  \Kepler has revolutionised our understanding of both exoplanets and their
host stars. Asteroseismology is a valuable tool in the characterisation of
stars and \Kepler is an excellent observing facility to perform
asteroseismology. Here we select a sample of 35 \Kepler solar-type stars which
host transiting exoplanets (or planet candidates) with detected solar-like
oscillations. Using available \Kepler short cadence data up to Quarter 16 we
create power spectra optimised for asteroseismology of solar-type stars. We
identify modes of oscillation and estimate mode frequencies by ``peak bagging''
using a Bayesian MCMC framework. In addition, we expand the methodology of
quality assurance using a Bayesian unsupervised machine learning approach. We
report the measured frequencies of the modes of oscillation for all 35 stars
and frequency ratios commonly used in detailed asteroseismic modelling. Due to
the high correlations associated with frequency ratios we report the covariance
matrix of all frequencies measured and frequency ratios calculated. These
frequencies, frequency ratios, and covariance matrices can be used to obtain
tight constraint on the fundamental parameters of these planet-hosting stars.
