[R] issue with numeric

[Rui Barradas]

Hello,

It's hard to tell without data but:


1) The data is read in in code line 19. Check if it has 19 columns and 
if columns 18 and 19 are numeric.
If they are of class factor run

D[18:19] <- lapply(D[18:19], function(x) as.numeric(as.character(x)))


2) code line nr 20 is
exon_offset = ifelse(ncol(D) == 19, 0, 2)

So if the data has 19 columns, as expected, exon_offset = 0.

3) The error comes from computing the correlation between D[, 18 + 
exon_offset] and D[, 19 + exon_offset] in code line 27:


cat("  * Correlation between Beta approx. and Empirical p-values =", 
round(cor(D[, 18+exon_offset], D[, 19+exon_offset]), 4), "\n")

This includes cor(D[, 18+exon_offset], D[, 19+exon_offset])


So check what are the values of ncol(D) and of exon_offset. Their sum 
cannot be bigger than ncol(D).


If none of the above, say something.


Hope this helps,

Rui Barradas




Às 18:25 de 18/12/19, Ana Marija escreveu:
> Hello,
> 
> I was running this code, located at:
> https://github.com/swvanderlaan/QTLToolKit/blob/master/SCRIPTS/runFDR_cis.R
> 
> Rscript runFDR_cis.R Retina_new_perms_full.txt 0.05 permutations_all
> 
> and I got this error:
> 
> Processing QTLtools output.
>    * Input  = [ Retina_new_perms_full.txt ]
>    * FDR    =  0.05
>    * Output = [ permutations_all ]
> 
> Read Input data. Note: we expect a file with 19 columns i.e. it is
> best to use the results from a permutation test.
>    * Gene level correction detected
>    * Number of molecular phenotypes = 17375
>    * Number of NA lines = 15
> Error in cor(D[, 18 + exon_offset], D[, 19 + exon_offset]) :
>    'x' must be numeric
> Calls: cat -> cor
> Execution halted
> 
>> a=read.table("Retina_new_perms_full.txt", header=T)
>> head(a)
>                 V1   V2     V3     V4 V5   V6      V7
> 1 ENSG00000227232 chr1  29571  29570  -  983 -828479
> 2 ENSG00000237613 chr1  36082  36081  - 1006  -38709
> 3 ENSG00000239945 chr1  91106  91105  - 1169 -782443
> 4 ENSG00000238009 chr1 133724 133723  - 1340   69986
> 5 ENSG00000241860 chr1 173863 173862  - 1441 -831895
> 6 ENSG00000279457 chr1 200323 200322  - 1620 -980529
>                                     V8   V9     V10     V11   Effect_allele
> 1              rs200956863:793429:T:C chr1  858049  858049               T
> 2                rs13328700:74790:C:G chr1   74790   74790               G
> 3               rs11240780:808928:C:T chr1  873548  873548               C
> 4            rs201888535:63735:CCTA:C chr1   63735   63738               C
> 5 rs61703480:941137:AGCCCCCGCAGCAGT:A chr1 1005757 1005771 AGCCCCCGCAGCAGT
> 6              rs13374146:1116231:T:C chr1 1180851 1180851               C
>    Baseline_allele V12     V13     V14     V15         V16       V17      V18
> 1               C 404 348.489 1.04262 139.753 0.000741814  0.269459 0.196180
> 2               C 404 346.832 1.03086 138.165 0.002822220 -0.687290 0.530547
> 3               T 404 347.109 1.02189 152.726 0.000626379 -0.284821 0.203080
> 4            CCTA 404 338.804 1.04423 154.301 0.000797573 -0.398402 0.264974
> 5               A 404 341.822 1.04355 171.178 0.002893770  0.340855 0.638936
> 6               T 404 338.232 1.05240 180.879 0.001846080 -0.458547 0.528947
>         V19
> 1 0.198142
> 2 0.529105
> 3 0.199394
> 4 0.261441
> 5 0.633917
> 6 0.524186
> 
> 
> Please advise,
> Ana
> 
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