Sharp increases in Alzheimer disease (AD) cases, deaths, and costs are stressing the health care system and caregivers. Several major AD data sources exist which allows researchers to conduct their research. For example, the BIOCARD study is a longitudinal, observational study initiated in 1995, and designed to identify biomarkers associated with progression from cognitively normal to mild cognitive impairment or dementia; the ADNI study is a multicenter observation study launched in 2004, to collect clinical, imaging, genetic and biospecimen biomarkers from cohorts of different clinical states at baseline; the NACC UDS data is a collection of data reflecting the total enrollment since 2005 across 34 AD Centers and includes subjects with a range of cognitive status. In this package, we establish AD data standards and data dictionaries in this package that define the formats and organization structures of the AD data across multiple data sources. R Functions are provided for data analysts to integrate data from multiple data sources and create their analysis datasets.

• Installation of Java. Please visit http://www.java.com for information on installing Java.
• All BIOCARD files have to be the same format. For example, .csv or .xls (the first row should be variable names/headers).

Use the following codes to install the ADTools package

library(devtools)
install_github("Thewhey-Brian/ADTools")

To calssify each variable more accurately, the data type need to be clarified before loading into R. ADTools uses keywords matching to achieve this goal. to check the default keywords, please see the "src_key_words" column in the result of

adt_get_dict("src_files")

There are two ways to match the files properly:

1. Change the files name corresponding to the default keywords.
2. Change the default keywords: Save the outputs from

adt_get_dict("src_files")

and change the keywords. Then pass it to the merging function:

dt_biocard = adt_get_biocard(path, src_tables = "dict_src_tables.xlsx")

• path: data direction
• reference_time: reference time for merging data for each patient

• An S3 object including the analysis dataset

# ref: the reference time for merging
# win: the window setting for each categories of variable
dt_biocard = adt_get_biocard(path, reference_time = ref, window_setting = win, src_tables = "dict_src_tables.xlsx")

Please use the help function to get more detailed information about the function setting

?adt_get_biocard

To check the meaning the each variable in the returned analysis dataset, please use function

analysis_data = dt_biocard$ana_dt
adt_tk_query(analysis_data, "variable name")

With the outputed S3 object, use the following functions to check the summary and plot statistics for intersted variables

summary(dt_biocard)
plot(dt_biocard, distn = "gender", group = age, baseline = TRUE)

Please use the help function to get more detailed information about the function setting.