<#C05785S3TMX|> Hello, I am trying to run nf-core ...
# riboseq
m
#C05785S3TMX Hello, I am trying to run nf-core riboseq pipeline using published dataset. The run was successful however, I failed to generate anota2seq output. Here are arguments options I used for running this pipeline:
'nextflow run nf-core/riboseq -r 1.1.0 \
-profile singularity \
-name riboseq_10 \
-params-file nf-params.json \
-resume \
--extra_ribotricer_detectorfs_args '--phase_score_cutoff 0.2' \
--run_anota2seq true \
`--extra_anota2seq_run_args '--nPermutations 1000 --useRVM TRUE`' The output folder has:
alignment  fastq  genome  multiqc  orf_predictions  other  pipeline_info  preprocessing  quantification  riboseq_qc  ribotricer
My input sample sheet is: sample,fastq_1,fastq_2,strandedness,type,sample_description,pair,treatment
WT_1,/data/project/ding_lab/riboseq/SRR24898155.fastq.gz,,auto,riboseq,WT_1,1,control
WT_2,/data/project/ding_lab/riboseq/SRR24898156.fastq.gz,,auto,riboseq,WT_2,2,control
SNORD97_knockout_1,/data/project/ding_lab/riboseq/SRR24898151.fastq.gz,,auto,riboseq,SNORD97_knockout_1,3,treated
SNORD97_knockout_2,/data/project/ding_lab/riboseq/SRR24898152.fastq.gz,,auto,riboseq,SNORD97_knockout_2,4,treated
SNORD133_knockout_1,/data/project/ding_lab/riboseq/SRR24898149.fastq.gz,,auto,riboseq,SNORD133_knockout_1,5,treated
SNORD133_knockout_2,/data/project/ding_lab/riboseq/SRR24898150.fastq.gz,,auto,riboseq,SNORD133_knockout_2,6,treated
SNORD97_133_double_knockout_1,/data/project/ding_lab/riboseq/SRR24898153.fastq.gz,,auto,riboseq,SNORD97_133_double_knockout_1,7,treated
SNORD97_133_double_knockout_2,/data/project/ding_lab/riboseq/SRR24898154.fastq.gz,,auto,riboseq,SNORD97_133_double_knockout_2,8,treated
WT_1,/data/project/ding_lab/riboseq/SRR24898195.fastq.gz,,auto,rnaseq,WT_1,1,control
WT_2,/data/project/ding_lab/riboseq/SRR24898196.fastq.gz,,auto,rnaseq,WT_2,2,control
SNORD97_knockout_1,/data/project/ding_lab/riboseq/SRR24898191.fastq.gz,,auto,rnaseq,SNORD97_knockout_1,3,treated
SNORD97_knockout_2,/data/project/ding_lab/riboseq/SRR24898192.fastq.gz,,auto,rnaseq,SNORD97_knockout_2,4,treated
SNORD133_knockout_1,/data/project/ding_lab/riboseq/SRR24898189.fastq.gz,,auto,rnaseq,SNORD133_knockout_1,5,treated
SNORD133_knockout_2,/data/project/ding_lab/riboseq/SRR24898190.fastq.gz,,auto,rnaseq,SNORD133_knockout_2,6,treated
SNORD97_133_double_knockout_1,/data/project/ding_lab/riboseq/SRR24898193.fastq.gz,,auto,rnaseq,SNORD97_133_double_knockout_1,7,treated
SNORD97_133_double_knockout_2,/data/project/ding_lab/riboseq/SRR24898194.fastq.gz,,auto,rnaseq,SNORD97_133_double_knockout_2,8,treated
j
may we see the output of the pipeline or the .nextflow.log for that run?
m
nextflow log | grep anota2seq
2025-06-05 08:56:49     -               riboseq_7       -       235e008eda      7e1dea40-8b78-4368-b447-157ada473cbd    nextflow run nf-core/riboseq -r 1.1.0 -profile singularity -name riboseq_7 -params-file nf-params.json -resume --extra_ribotricer_detectorfs_args '--phase_score_cutoff 0.2' --extra_anota2seq_run_args true
2025-06-05 08:59:59     35.6s           riboseq_8       OK      235e008eda      7e1dea40-8b78-4368-b447-157ada473cbd    nextflow run nf-core/riboseq -r 1.1.0 -profile singularity -name riboseq_8 -params-file nf-params.json -resume --extra_ribotricer_detectorfs_args '--phase_score_cutoff 0.2' --run_anota2seq true
2025-06-05 09:06:20     36.4s           riboseq_9       OK      235e008eda      7e1dea40-8b78-4368-b447-157ada473cbd    nextflow run nf-core/riboseq -r 1.1.0 -profile singularity -name riboseq_9 -params-file nf-params.json -resume --extra_ribotricer_detectorfs_args '--phase_score_cutoff 0.2' --extra_anota2seq_run_args '--nPermutations 1000 --useRVM TRUE'
2025-06-05 09:11:04     38.3s           riboseq_10      OK      235e008eda      7e1dea40-8b78-4368-b447-157ada473cbd    nextflow run nf-core/riboseq -r 1.1.0 -profile singularity -name riboseq_10 -params-file nf-params.json -resume --extra_ribotricer_detectorfs_args '--phase_score_cutoff 0.2' --run_anota2seq true --extra_anota2seq_run_args '--nPermutations 1000 --useRVM TRUE'
j
In the directory where you ran this successful run there should be a file called
.nextflow.log
. This is the one that will be helpful to see
m
j
Agh sorry. Could have caught this without the log. Looks like you need to give a csv to
--contrasts
See the README:
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In the translational efficiency analysis provided by anota2seq, we use matched pairs of Ribo-seq and RNA-seq data to study the relationship between transcription and translation as they differ between two treatment groups. For example the test data for this workflow has a contrasts file like:

id,variable,reference,target,batch,pair
treated_vs_control,treatment,control,treated,,pair
m
Please see if this contrast csv file make sense: id,variable,reference,target,batch,pair
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SNORD97_vs_control,pair,1,3,,pair
SNORD97_vs_control,pair,2,4,,pair
SNORD133_vs_control,pair,1,5,,pair
SNORD133_vs_control,pair,2,6,,pair
SNORD97_133_double_vs_control,pair,1,7,,pair
SNORD97_133_double_vs_control,pair,2,8,,pair
I tried different ways for providing control and treatment groups for anota2seq but it is failed. Can you please suggest anything? Thank you
I also have two samples per group and based on this thread it may not work with my analysis as well !!! https://nfcore.slack.com/archives/C05785S3TMX/p1727374472061639. Can you please suggest any alternative?
j
m
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salmon]$ ls
SNORD133_knockout_1            WT_1                                                       salmon.merged.gene.scaled.R_sessionInfo.log         salmon.merged.gene_tpm.tsv
SNORD133_knockout_2            WT_2                                                       salmon.merged.gene.scaled.SummarizedExperiment.rds  salmon.merged.transcript.R_sessionInfo.log
SNORD97_133_double_knockout_1  salmon.merged.gene.R_sessionInfo.log                       salmon.merged.gene_counts.tsv                       salmon.merged.transcript.SummarizedExperiment.rds
SNORD97_133_double_knockout_2  salmon.merged.gene.SummarizedExperiment.rds                salmon.merged.gene_counts_length_scaled.tsv         salmon.merged.transcript_counts.tsv
SNORD97_knockout_1             salmon.merged.gene.length_scaled.R_sessionInfo.log         salmon.merged.gene_counts_scaled.tsv                salmon.merged.transcript_lengths.tsv
SNORD97_knockout_2             salmon.merged.gene.length_scaled.SummarizedExperiment.rds  salmon.merged.gene_lengths.tsv                      salmon.merged.transcript_tpm.tsv
I do not see separate RNAseq and riboseq count files.
DeltaTE needs both seq counts to do comparison
j
Your workflow didnt procces any RNA-Seq if you look at the log
m
Can you please point out anything why it could not process any RNA seq data?
I am rerunning the pipeline using discrete sample names for riboseq and RNAseq
j
Hi Mohit, sorry I had no time to pay proper attention to this yesterday. Looks like your contrasts file is not valid. With your current samplesheet you can use
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id,variable,reference,target,batch,pair
treated_vs_control,treatment,control,treated,,pair
But this will compare all knockouts versus the controls. You likely want to run a different test for each knockout. For this youd need to update the treatment column in the samplesheet to contain info on the specific knockout. Treatment might be
SNORD97_KO
etc. then contrasts file would be more complex. I asked AI to mock one up so dont necessarily trust what I give you.
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id,variable,reference,target,batch,pair
SNORD97_vs_control,treatment,control,SNORD97_KO,,pair
SNORD133_vs_control,treatment,control,SNORD133_KO,,pair
DOUBLE_KO_vs_control,treatment,control,DOUBLE_KO,,pair
SNORD97_vs_SNORD133,treatment,SNORD133_KO,SNORD97_KO,,pair
DOUBLE_vs_SNORD97,treatment,SNORD97_KO,DOUBLE_KO,,pair
DOUBLE_vs_SNORD133,treatment,SNORD133_KO,DOUBLE_KO,,pair
That being said, anota2seq isnt even appropriate for your case as you don't have the required replicates. As I said I dont believe DetlaTE has these restrictions. I think you will need to add the header row with column names to your sample sheet to ensure the rna-seq can be processed correctly. I can also see that there were errors with STAR. The correct outputs werent found in a number of cases.. This would be good to know more about.
m
Hello @Jack Tierney, I tried riboseq pipeline using two different published data but the pipeline failed with one or two sample gave error: no
periodic read length found
I tried reducing the
--extra_ribotricer_detectorfs_args to 0.2 or 0.1
but still failed. I am wondering if you can let me know any published dataset which has been used to test this pipeline.
?