Study

Local In Time Statistics for processual research

Study ID Alternative Stable ID Type
EGAS00001002520 Other

Study Description

Background: Functional genomics in a processual analysis cover the time-dependent changes in transcriptomics and epigenetics before diagnosis of a disease, reflecting the changes in both life style and disease processes. The aim of this paper is to explore the dynamic, time-dependent mechanisms of the metastatic processes, using blood transcriptomics and including time in a continuous manner. For achieving this goal we develop new statistical methods based on statistics that are local in time. Methods: The new statistical method, Local In Time Statistics (LITS), is based on calculating statistics in moving windows and randomization. The method has been tested for the analysis of a dataset that collectively provides information on the blood transcriptome up to eight years before breast cancer diagnosis. The dataset from the NOWAC Post-genome Cohort consists of 467 case-control pairs matched on birth year and time of blood sampling. The data for a pair is the difference in log2 gene expression between the case and control. The stratified analyses are based on important biological ... (Show More)

Study Datasets 1 dataset.

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Dataset ID Description Technology Samples
EGAD00010001400
Difference in gene expression values between case and control, log2 values. Blood transcriptome from women participating in the Norwegian Women and Cancer study (NOWAC) Post-genome Cohort taken up to eight years before brest cancer diagnosis. Illumina HumanWG-6 version 3 or Illumina HumanHT-12 expression bead chip, combined on identical nucleotide universal identifiers.
Illumina HumanWG-6 467

Who archives the data?

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