RiboToolkit | Group

Differential translation studies

Use single case job IDs to perform group case differential analysis:

Input gene expression matrix and RPF expression matrix (raw read counts) to perform differential translation efficiency analysis.
At least one replicate for each group and the INPUT and Ribo-seq sample should be consistent in gene expression matrix and RPF expression matrix.

The fields marked by "*" are required!

Select the input type

Input type *

Expression matrix Re-analysis

Upload gene expression count (both RNA-seq and Ribo-seq) for studying translation efficiency and differential translation

Gene expression counts

Upload gene expression count matrix
Test data

job ID(s) *

Provide completed job ID(s) to re-analyze your data with different parameters

Tool to identify differential translation:

Riborex Xtail

Parameters for statistics

RNA-seq samples *

Input multiple RNA-seq sample names in the gene count matrix and separate by comma ",", such as "RNA.WT1,RNA.WT2,RNA.KO1,RNA.KO2"

Ribo-seq samples *

Input Ribo-seq samples in the gene count matrix with the same order to RNA-seq samples and separate by comma ",", such as "RPF.WT1,RPF.WT2,RPF.KO1,RPF.KO2"

Group labels *

Use 1 and 2 to indicate two groups and separate by comma ",", such as 1,1,2,2

Group names *

Separate two group names by "#"

F-value *

Fold change of translation efficiency

P-value *

Statistical significant p-value for differential translation

P-value type

FDR (Adjusted p-value) Raw p-value

P-value type for differential translation

P value for functional enrichments *

Statistical significant p-value for functional enrichments (GO, Pathways and GSEA)

Get an notification when the job is done (optional)