Novel analytical methods to interpret large sequencing data from small sample sizes.

ABSTRACT:

Background

Targeted therapies have greatly improved cancer patient prognosis. For instance, chronic myeloid leukemia is now well treated with imatinib, a tyrosine kinase inhibitor. Around 80% of the patients reach complete remission. However, despite its great efficiency, some patients are resistant to the drug. This heterogeneity in the response might be associated with pharmacokinetic parameters, varying between individuals because of genetic variants. To assess this issue, next-generation sequencing of large panels of genes can be performed from patient samples. However, the common problem in pharmacogenetic studies is the availability of samples, often limited. In the end, large sequencing data are obtained from small sample sizes; therefore, classical statistical analyses cann

SUBMITTER: Lichou F 

PROVIDER: S-EPMC6717342 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature