Question: Problem in analysis of Ballgown output by R (why q value are same in result ? )
0
gravatar for amitunited0532
11 months ago by
amitunited053210 wrote:

Hello,

I have performed an RNAseq experiment, for which I used HISAT2 for the alingment, Stringtie for the assembly and the R package Ballgown for the Differential Expression (DE) analysis. After generation of differential expression table, I found q value is mostly same for all genes which is given below.

Command which I run:

results_genes = stattest(bacteria_filter, feature = "gene", covariate = "sample", getFC = TRUE, meas = "FPKM") 
results_genes = merge(results_genes,bacteria_gene_names,by.x=c("id"),by.y=c("gene_id"))

differential_genes = subset(results_genes, results_genes$pval<0.05)
write.csv(differential_genes, "differential_genes.csv", row.names = FALSE)

Output:

qval

0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586 0.999988586

Thank you

ADD COMMENTlink modified 11 months ago by ATpoint22k • written 11 months ago by amitunited053210
1

Please use the code rather than the blockquote buttom to indicate code :)

code

ADD REPLYlink written 11 months ago by ATpoint22k
1

you probably don't have any significant hits even at non-FDR-adjusted levels. FDR-adjustment does lead to chunking quite often, though it's rarely a concern: if you need to rank by reproducibility use the untransformed levels, if you need to test at a certain threshold, use the FDR-adjusted levels

ADD REPLYlink written 11 months ago by russhh4.7k
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