorrect dimension number >> > > Without looking at the code itself, that looks like a classical > mistake. When writing > > posteriorfin2[profile == k, ] > > without an explicit 'drop=FALSE', the developer assumes that 'profile > == k' will match > two or more rows in the 'posteriorfin2' matrix/data.frame. I suspect > that in your case > 'profile == k' is only TRUE in one case, which makes > 'posteriorfin2[profile == k, ]' > return a vector and not a matrix/data.frame. This will cause the next > subsetting '[,-1]' > to fail, because there are no columns in a plain vector ("Incorrect > dimension number"). > If the code would have said > > posteriorfin2[profile == k,,drop=FALSE] > > the particular error would not show up. > > However, in the end of the day, the real question might be why you end > up with only > a single case for which 'profile == k' is TRUE. > > That's my $0.02 > > Henrik > > > > -- ******************************************** 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 ******************************************** **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, y ...{{dropped:3}}
ADD REPLYlink written 11.5 years ago by Daniel Rico110
Dear Henrik, thanks for your suggestion to make the code more robust! We'll fix it. Dear Daniel, your data still has missing values (NA) in it, which causes the error. Please use the impute package or our preprocess function to impute these values, or just remove the targets with missing values (there are only 4 I think). The error messages should be more clear, we are working on that for a future release. Let me know if this solves your problems and feel free to contact me directly if you have any questions or suggestions. Sjoerd -----Oorspronkelijk bericht----- Van: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor- bounces at stat.math.ethz.ch] Namens Daniel Rico Verzonden: Tuesday, February 05, 2008 17:21 Aan: Henrik Bengtsson CC: bioconductor at stat.math.ethz.ch Onderwerp: Re: [BioC] CGHcall error hits=-2.6 tests=BAYES_00 X-USF-Spam-Flag: NO Hi Henrik, Sjoerd Vosse, developer of CGHcall, is having a look at my data. Thanks to both! Daniel Henrik Bengtsson wrote: > On Feb 5, 2008 3:44 AM, Daniel Rico <drico at="" cnio.es=""> wrote: > >> 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] : >> n?mero incorreto de dimensiones # Incorrect dimension number >> > > Without looking at the code itself, that looks like a classical > mistake. When writing > > posteriorfin2[profile == k, ] > > without an explicit 'drop=FALSE', the developer assumes that 'profile > == k' will match > two or more rows in the 'posteriorfin2' matrix/data.frame. I suspect > that in your case > 'profile == k' is only TRUE in one case, which makes > 'posteriorfin2[profile == k, ]' > return a vector and not a matrix/data.frame. This will cause the next > subsetting '[,-1]' > to fail, because there are no columns in a plain vector ("Incorrect > dimension number"). > If the code would have said > > posteriorfin2[profile == k,,drop=FALSE] > > the particular error would not show up. > > However, in the end of the day, the real question might be why you end > up with only > a single case for which 'profile == k' is TRUE. > > That's my $0.02 > > Henrik > > > > -- ******************************************** 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 ******************************************** **NOTA DE CONFIDENCIALIDAD** Este correo electr?nico, ...{{dropped:10}}
ADD REPLYlink written 11.5 years ago by Vosse, S.J.30
Please log in to add an answer.

Help
Access

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.
Powered by Biostar version 16.09
Traffic: 262 users visited in the last hour