we selected eight genes known to be involved in the ras pathway , namely cdk5 , hras , mapk1 , mapk3 , map2k1 , map2k2 , ngfr and raf1 .
core genes due to their relevance in the ras pathway   and their consequential importance in colorectal cancer .
the knock - down experiments were performed on the eight core genes using short hairpin rna ( shrna ) in two colorectal cancer cell lines sw480 and sw620 . for each knock - down
there are six replicates ( except cdk5 in sw620 with five replicates ) with three different types of controls ( empty vector , nontarget and non transduced ) , totaling 125 samples .
we used the affymetrix genechip hg - u133plus2 platform to profile the gene expression of each sample .
we used the simpleaffy bioconductor package   to check the quality of each individual cel file .
1 shows that a majority of files contains a sufficiently large percentage of present calls ( >  40% , except for biological replicates one and two and hras biological replicate three with 39.58% ) and all scale factors lie within a 3-fold range which complies with the good quality guidelines from affymetrix . in more detail
, we can observe that those cel files that were generated in the early stages of the data generation are of lower quality than the rest of the files , namely the biological replicates one and two ( fig .  2 and table  1 ) .
the raw and normalized data are available from ncbi gene expression omnibus repository   with accession number gse53091 .
a successful knock - down experiment should result in significantly lower expression compared to the unperturbed samples . here , we assess the quality of a knock - down experiments by testing the difference between matched knock - down samples versus nontarget control samples using a wilcoxon signed rank test . in fig .  3
, we show the difference between knock - down and control sample expression for each of the eight knock - downs for both cell - lines together . in each plot , the knocked - down gene is highlighted in blue and the obtained p - values are represented by symbols in the bottom of each plot .
the significance levels are represented as follows :  * * *  for p  <  0.001 ,  * *  for p  <  0.01 ,  *  for p  <  0.05 and 
- for p  <  0.1 . from the eight plots in fig .  3
, we can observe that the difference in expression between knock - down and control samples is significant for all of the eight knock - downs ( the differential expression of the blue boxes is significantly lower than zero ) . in our study
, we determined the set of significantly affected genes for each of the eight knock - downs .
for example , the knock - down of raf1 significantly changes the expression of map2k2 and ngfr with p - values  <  0.001 ( only considering the eight core genes ) .
we then used the set of significantly affected genes to quantitatively validate inferred gene regulatory interactions .
we selected eight genes known to be involved in the ras pathway , namely cdk5 , hras , mapk1 , mapk3 , map2k1 , map2k2 , ngfr and raf1 .
core genes due to their relevance in the ras pathway   and their consequential importance in colorectal cancer .
the knock - down experiments were performed on the eight core genes using short hairpin rna ( shrna ) in two colorectal cancer cell lines sw480 and sw620 . for each knock - down
there are six replicates ( except cdk5 in sw620 with five replicates ) with three different types of controls ( empty vector , nontarget and non transduced ) , totaling 125 samples .
we used the affymetrix genechip hg - u133plus2 platform to profile the gene expression of each sample .
we used the simpleaffy bioconductor package   to check the quality of each individual cel file .
1 shows that a majority of files contains a sufficiently large percentage of present calls ( >  40% , except for biological replicates one and two and hras biological replicate three with 39.58% ) and all scale factors lie within a 3-fold range which complies with the good quality guidelines from affymetrix . in more detail
, we can observe that those cel files that were generated in the early stages of the data generation are of lower quality than the rest of the files , namely the biological replicates one and two ( fig .  2 and table  1 ) .
the raw and normalized data are available from ncbi gene expression omnibus repository   with accession number gse53091 .
a successful knock - down experiment should result in significantly lower expression compared to the unperturbed samples . here , we assess the quality of a knock - down experiments by testing the difference between matched knock - down samples versus nontarget control samples using a wilcoxon signed rank test . in fig .  3
, we show the difference between knock - down and control sample expression for each of the eight knock - downs for both cell - lines together . in each plot , the knocked - down gene is highlighted in blue and the obtained p - values are represented by symbols in the bottom of each plot .
the significance levels are represented as follows :  * * *  for p  <  0.001 ,  * *  for p  <  0.01 ,  *  for p  <  0.05 and  - for p 
<  0.1 . from the eight plots in fig .  3 , we can observe that the difference in expression between knock - down and control samples is significant for all of the eight knock - downs ( the differential expression of the blue boxes is significantly lower than zero ) . in our study
, we determined the set of significantly affected genes for each of the eight knock - downs .
for example , the knock - down of raf1 significantly changes the expression of map2k2 and ngfr with p - values  <  0.001 ( only considering the eight core genes ) .
we then used the set of significantly affected genes to quantitatively validate inferred gene regulatory interactions .
in this article we described a unique data set containing ras pathway - related gene knock - down experiments in two different colon cancer cell - lines .
it contains the expression values from the knock - down of eight genes as well as three different controls in six biological replicates .
the genome - wide gene expression was measured using the human genome u133 plus 2.0 array .
this data was recently used in a published study on the validation of regulatory gene networks .
r code enabling to programmatically access the data and to fully reproduce the results presented in the paper .
r code enabling to programmatically access the data and to fully reproduce the results presented in the paper .
 quantitative validation of gene regulatory networks ( grns ) inferred from observational expression data is a difficult task usually involving time intensive and costly laboratory experiments . we were able to show that gene knock - down experiments can be used to quantitatively assess the quality of large - scale grns via a purely data - driven approach ( olsen et al . 
 2014 ) . 
 our new validation framework also enables the statistical comparison of multiple network inference techniques , which was a long - standing challenge in the field.in this data in brief we detail the contents and quality controls for the gene expression data ( available from ncbi gene expression omnibus repository with accession number gse53091 ) associated with our study published in genomics ( olsen et al . 
 2014 ) . 
 we also provide r code to access the data and reproduce the analysis presented in this article . 
Direct link to deposited data
Experimental design, materials and methods
Short hairpin RNA experiments
Quality control
Normalization
Basic analysis
Discussion
Supplementary data