DESEQ2 Error in .local(object, ...) : all genes have equal values

Question

[ovariohisterectomia]

Hi everyone, hope you may help me. Im stucked here...i have this error in Deseq2

Error in .local(object, ...) : all genes have equal values for all samples. will not be able to perform differential analysis

I will tell you the whole story...

First i generated my countDATA, with this

CONTEOMERGED = featureCounts(files=c("B766.bam", "B767.bam", "B768.bam", "B769.bam", "OV1.bam", "OV2.bam", "OV3.bam", "OV4.bam"), annot.ext="GCF_000524195.1_ASM52419v1_genomic.gff", isGTFAnnotationFile=TRUE, isPairedEnd=TRUE, GTF.attrType="Dbxref")

(the files was previously sorted)

Then i started my script for Differential analysis

########### RNAseq DE ################
library(DESeq2)
library("gplots")
library(RColorBrewer)
library(genefilter)

setwd("/media/isma/6CAE9DAF1D4BB3FE/com_oveja_bovino/matrices_de_conteo")


countData <- read.table("countData.txt", header = TRUE, dec = ".", sep = "\t", row.names = "GeneID")
colData <- read.table("colData.txt", header = TRUE, sep = "\t")
head(colData)

dds <- DESeqDataSetFromMatrix(countData = countData,
                              colData = colData,
                              design = ~treatment)


### Filter low counts ###
dds <- estimateSizeFactors(dds)
idx <- rowSums( counts(dds, normalized=TRUE) >= 2 ) >= 12 
dds <- dds[idx,]

Until here everything was ok, but then i performed this command and it says there is an Error

> dds <- DESeq(dds)
using pre-existing size factors
estimating dispersions
Error in .local(object, ...) : 
  all genes have equal values for all samples. will not be able to perform differential analysis

I dont know why it says that...i will write the first columns of my countdata here, maybe its helpful...

Thank you everyone for your kind help

GeneID  B766    B767    B768    B769    OV1 OV2 OV3 OV4
36347034    0   0   0   0   0   0   0   0
36347033    0   0   0   0   0   0   0   0
36347032    43  47  43  47  256 355 191 153
36347031    66  60  52  57  275 358 443 478
36347030    0   0   0   0   20  19  43  36
36347029    0   0   0   0   0   0   0   0
36347028    0   0   0   0   0   1   0   0
36347027    0   0   0   0   0   0   0   0
36347026    0   0   0   0   1   12  3   6
36347025    94  58  385 347 3405    1653    3339    2221
36347024    0   0   0   0   4   0   4   0
36347023    0   0   0   0   0   0   0   0
36347022    0   0   0   0   778 466 495 239
36347020    1744    2212    2958    2621    1153    969 1510    2506
36347021    1107    1021    1339    1376    1265    880 1638    2526
36347019    0   0   0   0   6   1   3   0
36347018    0   1   0   0   39  7   42  22
36347017    0   0   0   0   22  163 26  110
36347016    0   0   0   0   1   0   0   1
36347015    195 265 81  121 136 69  91  33
36347014    0   0   0   0   0   0   0   0
36347013    56  93  20  22  507 297 391 866
36347012    0   0   0   0   0   0   2   1
36347011    0   0   1   0   7   0   1   0
36347010    2   3   10  22  202 128 205 60
36347009    0   0   0   0   0   6   1   5
36347008    3   2   1   9   20  8   6   1
36347007    0   0   0   0   0   0   0   0
36347006    0   0   0   0   0   0   0   0
36347005    86  89  67  79  915 1052    739 753
36347004    77  80  103 67  0   0   0   0
36347003    0   0   0   0   0   0   0   1
36347002    0   0   0   0   7   39  13  7
36347001    0   0   0   0   0   0   0   0
36347000    0   0   0   0   65  207 43  221
36346999    0   1   7   6   121 87  88  108
36346998    4   4   9   3   409 339 358 329

Answer 1

[ovariohisterectomia]

i found the ERROR,

I changed this

idx <- rowSums( counts(dds, normalized=TRUE) >= 2 ) >= 12

for this...

idx <- rowSums( counts(dds, normalized=TRUE) >= 2 ) >= 8

I had 8, not 12 rows...

SOLVED