selex.infogain {SELEX} | R Documentation |
A function used to compute and store the information gain for various K-mer lengths on sample
using markovModel
to predict prior probabilities.
selex.infogain(sample, k=NULL, markovModel, seqfilter=NULL, checkBarcode=TRUE)
sample |
A sample handle to the dataset on which to perform the analysis. |
k |
The range of K-mer lengths for which the information gain should be calculated. If |
markovModel |
A Markov model handle. |
seqfilter |
A sequence filter object to include/exclude sequences that are read in from the FASTQ file. |
checkBarcode |
Checks to see if the sample barcodes used to construct the Markov model match those in the current sample, and prevents computation if they do not match. |
selex.infogainSummary
is required to view the computed information gain values. When a new seqfilter
object is provided, the information gain analysis is redone. See selex.seqfilter
for more details.
See ‘References’ for more on the computation of information gain values.
selex.infogain
returns the highest information gain value.
Slattery, M., Riley, T.R., Liu, P., Abe, N., Gomez-Alcala, P., Dror, I., Zhou, T., Rohs, R., Honig, B., Bussemaker, H.J.,and Mann, R.S. (2011) Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins. Cell 147:1270–1282.
Riley, T.R., Slattery, M., Abe, N., Rastogi, C., Liu, D., Mann, R.S., and Bussemaker, H.J. (2014) SELEX-seq: a method for characterizing the complete repertoire of binding site preferences for transcription factor complexes. Methods Mol. Biol. 1196:255–278.
selex.infogainSummary
, selex.mm
, selex.run
# Calculate information gain for a fixed range ig1 = selex.infogain(sample=r2, k=c(8:10), markovModel=mm) # View the results selex.infogainSummary()[,c(1,2,3,4,5)] # Now calculate for the default range ig2 = selex.infogain(sample=r2, markovModel=mm) # View the results again selex.infogainSummary()[,c(1,2,3,4,5)]