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Investigators in the cognitive neurosciences have turned to Big Data to address persistent replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. While there is tremendous potential to advance science through open data sharing, these efforts unveil a host of new questions about how to integrate data arising from distinct sources and instruments. We focus on the most frequently assessed area of cognition - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated raw data from 53 studies from around the world which measured at least one of three distinct verbal learning tasks, totaling N = 10,505 healthy and brain-injured individuals. A mega analysis was conducted using empirical bayes harmonization to isolate and remove site effects, followed by linear models which adjusted for common covariates. After corrections, a continuous item response theory (IRT) model estimated each individual subject’s latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance by 37% while preserving covariate effects. The effects of age, sex, and education on scores were found to be highly consistent across memory tests. IRT methods for equating scores across AVLTs agreed with held-out data of dually-administered tests, and these tools are made available for free online. This work demonstrates that large-scale data sharing and harmonization initiatives can offer opportunities to address reproducibility and integration challenges across the behavioral sciences.
Chromosomal rearrangements of the human MLL (mixed lineage leukemia) gene are associated with high-risk infant, pediatric, adult and therapy-induced acute leukemias. We used long-distance inverse-polymerase chain reaction to characterize the chromosomal rearrangement of individual acute leukemia patients. We present data of the molecular characterization of 1590 MLL-rearranged biopsy samples obtained from acute leukemia patients. The precise localization of genomic breakpoints within the MLL gene and the involved translocation partner genes (TPGs) were determined and novel TPGs identified. All patients were classified according to their gender (852 females and 745 males), age at diagnosis (558 infant, 416 pediatric and 616 adult leukemia patients) and other clinical criteria. Combined data of our study and recently published data revealed a total of 121 different MLL rearrangements, of which 79 TPGs are now characterized at the molecular level. However, only seven rearrangements seem to be predominantly associated with illegitimate recombinations of the MLL gene (~ 90%): AFF1/AF4, MLLT3/AF9, MLLT1/ENL, MLLT10/AF10, ELL, partial tandem duplications (MLL PTDs) and MLLT4/AF6, respectively. The MLL breakpoint distributions for all clinical relevant subtypes (gender, disease type, age at diagnosis, reciprocal, complex and therapy-induced translocations) are presented. Finally, we present the extending network of reciprocal MLL fusions deriving from complex rearrangements.