cmp.parse: Parse an SDF file and compute descriptors for all compounds
In girke-lab/ChemmineR-release: Cheminformatics Toolkit for R

Description Usage Arguments Details Value Author(s) References See Also Examples

'cmp.parse' will take a SDF file, parse all the compounds encoded, compute their atom-pair descriptors, and return the descriptors as a list. The list contains two names, 'descdb' and 'cids'. 'descdb' is a vector of descriptors, and 'cids' is a list of names of compounds found in the SDF file. The returned list is usually used to a database, against which similarity search can be performed using the 'search' function. These two functions will parse all compounds in the SDF file. To parse a single compound, use 'cmp.parse1' instead.

1	cmp.parse(filename)

filename

The file name of the SDF file

The 'filename' can be a local file or an URL. It is interactive, and will display the parsing progress. Since the parsing will also compute of atom-pair descriptors, it is time consuming. You will be reminded to save the parsing result for future use at the end of parsing.

'type' is either set to the default value 'normal' or 'file-backed'. When set to 'file-backed', the parsing work will be delegated to a separate package called 'ChemmineRpp', and the database will be stored in a file instead of in the primary memory. Therefore, 'file-backed' mode can handle larger compound libraries. In 'file-backed' mode, 'dbname' will be used to name the database file. A suffix '.cdb' will be appended to the given name.

The type of the database is transparent to other part of the package. For example, calling 'cmp.search' against a database in 'file-backed' mode will cause the package to load the descriptors from the database file progressively.

Return a list that can be used as the database against which similarity search can be performed. The 'search' and 'cmp.cluster' functions both expect a database returned by 'cmp.parse'.

`descdb`	A vector containing the descriptors for all the compounds.
`cids`	Compound ID information found in the SDF file. It is the first line of SDF of a compound.

Y. Eddie Cao, Li-Chang Cheng

Chen X and Reynolds CH (2002). "Performance of similarity measures in 2D fragment-based similarity searching: comparison of structural descriptors and similarity coefficients", in J Chem Inf Comput Sci.

cmp.parse1, cmp.search, cmp.cluster, cmp.similarity

## Load sample SD file
# data(sdfsample); sdfset <- sdfsample

## Generate atom pair descriptor database for searching
# apset <- sdf2ap(sdfset) 

## Loads same atom pair sample data set provided by library
data(apset) 
db <- apset
# (optinally) save the db for future use
save(db, file="db.rda", compress=TRUE)
# ...
# later, in a separate session, you can load it back:
load("db.rda")