Clone wiki

GFOLD / Home

What is GFOLD?

GFOLD stands for Generalized FOLD change for ranking differentially expressed genes from RNA-seq data. GFOLD is especially useful when no replicate is available. GFOLD generalizes the fold change by considering the posterior distribution of log fold change, such that each gene is assigned a reliable fold change. It overcomes the shortcoming of p-value that measures the significance of whether a gene is differentially expressed under different conditions instead of measuring relative expression changes, which are more interesting in many studies. It also overcomes the shortcoming of fold change that suffers from the fact that the fold change of genes with low read count are not so reliable as that of genes with high read count, even these two genes show the same fold change.

Manual

Examples are available. Full manual could be found in the package source.

Questions?

Please visit and edit Issues. You can also send me emails jianxing.tongji在gmail.com

FAQ

  1. Why cannot I get correct mapping results? Two possible reasons: 1) The chromosome names for the annotation are different from the reads file; 2) You are using a GPF annotation but forget to add an extra parameter '-annf GPF'.
  2. How does GFOLD calculate RPKM? If a gene contains multiple transcripts, all the exons of all the transcripts belonging to this gene will be collapsed and merged. Reads that are mappable to such merged regions are considered as 'mappable'. The calculation of RPKM is based on the merged region, i.e. counting reads and calculating gene length. Then the calculation of RPKM just follows the standard definition. GFOLD calculates RPKM based on all mappable reads instead of consider flagstat in sam/bam. The counting and therefore the RPKM is not perfect. For example, if a read is mapped to a location where two genes overlap, the read will be counted twice. If a gene has exons at multiple chromosomes, only the first encountered chromosome when the GTF file is scanned will be used and be effective. Finally, GFOLD cannot calculate transcript expression level, which is tricky and can be estimated by other tools like cufflinks.
  3. I cannot download from bitbucket You can download the latest files from here.
  4. Leave your questions at Issues (besides the Wiki tab) and I will reply ASAP

Citation

Feng J, Meyer CA, Wang Q, Liu JS, Liu XS, Zhang Y. GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. Bioinformatics 2012

Updated