Version 1.2.1

This release fixes the following bugs:

• Issue #14, where an exception was raised for launching to many event client listener on SGE using DRMAA.
• Issue #15, where an exception was raised while compiling execution time for the automatic report and there are missing time for failed bgzip compression.

Version 1.2.0

This new release of our genome-wide imputation pipeline includes the following changes:

• The impute2-merger tool now merges the marker-wise information file produced for each segment (*.impute2_info) into a single file (in the final_impute2 directory of each chromosome).
• The impute2-extractor tool can now extract markers according to their information value (along with other metrics, such as genomic locations, minor allele frequency and call rate).
• Minor bug fixed in the impute2-extractor tool, where minor allele frequency was computed using all probabilities instead of filtering out values lower than the specified threshold.

In brief, this release now takes into account the information file provided by IMPUTE2. This information file includes the measure of the observed statistical information associated with the allele frequency estimate. More information about this metric is available here.

Version 1.1.0

This is the second release of our genome-wide imputation pipeline (version 1.1.0). Here is the list of the changes:

• The package has been renamed to genipe (for GENome-wide Imputation PipelinE).
• Linear mixed effects models (for repeated measures) has been added to the imputed-stats tool (click here for more information).
• More tests have been added to the test suite (mostly for the linear mixed effects model).
• Documentation has been improved and updated for this release. The documentation is available here.

Complete documentation is available at http://pgxcentre.github.io/genipe

Installation: http://pgxcentre.github.io/genipe/installation.html

Tutorials: http://pgxcentre.github.io/genipe/tutorials.html

Version 1.0.0

This is the initial release of gwip (Genome-Wide Imputation Pipeline). Interesting features include:

• Complete and automatic genome-wide imputation pipeline from binary Plink files. Steps include:
  • strand verification
  • phasing
  • imputation
  • quality metrics
• All analysis are performed by chromosome and can be launch on an computer cluster using the DRMAA API (if required).
• Automatically generates a LaTeX report that can be compiled in PDF format.
• Commonly used statistical analysis
  • linear regression
  • logistic regression
  • SKAT analysis
  • survival analysis (Cox’s proportional hazard model)
• Indexing of file for easy imputed marker extraction

Complete documentation is available at http://pgxcentre.github.io/gwip

Installation: http://pgxcentre.github.io/gwip/installation.html

Tutorials: http://pgxcentre.github.io/gwip/tutorial.html