PT  - JOURNAL ARTICLE
AU  - Dhawan, Andrew
AU  - Barberis, Alessandro
AU  - Cheng, Wei-Chen
AU  - Domingo, Enric
AU  - West, Catharine
AU  - Maughan, Tim
AU  - Scott, Jacob G.
AU  - Harris, Adrian L.
AU  - Buffa, Francesca M.
TI  - <em>sigQC</em>: A procedural approach for standardising the evaluation of gene signatures
AID  - 10.1101/203729
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 203729
4099  - http://biorxiv.org/content/early/2017/10/16/203729.short
4100  - http://biorxiv.org/content/early/2017/10/16/203729.full
AB  - With the increase in next generation sequencing generating large amounts of genomic data, gene expression signatures are becoming critically important tools, poised to make a large impact on the diagnosis, management and prognosis for a number of diseases. Increasingly, it is becoming necessary to determine whether a gene expression signature may apply to a dataset, but no standard quality control methodology exists. In this work, we introduce the first protocol, implemented in an R package sigQC, enabling a streamlined methodological and standardised approach for the quality control validation of gene signatures on independent data sets. The emphasis in this work is in showing the critical quality control steps involved in the generation of a clinically and biologically useful, transportable gene signature, including ensuring sufficient expression, variability, and autocorrelation of a signature. We demonstrate the application of the protocol in this work, showing how the outputs created from sigQC may be used for the evaluation of gene signatures on large-scale gene expression data in cancer. Flowchart of steps involved in the proposed sigQC protocol and sample output plots produced by the sigQC R package.