Hello,

I am using DEXseq for exon differential analysis. The analysis seems to work
well on genes with several exons, but I have a problem with genes with only
one exon.
Let me present you my dataset:

pData(ecs)
        sizeFactor condition replicate       type
Raman_1  0.9638822    nonvir         1 paired-end
HM1_1    1.4000715       vir         1 paired-end
Raman_2  1.0314049    nonvir         2 paired-end
Raman_3  1.0734133    nonvir         3 paired-end
HM1_2    0.7801269       vir         2 paired-end
HM1_3    0.9488409       vir         3 paired-end


table( table (geneIDs(ecs)))
   1    2    3    4    5    6    7    8
3149  893  874  206  100   42   18    4

As you can see, I have 3149 genes (out of 5286) which have only 1 exon.
There are 9291 exons.

res1 <- DEUresultTable(ecs)

> summary(res1)
                     geneID         exonID     dispersion_CR_est
 EHI_051420             :   8   E001   :5286   Min.   :0.000e+00
 EHI_070690             :   8   E002   :2137   1st Qu.:7.176e-03
 EHI_169670             :   8   E003   :1244   Median :1.693e-02
 EHI_175010+EHI_175000.1:   8   E004   : 370   Mean   :5.546e-02
 EHI_005010             :   7   E005   : 164   3rd Qu.:3.641e-02
 EHI_042710             :   7   E006   :  64   Max.   :1.300e+01
 (Other)                :9245   (Other):  26   NA's   :3.153e+03
   dispersion            pvalue             padjust
 Min.   :2.010e-02   Min.   :   0.0000   Min.   :   0.0000
 1st Qu.:2.202e-02   1st Qu.:   0.1150   1st Qu.:   0.4597
 Median :2.628e-02   Median :   0.4054   Median :   0.8086
 Mean   :3.229e+04   Mean   :   0.4269   Mean   :   0.6775
 3rd Qu.:4.214e-02   3rd Qu.:   0.7133   3rd Qu.:   0.9510
 Max.   :1.000e+08   Max.   :   1.0000   Max.   :   1.0000
                     NA's   :3153.0000   NA's   :3153.0000

There are 3153 NA's values. When checking out what were those NA's values, I
realized that they were all the genes with only one exon (and only 4 more
genes in the other cases). I doubt that it is by chance... And they don't
have weird read counts. Check for example EHI_000010, EHI_000410,
EHI_000420, EHI_000430, EHI_000440:

geneCountTable(ecs)[1:21,]
             Raman_1 HM1_1 Raman_2 Raman_3 HM1_2 HM1_3
EHI_000010       391  1364     464     449   457   560
EHI_000130     18806  8116   21890   24994  6509 14067
EHI_000240     24057 21825   15365   26903 21101 27841
EHI_000250      3374  2689    3938    4854  2310  3556
EHI_000290       458  3721     437     550  1716  1054
EHI_000410       896  1041    1086     978   905   745
EHI_000420       140   220     244     117   140    78
EHI_000430       583  2043     304     634  1398  1197
EHI_000440      3103 15309    5358    3619  9152 10392
EHI_000450       358   559     991     516   281   564
EHI_000460.1     357   118     449     425    43   746
EHI_000470.1     408  2657     297     397   946   909
EHI_000480       842  1702     858     778   841   847
EHI_000490       187   648     221     239   370   249
EHI_000500       329   506     454     402   244   555
EHI_000520       482  1615     883     440   925   751
EHI_000530      1794  1588    1751    1966  1099  1860
EHI_000540      2857  2504    3706    4152  1479  2547
EHI_000550      1967  3999    1241    1904  2505  2448
EHI_000560       152   434     239     165   273   175
EHI_000570      1209  2142    2183    1213  1905  2662


res1[1:20,]
                       geneID exonID dispersion_CR_est dispersion     pvalue
EHI_000010:001     EHI_000010   E001                NA 0.02377712         NA
EHI_000130:001     EHI_000130   E001       0.074669451 0.07466945 0.48673539
EHI_000130:002     EHI_000130   E002       0.128972813 0.12897281 0.94279527
EHI_000130:003     EHI_000130   E003       0.019602219 0.02031871 0.84327914
EHI_000130:004     EHI_000130   E004       0.067337196 0.06733720 0.70429765
EHI_000240:001     EHI_000240   E001       0.043753997 0.04375400 0.74939865
EHI_000240:002     EHI_000240   E002       0.058562700 0.05856270 0.74939865
EHI_000250:001     EHI_000250   E001       0.031440630 0.03144063 0.70444841
EHI_000250:002     EHI_000250   E002       0.037457450 0.03745745 0.70444841
EHI_000290:001     EHI_000290   E001       0.021113888 0.02396819 0.05100089
EHI_000290:002     EHI_000290   E002       0.007626346 0.03471905 0.95676220
EHI_000290:003     EHI_000290   E003       0.036889359 0.03688936 0.03057067
EHI_000410:001     EHI_000410   E001                NA 0.02235347         NA
EHI_000420:001     EHI_000420   E001                NA 0.03395573         NA
EHI_000430:001     EHI_000430   E001                NA 0.02219522         NA
EHI_000440:001     EHI_000440   E001                NA 0.02037263         NA
EHI_000450:001     EHI_000450   E001       0.024495906 0.04492663 0.64717121
EHI_000450:002     EHI_000450   E002       0.020356260 0.02483641 0.64717121
EHI_000460.1:001 EHI_000460.1   E001                NA 0.02602179         NA
EHI_000470.1:001 EHI_000470.1   E001                NA 0.02254333         NA
                   padjust
EHI_000010:001          NA
EHI_000130:001   0.8639624
EHI_000130:002   0.9927663
EHI_000130:003   0.9756197
EHI_000130:004   0.9503086
EHI_000240:001   0.9611397
EHI_000240:002   0.9611397
EHI_000250:001   0.9503086
EHI_000250:002   0.9503086
EHI_000290:001   0.2890521
EHI_000290:002   0.9962043
EHI_000290:003   0.2087239
EHI_000410:001          NA
EHI_000420:001          NA
EHI_000430:001          NA
EHI_000440:001          NA
EHI_000450:001   0.9278993
EHI_000450:002   0.9278993
EHI_000460.1:001        NA
EHI_000470.1:001        NA

I checked the model in the documentation and I don't see why the test does
not give a result in this case. Has anyone get the same problem?

Thanks for your help,
Jane Merlevède

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