[BioC] Deciding on a cut off after QC

Ankit Pal pal_ankit2000 at yahoo.com
Mon May 16 13:49:38 CEST 2005


Dear Dr Smyth,
I'm sorry for not having specified which result file.
It is the final result summary we get after we give
the command
Resultfile <- topTable(fit,n=200, adjust="fdr")
A sample result file has been attached.
The code I used for my analysis is 

> targets <- readTargets("target.txt")

#The QC filter
> myfun <- function(x,threshold=55){
+ okred <- abs(x[,"% > B635+2SD"]) > threshold
+ okgreen <- abs(x[,"% > B532+2SD"]) > threshold
+ okflag <- abs(x[,"Flags"]) > 0
+ okRGN <- abs(x[,"Rgn R²"]) > 0.6
+ as.numeric(okgreen || okred || okflag || okRGN)
+ }
#end of QC filter 

> RG_7 <- read.maimages(targets$FileName,
source="genepix",wt.fun=myfun)
> RG_7$genes <- readGAL()
> RG_7$printer <- getLayout(RG_7$genes)
> MA_7 <- normalizeWithinArrays(RG_7,method="loess")
> MA_7 <- normalizeBetweenArrays(MA_7)
> fit_7 <- lmFit(MA_7, design=c(1,-1,1,-1))
> fit_7 <- eBayes(fit_7)
> options(digits=3)
> Resultfile_7 <- topTable(fit_7, n=39000,
adjust="fdr")
> Resdat_7 <-data.frame(Resultfile_7)
> write.table(Resdat_,file='Result.csv',quote = FALSE,
sep = "\t")

I understand that the spots that do not qualify the QC
filter are given a weight of "0" by limma and are not
considered for normalization and will not affect the
analysis.
The result file I get contains all the spots (38000)
in my case.
Didn't the spots that were bad get removed from the
final result?
If not what is the cut off value (B, p etc) that I
need to use to get a set of reliable spots(I cant use
all the 38000) from my result file for my analysis.
Is there a fixed formula to derive the same as the
values vary with the analysis.
Waiting for your reply,
Thank you,
-Ankit






--- Gordon K Smyth <smyth at wehi.EDU.AU> wrote:
> > Date: Sun, 15 May 2005 21:34:18 -0700 (PDT)
> > From: Ankit Pal <pal_ankit2000 at yahoo.com>
> > Subject: [BioC] Deciding on a cut off after QC
> > To: bioconductor at stat.math.ethz.ch
> >
> > Dear All,
> > I'm using LIMMA to analyse a set of GPR files.
> > I used the weight fuction to apply QC parameter
> > threshold values recommended by Genepix.
> > The code for the same is
> >
> >>myfun <- function(x,threshold=55){
> > + okred <- abs(x[,"% > B635+2SD"]) < threshold
> > + okgreen <- abs(x[,"% > B532+2SD"]) < threshold
> > + as.numeric(okgreen & okred)
> > }
> >
> >  On completion of the analysis, all the spots
> showed
> > up in the results file inspite of being flagged
> off. I
> > understand that on being flagged off by limma (wt
> =
> > 0), the spots are not considered for further
> analysis.
> > Is there any way they can be excluded from the
> final
> > result file.
> 
> What result file?
> 
> > Also, if I get an output of all the spots (38000
> in my
> > case) how do I decide on a cut off. Do I use the
> rank
> > or something else?
> 
> What output?
> 
> Gordon
> 
> > Waiting eagerly for a reply,
> > thank you,
> > -Ankit
> 
> 
> 


		

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-------------- next part --------------
      Block Row Column        ID                                               Name     M     A     t P.Value     B
4004      5  29     12 NC_001552                      9627219_516_rc | Sendai virus -2.33  2.57 -5.07   0.679 -2.72
4013      5  29     21         -                                     MJ-2000-88_501 -2.72  4.05 -4.95   0.679 -2.76
34570    43  22     25 NM_019694                                   scl0056384.1_230  2.24  5.51  4.87   0.679 -2.78
3502      5  10     23         -                                   scl13898.1.1_259 -2.60  4.37 -4.86   0.679 -2.78
32222    40  25     23 NM_153458                                    scl0001924.1_45  2.09  5.64  4.82   0.679 -2.79
31332    39  22     23 NM_025574                                    scl0066459.2_45  2.04  4.39  4.81   0.679 -2.80
7238      9  29     10 NC_001552                      9627219_435_rc | Sendai virus -2.17  2.72 -4.71   0.679 -2.83
27862    35  14      5         -                                     scl21854.2_284  2.05  3.97  4.70   0.679 -2.83
32256    40  27      3 NM_146139                                    scl0001929.1_72  2.00  5.97  4.66   0.679 -2.84
26620    33  28      3 NM_029357                                   scl0002178.1_304  2.45  6.12  4.60   0.679 -2.86
3275      5   2     12 XM_135092                                   scl36514.13.4_62 -3.29  3.07 -4.55   0.679 -2.88
34632    43  25      6         -                                              EMPTY  2.20  7.70  4.55   0.679 -2.88
3490      5  10     11         -                                    scl30794.6.1_93 -2.68  5.65 -4.54   0.679 -2.88
167       1   7      5         -                                     scl37855.3.1_1 -2.11  3.18 -4.52   0.679 -2.89
31373    39  24     10 NM_007692                                   scl0012651.2_322  2.25  6.42  4.52   0.679 -2.89
31919    40  14     17 XM_130346                                   scl19143.19.1_31  2.29  4.18  4.51   0.679 -2.89
31455    39  27     11 NM_139236                                    scl0002764.1_60  2.00  5.00  4.51   0.679 -2.89
21694    27  25     12 NM_010325                                     scl000715.1_17  2.26  3.15  4.50   0.679 -2.89
4003      5  29     11 NC_001503         9626965_214_rc | Mouse mammary tumor virus -2.71  2.81 -4.48   0.679 -2.90
22370    28  20     14 NM_008645                                    scl017836.18_18  2.70  6.33  4.43   0.679 -2.92
244       1  10      1         -                                    scl45289.2.1_35 -2.32  3.48 -4.42   0.679 -2.92
33082    41  27     20  BC042842                                  scl0003611.1_1554  2.04  5.38  4.41   0.679 -2.93
3278      5   2     15 XM_135940                                   scl54814.1.2_130 -2.62  3.57 -4.40   0.679 -2.93
32204    40  25      5 NM_008183                                     scl0014863.1_0  2.02  5.65  4.37   0.679 -2.94
7216      9  28     15 NM_008697                                    scl0002340.1_98 -2.42  3.53 -4.36   0.679 -2.94
29998    38   3     11 NM_011361                                     scl39091.7.1_0  2.40  3.78  4.35   0.679 -2.95
31475    39  28      4    M33467                                    scl0003417.1_10  1.83  4.12  4.30   0.679 -2.97
274       1  11      4 NM_178646                                     scl47812.1_441 -2.12  3.56 -4.28   0.679 -2.97
29838    37  27     12 NM_009372                                    scl0001623.1_60  2.52  5.75  4.28   0.679 -2.97
30621    38  26     13 NM_029620                                    scl0003537.1_10  2.17  5.43  4.27   0.679 -2.98
3926      5  26     15 NM_018865                                  scl0002564.1_1395 -2.16  3.13 -4.25   0.679 -2.98
3299      5   3      9 NM_173735                                     scl42940.8_203 -2.42  2.78 -4.24   0.679 -2.99
10018    13  12     13 NM_153786                                    scl38936.3.1_27 -2.73  2.57 -4.22   0.679 -3.00
37140    46  28      6 NM_009759                                    scl0002909.1_40  1.89  5.01  4.22   0.679 -3.00
3516      5  11     10 NM_173423                                   scl51436.1.1_135 -2.04  3.03 -4.19   0.679 -3.01
3461      5   9      9         -                                     scl24020.1.1_3 -2.67  3.99 -4.19   0.679 -3.01
30367    38  17      2 NM_027853                                    scl071664.1_311  2.06  3.69  4.18   0.679 -3.01
7265      9  30     10         -                                       MJ-250-11_13 -2.57  2.83 -4.16   0.679 -3.02
791       1  30      8         -                                     MJ-1000-72_435 -2.39  3.26 -4.15   0.679 -3.02
28154    35  24     27 NM_010325                                   scl0014719.1_330  1.80  5.64  4.14   0.679 -3.02
31503    39  29      5  AF304551      IGHV1S131|AF304551|Ig_heavy_variable_1S131_48  2.18  6.61  4.14   0.679 -3.02
25577    32  19     12 NM_010561                                    scl016201.19_34  2.64  6.13  4.14   0.679 -3.02
33092    41  28      3 NM_028990                                   scl0001077.1_623  2.32  6.10  4.13   0.679 -3.03
26519    33  24     10 NM_018823                                   scl0054446.1_138  2.42  6.60  4.12   0.679 -3.03
254       1  10     11 NM_146446                                    scl28511.1.1_86 -2.08  3.04 -4.12   0.679 -3.03
3973      5  28      8 NM_023655                                   scl0003501.1_700 -1.97  2.70 -4.11   0.679 -3.03
7240      9  29     12 NC_001846               9629812_535 | Murine hepatitis virus -1.75  2.58 -4.11   0.679 -3.03
169       1   7      7 NM_023608                                    scl54748.8.1_13 -2.08  3.79 -4.10   0.679 -3.04
36918    46  19     27 NM_011949                                     scl026413.2_16  2.18  8.92  4.09   0.679 -3.04
31417    39  25     27 NM_184053                                    scl0001200.1_31  1.78  4.72  4.08   0.679 -3.05
26621    33  28      4 NM_183336                                    scl0002922.1_48  2.11  3.59  4.08   0.679 -3.05
3835      5  23      5 NM_013560                                   scl0015507.1_320 -2.16  2.86 -4.08   0.679 -3.05
3497      5  10     18         -                                     scl43880.2_317 -1.97  3.93 -4.06   0.679 -3.05
37929    47  27     13  BC019769                                    scl0002315.1_12  1.89  4.69  4.06   0.679 -3.06
28828    36  19     27 XM_358370                                   scl017364.14_266  2.25  5.99  4.05   0.679 -3.06
38757    48  28      5 NM_177089                                    scl000578.1_190  2.03  4.57  4.05   0.679 -3.06
23424    29  29     16         -                                   MJ-3000-114_1506  2.56  5.87  4.04   0.679 -3.06
29003    36  26     13  BC066093                                   scl0002019.1_208  2.77  8.09  4.04   0.679 -3.06
13281    17  13     13 NM_025872                                    scl1412.1.1_281 -1.77  3.17 -4.01   0.679 -3.08
25725    32  24     25 NM_019927                                   scl0023806.2_110  1.99  3.80  3.99   0.679 -3.08
35186    44  15     21 NM_175347                                    scl0106393.1_61  1.76  3.80  3.99   0.679 -3.08
32853    41  19      7 XM_488538                                    scl0319934.1_56  3.07  6.50  3.97   0.679 -3.09
171       1   7      9         -                                    scl41474.1.1_55 -3.29  2.83 -3.97   0.679 -3.09
38779    48  28     27  AE000663 TRBV5|AE000663|T_cell_receptor_beta_variable_5_143  2.13  4.85  3.97   0.679 -3.09
37127    46  27     20  AK031926                                    scl0003274.1_34  2.08  6.41  3.96   0.679 -3.09
3761      5  20     12 NM_008852                                     scl018742.1_85 -1.79  2.58 -3.96   0.679 -3.09
308       1  12     11 XM_488860                                   scl14835.1.1_101 -2.82  2.90 -3.95   0.679 -3.10
97        1   4     16 NM_013633                                    scl50775.4.1_25 -2.34  3.36 -3.94   0.679 -3.10
33223    42   2     27 NM_019420                                   scl50036.1.4_192  3.04  8.01  3.94   0.679 -3.10
34200    43   9      6         -                                    scl25225.3.1_30  1.79  5.43  3.93   0.679 -3.11
32104    40  21     13         -                                     scl0077969.1_1  2.09  5.59  3.93   0.679 -3.11
35566    44  29     23         -                                     MJ-1000-76_241  1.95  7.52  3.90   0.679 -3.12
59        1   3      5 NM_025696                                    scl52928.27_344 -1.93  3.95 -3.89   0.679 -3.12
31204    39  18      3 NM_207550                                   scl0404310.1_281  3.68  9.19  3.89   0.679 -3.12
30594    38  25     13  AF124385                                     scl0001994.1_3  2.97  6.47  3.89   0.679 -3.12
27142    34  17     13         -                                    scl0320791.1_13  2.38  6.91  3.89   0.679 -3.12
7021      9  21      9 NM_172824                                  scl00239839.2_254 -2.23  4.00 -3.89   0.679 -3.12
25810    32  28      2 NM_023061                                     scl0003554.1_4  1.85  6.25  3.88   0.679 -3.13
25635    32  21     16 NM_207298                                   scl0099151.1_201  2.40  6.52  3.87   0.679 -3.13
31258    39  20      3 NM_009686                                     scl011787.1_19  1.79  4.94  3.87   0.679 -3.13
6700      9   9     12 NM_027614                                    scl43167.2.1_10 -2.01  3.32 -3.87   0.679 -3.13
15674    20  12      6 NM_173421                                     scl47999.3_178  1.84  5.89  3.86   0.679 -3.13
231       1   9     15         -                                   scl53117.1.4_247 -2.24  3.82 -3.86   0.679 -3.14
3282      5   2     19 NM_018871                                      scl25917.6_37 -2.95  3.95 -3.85   0.679 -3.14
217       1   9      1 NM_029681                                    scl25936.3.1_82 -1.72  3.71 -3.85   0.679 -3.14
30669    38  28      7  BC044883                                    scl0004073.1_36  2.61  7.36  3.84   0.679 -3.14
32274    40  27     21 NM_029945                                    scl0001884.1_59  1.72  4.92  3.84   0.679 -3.14
37809    47  23      1 XM_129809                                    scl0070155.1_99  2.29  8.15  3.83   0.679 -3.15
35928    45  13      8 NM_170758                                     scl40740.8_132 -2.30  3.37 -3.83   0.679 -3.15
32641    41  11     11 XM_484710                                   scl52179.17.1_47  2.15  6.46  3.83   0.679 -3.15
21676    27  24     21 NM_175657                                    scl00319161.1_8  2.12  5.11  3.82   0.679 -3.15
29680    37  21     16         -                                   scl0066491.1_300  1.66  5.04  3.81   0.679 -3.15
8796     11  27      4 NM_133798                                   scl0002392.1_125  3.35  5.83  3.80   0.679 -3.16
87        1   4      6 XM_355937                                    scl32097.7.1_17 -2.36  4.67 -3.79   0.679 -3.16
28118    35  23     18 NM_009567                                   scl0022755.1_133  1.73  4.77  3.78   0.679 -3.17
4107      6   3      8 NM_013465                                     scl49315.8.1_6 -2.93  4.70 -3.78   0.679 -3.17
37052    46  24     26 NM_026293                                   scl0067652.2_149  1.86  4.99  3.77   0.679 -3.17
33140    41  29     24         -                                   MJ-3000-103_2290  1.66  5.11  3.77   0.679 -3.17
32208    40  25      9         -                                              EMPTY  1.85  6.74  3.77   0.679 -3.17
14776    19   8     25         -                                     scl3899.5.1_15  2.48  6.50  3.77   0.679 -3.17
33200    42   2      4 NM_011118                                    scl0018812.1_77 -2.16  3.47 -3.76   0.679 -3.18
36336    45  28     11  BC054076                                    scl0003827.1_21  1.67  5.36  3.75   0.679 -3.18
30701    38  29     12 NC_002512                20198505_5605 | Rat cytomegalovirus  1.65  4.92  3.73   0.679 -3.19
38722    48  26     24 NM_025578                                    scl0001137.1_14  2.12  7.26  3.73   0.679 -3.19
30244    38  12     14 NM_011079                                     scl25995.10_72  1.75  5.06  3.71   0.679 -3.20
746       1  28     17 NM_134046                                      scl000016.1_3 -1.73  3.41 -3.71   0.679 -3.20


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