In [1]:
from msdas import *
from msdas import yeast
%pylab inline
In [2]:
from easydev import gsf
In [3]:
filename = gsf("msdas", "data", "Yeast_all_raw.csv")
In [4]:
rep = replicates.Replicates(filename, verbose=True)
In [5]:
# a = annotations.Annotations(rep, 'YEAST', verbose=True)
# a.set_annotations()
# a.to_pickle(tag='all')
rep.read_annotations(gsf('msdas', 'data', 'YEAST_annotations_all.pkl'))
In [7]:
rep.merge_peptides()
In [8]:
# if you have already an instance of MassSpecReader, you can call
# directly read the replicates as follow
# r = readers.MassSpecReader(filename, merge_peptides=True)
# Replicatse is a child of MassSpecReader, so you can also do :
rep = replicates.Replicates(rep)
In [9]:
data = rep.hist_coefficient_variation(normed=True, color="red")
In [10]:
rep.metadata.columns
Out[10]:
In [11]:
rep.measurements.columns
Out[11]:
In [12]:
rep = replicates.ReplicatesYeast(rep)
In [13]:
rep.measurements.columns
Out[13]:
In [14]:
rep.boxplot()
In [15]:
rep.plot_mu_sigma(["a0_t0"])
In [16]:
rep.hist_na_per_experiments()
# there are 108 experiments() with replicates, which is the xaxis
In [17]:
na = rep.pcolor_na(sort_index=True, noxticks=True)
In [18]:
rep.plot_na_per_experiment()
In [19]:
mu = rep.get_mu_df()
In [20]:
mu.ix[0], rep.df.ix[0].Identifier
Out[20]:
In [ ]: