Hi all,

I've question regard dmpFinder method in Minfi package 1.10.2.

My Dataset has composed by 49 Samples.
I've splitted my methylation profiling matrix (always SWAN normalized,
filtered on p-value and sex chromosomes)
with all Cg Probe ID, in some sub-matrices with Cg Probe ID that covering
some genomic regions of interest.
Then I call dmpFinder method with a sub-matrix as input.

I got strange results from dmpFinder like this (only the head of dmp result
table):

              intercept            f                         pval
                      qval
63803    -1.7708894377    33.0502014338    5.7429067504821e-07
0.0295814503
35558    -2.0594919426    30.5216185561    1.26280541394315e-06
0.0325232649
37196    1.6545682828    29.0969331518    1.99216453478782e-06
0.0342051617
17326    2.6031068482    24.9262239789    7.98412955973361e-06
0.1028147164
13446    2.0077186022    22.9217904185    1.60468187115676e-05
0.1233703844
21260    -1.6861162973    22.9201474848    1.60561441086618e-05
0.1233703844
54663    -2.2310293103    22.4803114045    1.87681049414807e-05
0.1233703844
9834    -0.9628830679    22.2169618742    2.06170232814137e-05
0.1233703844
2522    -1.7629900864    22.0160423365    2.2154998438435e-05
0.1233703844


As you have to see the Cg Probe ID is strange/non-usual (It seems
truncated), Why? What's happened?


A sub_matrix is like this (only its first rows) and it has less than one
hundred thousand rows:

                      Sample_1           Sample_2         Sample_3
...    Sample_49
cg04761824    -2.2724251241    -1.135988521    -1.4793999396    ...    ...
cg13965272    -2.151897009    -1.214990173    -2.0012750288    ...    ...
cg14138549    -1.2409738471    1.4247978635    0.0392966574    ...    ...
cg14585967    -2.2641519697    -1.5533007179    -3.0725520279    ...    ...
cg14631486    -2.0956352791    -1.0406844361    -2.2111675268    ...    ...
cg00557872    2.5607532507    0.7251602564    1.5072624496    ...    ...
cg02570981    -2.1684190566    -1.0676436576    -1.6305898233    ...
...
cg03836638    0.5482586716    -0.3210537101    0.8483187571    ...
...
cg04267704    -2.6055084465    -3.0680224081    0.2251577771    ...    ...



Thanks in advance,
Giovanni

Laboratory of Preclinical and Translational Research
IRCCS - CROB Oncology Referral Center of Basilicata
Rionero in Vulture - Italy


***** sessionInfo *****

> sessionInfo()
R version 3.1.0 (2014-04-10)
Platform: x86_64-unknown-linux-gnu (64-bit)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C
 [9] LC_ADDRESS=C               LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods
[8] base

other attached packages:
 [1] minfi_1.10.2         bumphunter_1.4.2     locfit_1.5-9.1
 [4] iterators_1.0.7      foreach_1.4.2        Biostrings_2.32.1
 [7] XVector_0.4.0        GenomicRanges_1.16.3 GenomeInfoDb_1.0.2
[10] IRanges_1.22.9       lattice_0.20-29      Biobase_2.24.0
[13] BiocGenerics_0.10.0

loaded via a namespace (and not attached):
 [1] annotate_1.42.1       AnnotationDbi_1.26.0  base64_1.1
 [4] beanplot_1.1          codetools_0.2-8       DBI_0.2-7
 [7] digest_0.6.4          doRNG_1.6             genefilter_1.46.1
[10] grid_3.1.0            illuminaio_0.6.0      limma_3.20.8
[13] MASS_7.3-33           matrixStats_0.10.0    mclust_4.3
[16] multtest_2.20.0       nlme_3.1-117          nor1mix_1.1-4
[19] pkgmaker_0.22         plyr_1.8.1            preprocessCore_1.26.1
[22] RColorBrewer_1.0-5    Rcpp_0.11.2           registry_0.2
[25] reshape_0.8.5         R.methodsS3_1.6.1     rngtools_1.2.4
[28] RSQLite_0.11.4        siggenes_1.38.0       splines_3.1.0
[31] stats4_3.1.0          stringr_0.6.2         survival_2.37-7
[34] tools_3.1.0           XML_3.98-1.1          xtable_1.7-3
[37] zlibbioc_1.10.0
>

***** End sessionInfo *****

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