get_tf: Get transcription factor correlations from cRegulome.db
In cRegulome: Obtain and Visualize Regulome-Gene Expression Correlations in Cancer

Description Usage Arguments Value Examples

This function access the sqlite database file which is obtained by running get_db. Basically, the function provides ways to query the database to the correlation data of the transcription factors of interest. The function returns an error if the database file cRegulome.db is not in the working directory.

1	get_tf(conn, tf, study, min_abs_cor, max_num, targets_only = FALSE, targets)

`conn`	A connection such as this returned by `dbConnect`
`tf`	A required `character` vector of the transcription factor of interest. These are the HUGO official gene symbols of the genes contains the transcription factor.
`study`	A `character` vector of The Cancer Genome Atlas (TCGA) study identifiers. To view the available studies in TCGA project, https://tcga-data.nci.nih.gov/docs/publications/tcga. When left to default `NULL` all available studies will be included.
`min_abs_cor`	A `numeric`, an absolute correlation minimum between 0 and 1 for each `mir`.
`max_num`	An `integer`, maximum number of `features` to show for each `mir` in each `study`.
`targets_only`	A `logical` whether restrict the output to the recognized target features.
`targets`	A `character` vector of gene symbol names.

A tidy data.frame of four columns. tf is the official gene symbols of the genes contains the transcription factor, feature is the features/genes, cor is the corresponding expression correlations and study is TCGA study ID.

# locate the testset file and connect
fl <- system.file('extdata', 'cRegulome.db', package = 'cRegulome')
conn <- RSQLite::dbConnect(RSQLite::SQLite(), fl)

## Not run: 
# get transcription factors correlations in all studies
get_tf(conn,
        tf = 'LEF1')

## End(Not run)

# get correlations in a particular study
get_tf(conn,
       tf = 'LEF1',
       study = 'STES')

# enter a custom query with different arguments
get_tf(conn,
       tf = 'LEF1',
       study = 'STES',
       min_abs_cor = .3,
       max_num = 5)