Real-time definition of non-randomness in the distribution of genomic events.
Features such as mutations or structural characteristics can be non-randomly or non-uniformly distributed within a genome. So far, computer simulations were required for statistical inferences on the distribution of sequence motifs. Here, we show that these analyses are possible using an analytical, mathematical approach. For the assessment of non-randomness, our calculations only require information including genome size, number of (sampled) sequence motifs and distance parameters. We have developed computer programs evaluating our analytical formulas for the real-time determination of expected values and p-values. This approach permits a flexible cluster definition that can be applied to most effectively identify non-random or non-uniform sequence motif distribution. As an example, we show the effectivity and reliability of our mathematical approach in clinical retroviral vector integration site distribution.
Abel
Ulrich
U
Department of Translational Oncology, National Center for Tumor Diseases, German Cancer Research Center, Heidelberg, Germany; Department of Medical Biostatistics, Tumor Center Heidelberg-Mannheim, Heidelberg, Germany.
Deichmann
Annette
A
Bartholomae
Cynthia
C
Schwarzwaelder
Kerstin
K
Glimm
Hanno
H
Howe
Steven
S
Thrasher
Adrian
A
Garrigue
Alexandrine
A
Hacein-Bey-Abina
Salima
S
Cavazzana-Calvo
Marina
M
Fischer
Alain
A
Jaeger
Dirk
D
von Kalle
Christof
C
Schmidt
Manfred
M
D016000:Cluster Analysis; D003198:Computer Simulation; D015894:Genome, Human; D006801:Humans; D012190:Retroviridae / Q000235:genetics*; D016662:Virus Integration / Q000235:genetics*