Supplementary note 1.
Identification of transcripts with dose-dependent expression change
The transcripts whose expression changes are in accordance with the imatinib doses
across sublines can fall into two categories, directly or inversely correlated with
escalatinb imatinib doses. We used Bartholomew’s homogeneity law for ordered
alternatives, modified F statistics for comparison of more than two groups.1 This test is
an extended version of one-side t-tests modified to deal with more than two groups.
First, 5 mean expression levels of control K562 and 4 resistant sublines were considered
as continuum corresponding 200 nM of imatinib dose increments up to 800 nM. The
significance level of up- and down-progression was determined under the alternative
hypotheses,
H1 : mcont  m200nM  m400nM  m600nM  m800nM
or
the
vice
versa, H1 : mcont  m200nM  m400nM  m600nM  m800nM , respectively. Five mean values of
expression ( mcont , m200nM , m400nM , m600nM , and m800nM ) of a gene are reduced into a
    
set of l means ( m1 , m2 , m3 , m4 , m5 ) treating m j , j 1  (a j m j  a j 1m j 1 ) (a j  a j 1 ) as a
single observation when m j  m j 1 or m j  m j 1 considering weights a j and a j 1 .
Then, Fk is calculated using reduced l number of means:
ni (mˆ i  x..) 2
Fk  
(l  1) S 'e2
i 1
k
where, S 'e 2 is residual sum of squares with degree of freedom, N  l .
1
The significance level is calculated using incomplete B function,
k
k
l 2
l 2
Pr{Fk  r}   p(l , k ) Pr{Fl 1, N l  r}  p(l , k ) I1 z ( 12 ( N  l ), 12 (l  1))
Pr{Fk  0}  p(1, k )
where, z  (l 1)r ( N  l  (l 1)r ) .
Since we dealt with many number of probe sets, the adjustment problem arising from
multiple hypotheses testing must be considered. We used Q-value package
(http://faculty.washington.edu/~jstorey/qvalue/) that performs multiple adjusting based
on false discovery rate (FDR) methods.2 FDR is measured as the ratio of truly null
features over the total number of tests called significant and 5% of FDR (q-value <
0.05) was considered significant. The transcripts that passed the test for up- and downprogression were further tested for t-test both on high imatinib dose groups (600 nM
and 800 nM) as previously described.3 We compared the gene expression between K562
control and high imatinib dose groups (600 nM and 800 nM) using Student’s t-test with
Welch correction. Test was performed under the assumption of unequal variance, as
previously suggested.4 Genes that passed the second criteria, both significant in 600 nM
and 800 nM t-tests, were regarded to be coordinately changed across resistant sublines.
In this way, genes whose expression changes correlated or inversely correlated with
imatinib doses increments were identified and defined as up-progression and downprogression, respectively.
2
References
1. Bartholomew,D.J. (1959) A test of homogeneity for ordered alternatives.
Biometrika, 46, 36-48.
2. Storey,J.D. and Tibshirani,R. (2003) Statistical significance for genomewide
studies. Proc. Natl. Acad. Sci. U. S. A, 100, 9440-9445.
3. Tseng,Y.H., Butte,A.J., Kokkotou,E., Yechoor,V.K., Taniguchi,C.M.,
Kriauciunas,K.M., Cypess,A.M., Niinobe,M., Yoshikawa,K., Patti,M.E. et al.
(2005) Prediction of preadipocyte differentiation by gene expression reveals role
of insulin receptor substrates and necdin. Nat Cell Biol., 7, 601-611.
4.Ideker,T., Thorsson,V., Siegel,A.F. and Hood,L.E. (2000) Testing for differentiallyexpressed genes by maximum-likelihood analysis of microarray data. J. Comput.
Biol., 7, 805-817.
3