BACKGROUND
type  <dig> diabetes mellitus  is an autoimmune disease caused by the selective destruction of the pancreatic beta-cells causing impaired insulin secretion.
beta-cell dysfunction and death in t1dm is the result of direct contact with activated macrophages and t-lymphocytes, and/or exposure to soluble mediators secreted by these cells, such as cytokines, oxygen free radicals and nitric oxide   <cit> .
there is increasing evidence that apoptosis is the main cause of beta-cell death at the onset of t1dm  <cit>  and after islet transplantation  <cit>  apoptosis is a regulated process, affected by expression of diverse pro- and anti-apoptotic genes  <cit>  cytokines play a role in the inflammatory destruction of islet grafts immediately after transplantation  <cit>  a process that hampers the success of islet transplantation in patients with t1dm.
in vitro beta-cell exposure to the cytokine interleukin -1β induces functional impairment, whereas exposure to il-1β in combination with interferon -γ and/or tumor necrosis factor -α, induces beta-cell death by apoptosis in rodent and human islet cells after a period of 3– <dig> days  <cit>  these cytokines modify the expression of several hundreds of genes in beta-cells, including stress response genes that are either protective or deleterious for beta-cell survival, whereas genes related to differentiated beta-cell functions are mostly down-regulated  <cit>
dna microarrays have become a standard tool for several applications in molecular biology and provide a way to monitor the expression of thousands of genes in a single assay.
the two major microarray platforms presently in use are the high density microarrays produced by in situ synthesis and the arrays produced by deposition of pre-synthesized dna onto a solid surface.
one widely used implementation is the affymetrix genechip which uses photolithography and solid-phase chemistry to produce high density arrays of 25-mer oligonucleotides  <cit> .
spotted long oligonucleotides arrays were recently introduced as an alternative to cdna arrays and in situ synthesized oligonucleotide arrays  <cit> .
utilizing this technology we have prepared a custom oligonucleotide array representing  <dig> genes chosen for their putative involvement in beta cell death, the apochip.
gene selection was based on the analysis of a large number of array determinations of cytokine- and double stranded rna-treated primary beta cells or insulin-producing ins- <dig> cells using affymetrix chips  <cit> .
this targeted and low cost array to be made freely available to the research community will allow the performance of detailed time-course studies and thus contribute to the understanding of the molecular events leading to beta cell dysfunction and death in diabetes mellitus.
to evaluate the performance of the spotted oligonucleotide array, we presently used two approaches.
first we investigated the ability of the individual probes to respond to changes in target concentration.
we expected that the m-value  would be proportional to the target concentration on a logarithmic scale and that slopes ideally would be close to one.
we performed a weighted regression of m on concentration  using data from hybridisations at five different target concentrations.
next we used ten dissimilar rna samples to compare the gene expression between the spotted array and affymetrix platforms.
we expected that this would yield a sufficient number of differentially expressed genes to allow for meaningful conclusions to be drawn about the concordance between the two platforms.
our data suggest a good reproducibility for technical replications both within and between chips.
high concordance to the affymetrix genechip in terms of relative gene expression indicates that the apochip is a reliable tool for studying the molecular mechanisms involved in beta cell apoptosis.
RESULTS
the model based approach
internal replication
the results of the internal replicates are shown in table  <dig>  the spot variation was roughly  <dig>  fold as large as the measurement variation.
this shows that there are moderate variations in the replicated spots within a chip.
the channel variation was of the same order of magnitude as the spot variation except for the lowest target concentration, where it was much larger .
the origin of the channel variation remains to be clarified, but it may be due to intensity dependent properties between the two channels.
by normalising the two channels against one another, block wise, we obtained only a small reduction in the channel variance .
the two chips with the lowest concentration generally showed higher variance values than at the higher concentrations, and may reflect that the target concentration for the test sample  is close to the lower detection limit of this system, a hypothesis supported by the substantial increase in "bad" and "not found" calls around this concentration .
the first column σωm is the average measurement error, the second σs is the spot variation, and the third σc is the channel variation.
the fourth column is the median fold-change, exp , between the two channels.
the last column is the ratio of median fold-change to median fold-change for concentration  <dig>
external replication
the first column is the additional variance where a positive value indicates additional variance.
the last column is the variance of the measurement error obtained from table  <dig> and is included for comparison.
the spot variance provides information on the difference between using a one-colour system as opposed to a two-colour system.
in a two-colour system the spot variance terms for each channel within a chip cancel when using ratios.
thus a log <dig> fold-change obtained from two chips in a one colour system will have a variance of at least 2σs <dig> + 2σ2ω <dig> compared to a two colour system where it is 2σs <dig> .
as depicted in table  <dig> the estimated one-colour variance was comparable to the spot variance when print-tip differences were accounted for in the normalisation.
in the first column a global median centering is used, and in the second a median centering for each of the  <dig> blocks is used.
the last column gives 2σs <dig> for comparison.
fold-change regression
the result of the regression is illustrated in figure  <dig>  if the fold-change is proportional to the concentration the slope β in the regression of log <dig> fold-changes is  <dig>  as can be seen in figure  <dig> most slopes are in the range  <dig> – <dig>  .
interestingly, there seems to be a spread around  <dig> suggesting that each gene has its own sensitivity to changes in the concentration.
a formal test at level 5% for the slope being equal to one gives acceptance in only 25% of the genes.
furthermore, as the lower left subplot of figure  <dig> shows, when the signal intensity is very high all slopes are either larger than  <dig> or very small.
also, a small value of the slope does not imply that the probe does not respond at all, rather the sensitivity to changes in the concentration is limited.
the physical origin of these phenomena is unclear.
using the linear relation between the measured log <dig> fold-changes and the log <dig> concentration we may ask for which probes are we able to detect a true fold-change of a certain size.
using average properties and considering only internal replication we found in our experiments that for a true log2fold-change λ the measured log <dig> fold-change is roughly normally distributed with mean βλ and standard deviation  <dig> .
if we want the measured log <dig> fold-change to be larger than αλ, for some chosen value of α, the probability of this event is the probability that a standard normal variate is bigger than  λ/ <dig> .
as an example, if we require this latter probability to be bigger than  <dig> , we find that we can use the probes with β > α. elaborating on this example, if we take α =  <dig> , there are in our experiment  <dig> % of the probes satisfying β >  <dig> , with  <dig> probes only left out.
as depicted in table  <dig> we observed a discrepancy between the log <dig> concentration and the median log <dig> fold-change.
this may partly be accounted for by the scanner settings which were set to fixed but arbitrary values.
considering the self-self hybridisations  it is evident that the settings for the test channel were too high compared to the settings for the reference channel.
this effect may be minimized by using automated settings generated by the scanning software .
however, the ratios between two consecutive concentrations are close to the expected values except for the highest concentration where it is lower than expected .
cross platform comparison
we compared the relative expression of  <dig> genes present on both the apochip and affymetrix genechip 230a arrays.
these genes, corresponding to  <dig> probes on the apochip, were used to compare the relative gene expression profiles in ten rat rna samples.
on average,  <dig> % of the spots were called "good" by the scanarray express software and  <dig> % was called either "bad" or "not found".
the samples and the pooled reference was analysed separately on genechip 230a arrays, since this system utilizes single colour hybridisations.
normalised m-values  were calculated for each probe set on the array using rma  <cit>  and affymetrix mas  <dig>  algorithm that compares signal intensity from perfect-match and mis-match 25-mers  <cit> .
on average,  <dig> % of the genes surveyed on these arrays were called "present" and  <dig> % were called "absent" and the remainder "marginal" using mas  <dig> .
this software also reports calls for "increased" , "decreased"  and "no change"  for the relative gene expression.
to take into account possible differences due to normalisation methods we compared the results obtained by our approach  to those obtained using rma and a lowess  procedure implemented in midas  <cit> .
we found similar results particularly when low intensity data was excluded, as described below .
as low intensity data are prone to increased variation  <cit>  and therefore less reliable we set the following criteria for the comparison: a. affymetrix array:  <dig>  for "nc" calls both test and reference pool signal should be called "present",  <dig>  for "i" calls the test signal value should be called "present",  <dig>  for "d" calls the reference pool signal should be called "present"; b. apochip: measurements associated with "not found" or "bad" were excluded.
we then focused on the remaining  <dig> probes that fulfilled the above criteria in all ten measurements on both platforms.
the results are listed in table  <dig> and illustrated in figure  <dig> and figure  <dig>
the first column show the different steps of the data filtering, the second show the number of probes and genes compared, and the third show the median coefficient of correlation.
without this quality filtering of the probes the median of the weighted pearson correlation was  <dig> , whereas the filtering increased this value to  <dig>  .
a further filtering of the probes may be relevant.
if a gene has no differential expression between the ten samples there is no possibility of estimating the correlation.
similarly, if the probe does not respond at all in one of the two platforms, the estimated correlation is unreliable.
in an attempt to avoid this we removed probes that had a low variation over the ten samples in either one or both of the two platforms.
the affymetrix genechips showed the largest range of the log <dig> ratios.
to compare a large number of probes and include only the most varying we set an arbitrary cut-off of  <dig>  for the affymetrix platform.
to include a similar number of probes for the apochip we set an arbitrary cut-off of  <dig>  for the variance of this platform.
this reduced the number of probes to  <dig>  .
for this reduced set of probes the median correlation was  <dig>  , indicating a tight concordance between the two array types.
the distribution of the genes excluded from the analyses is illustrated in figure  <dig>  of the  <dig> most varying genes,  <dig> gave discordant results exhibiting a negative correlation .
further analysis of these genes revealed that in most instances the signal intensities were below the mean signal intensity on either one or both platforms.
moreover, two of these genes displayed variations close to the lower limits for one or both platforms as described above, indicating that the correlations obtained for these genes may be less reliable .
to further address this issue we performed a blast  <cit>  search based on the long oligonucleotide sequences.
we then mapped these probes and corresponding affymetrix probe-sets to the mrna sequence on which the apochip probe was based.
second, we checked for sequence overlap between the probes of the corresponding platforms.
as depicted in table  <dig> we found that six of the affymetrix probe-sets mapped to the apochip mrna but only one probe-set  showed overlap with the apochip oligonucleotide probe sequence.
for two of the remaining probes the affymetrix probes did not properly match the apochip mrna, suggesting that these sequences interrogate different sequences for these genes.
for the last apochip probe  the mrna annotation was changed and the 60-mer did not match the transcript perfectly.
in cases where both platform sequences align perfectly to the apochip mrna other factors such as differences in specificity and sensitivity, rna splice variants, and rna structure of the probes may be important.
a. low signal intensity ; b. affymetrix and long oligonucleotide probes mapped to the apochip target mrna; c. affymetrix and long oligonucleotide probes mapped partly or not at all to the apochip target mrna; d. probes exhibiting variation close to the lower limits shown in figure  <dig>  *.
new annotation obtained by blast.
discussion
microarrays have been widely used for expression profiling  <cit> , discovery of gene function  <cit> , pathway dissection  <cit> , classification of clinical samples  <cit>  as well as investigation of rna splice variants  <cit> .
several studies have been conducted comparing gene expression across platforms with varying results  <cit> .
whereas quantitative rt-pcr are usually found to agree well with corresponding array data concerns have been raised in some studies comparing different array formats  <cit> .
thus, kuo et al.
<cit>  compared cdna and affymetrix 25-mer arrays and reported little concordance.
the data in this study, however, was originated from two different laboratories and it is not clear whether the poor agreement was due to differences in the array types.
moreover, these results were based on absolute measurements which may be misleading  <cit> .
li et al.
<cit>  and kothapalli et al.
<cit>  also used cdna and affymetrix arrays and in both cases found substantial discrepancies; based on these findings, it was inferred that cdna arrays often fail to identify differentially expressed genes.
on the other hand, strong support for the use of long oligonucleotide microarrays comes from two independent studies  <cit> , and several recent studies suggest a robust concordance between the different microarray platforms  <cit> .
hughes et al.
<cit>  reported high concordance utilizing data from 60-mer oligonucleotide arrays synthesized by an ink-jet oligonucleotide synthesizer, cdna arrays and affymetrix genechip arrays.
barczak et al.
<cit>  compared relative gene expression measurements of a large collection of spotted 70-mers against affymetrix genechips and found good agreement.
although, the majority of the most differentially expressed probes yielded high correlations, there were exceptions .
there was also a group of genes exhibiting relatively large log <dig> fold-change variation in one, but not the other, platform .
these findings may partly be explained by differences in sensitivity and specificity and other probe specific effects.
of note, in some cases differences in transcript annotation and/or rna splicing may be more important than discrepancies in array performance.
several factors may influence the reproducibility when comparing data across platforms.
proper gene identification is essential as genes can only be compared if they are accurately identified on both platforms  <cit> .
this can be difficult as transcript information often comes from different sources and are continuously being improved.
the starting material must be consistent and procedures for rna handling standardized.
there are several labelling procedures in use, amplification versus no amplification, direct versus indirect dye incorporation which may contribute to downstream biases  <cit> .
in this study the samples were treated identically prior to rna amplification and similar amplification and labelling protocols were used for both array types.
pre-processing and methods for data handling may also influence the final results  <cit> .
as stated in the results section, there were differences using different spot identification software and normalisation algorithms, but these differences were substantially reduced by removing low intensity data and by comparing only the most varying genes .
moreover, when comparing gene expression data across platforms it is essential to do so using relative measurements, since absolute measurements are affected by probe and platform specific properties that may cause misleading interpretations  <cit> .
as discussed above, low signal intensities are prone to increased variation  <cit>  a phenomenon that is well established for most array formats, including spotted  <dig> mer arrays  <cit> , in situ synthesized  <dig> mer arrays  <cit>  and genechips  <cit> .
thus, it was not surprising to find that the correlation between differential measurements improved significantly when low-intensity measurements were excluded.
although intensities between two identical samples labelled to different dyes are rarely equal across all spots, we find that much of this variation is removed after proper normalisation .
two-colour hybridisations are generally used for spotted arrays, and many study designs involve comparison of the test sample to a common reference sample.
accurate quantification of a particular gene requires that the reference sample contains sufficient rna to produce a clear signal for the corresponding probe.
reference samples may be generated from a pool of several cell lines, or as here, by pooling of all samples obtained from different tissues.
the rationale for pooling the samples is that differentially expressed transcripts will also be present in the reference.
reference pools may not always produce sufficient signal intensity to allow for accurate quantification of some of the probes.
when using affymetrix mas  <dig>  software to analyse the pool reference for the subset of genes associated to both platforms,  <dig> % of the probe sets were called "present", as compared to  <dig> % "present" calls on average in the present data.
different designs such as a reference-free setup where pairs of test samples are compared directly may be preferable depending on the application  <cit> .
oligonucleotide probe design may also be important for signal intensity and for measuring differential gene expression.
oligonucleotide probes are designed on the basis of sequence.
several criteria, such as gc content and melting point, are used in the design but it is not possible to accurately account for differences in structure which may lead to unwanted steric effects.
we observed that there were sometimes large numerical differences in the signal intensity of different spotted probes corresponding to the same gene  a phenomenon that has been noted by others  <cit> .
in a few cases long oligonucleotides representing the same gene gave discordant results.
such differences between probes may depend on several factors, including low sensitivity of some probes, alternative splicing, nucleic acid structure, distance from the 3' end of the rna transcripts, gc content, and cross-hybridisation to unknown or poorly characterized mrnas including pseudo genes and non-coding rnas.
hence, the use of standardised sets of probes and protocols is an important issue when data from different laboratories and array platforms are compared  <cit> .
selection of a suitable microarray platform is influenced by several considerations.
the affymetrix system has been widely used for several applications and holds the advantage of standardisation in terms of probes and hybridisation protocols and, to some extent, data quantification  <cit> .
however, this technology has been limited by cost considerations for projects involving a large number of samples.
spotted arrays are labour intensive, but they can be made in large quantities by individual laboratories at a lower cost.
moreover, sequences with high homology to other genes can be avoided and probes for novel genes and gene variants may readily be designed.
in conclusion, we have constructed and validated the apochip, a spotted microarray designed for the study of beta cell death in diabetes mellitus that may be of use to the scientific community.
designing and printing in-house arrays offers a flexible mean to carry out combinations of extensive multipoint and detailed time course gene expression analysis, following exposure of pancreatic beta-cells to different pro-apoptotic stimuli.
we expect that this array will help research in the field enabling the performance of more detailed and complete experiments.
CONCLUSIONS
we have validated a rat oligonucleotide microarray constructed for the study of beta cell death in diabetes mellitus.
we evaluated the technical reproducibility of the array by estimating the variance associated with the internal and external replication.
we then used a fold-change regression model to estimate the ability of the probes to respond to changes in target concentration.
finally, we used ten dissimilar rna samples to compare the relative gene expression between the spotted array and affymetrix platforms.
we found a high reproducibility for technical replications both within arrays and between arrays, with most oligonucleotide probes responding to target concentration in a manner close to that predicted by the model.
there was a clear relation between successive data filtering and concordance between the two array types; by comparing only the most variable genes on both platforms we found that there was a high concordance between the apochip and the genechip platform, supporting the validity of this approach.

 type diabetes mellitus is an autoimmune disease caused by the selective destruction of the pancreatic beta-cells causing impaired insulin secretion. beta-cell dysfunction and death in t1dm is the result of direct contact with activated macrophages and t-lymphocytes, and/or exposure to soluble mediators secreted by these cells, such as cytokines, oxygen free radicals and nitric oxide. there is increasing evidence that apoptosis is the main cause of beta-cell death at the onset of t1dm and after islet transplantation apoptosis is a regulated process, affected by expression of diverse pro- and anti-apoptotic genes cytokines play a role in the inflammatory destruction of islet grafts immediately after transplantation a process that hampers the success of islet transplantation in patients with t1dm. in vitro beta-cell exposure to the cytokine interleukin -1β induces functional impairment, whereas exposure to il-1β in combination with interferon -γ and/or tumor necrosis factor -α, induces beta-cell death by apoptosis in rodent and human islet cells after a period of 3– days these cytokines modify the expression of several hundreds of genes in beta-cells, including stress response genes that are either protective or deleterious for beta-cell survival, whereas genes related to differentiated beta-cell functions are mostly down-regulated dna microarrays have become a standard tool for several applications in molecular biology and provide a way to monitor the expression of thousands of genes in a single assay. the two major microarray platforms presently in use are the high density microarrays produced by in situ synthesis and the arrays produced by deposition of pre-synthesized dna onto a solid surface. one widely used implementation is the affymetrix genechip which uses photolithography and solid-phase chemistry to produce high density arrays of 25-mer oligonucleotides. spotted long oligonucleotides arrays were recently introduced as an alternative to cdna arrays and in situ synthesized oligonucleotide arrays. utilizing this technology we have prepared a custom oligonucleotide array representing genes chosen for their putative involvement in beta cell death, the apochip. gene selection was based on the analysis of a large number of array determinations of cytokine- and double stranded rna-treated primary beta cells or insulin-producing ins- cells using affymetrix chips. this targeted and low cost array to be made freely available to the research community will allow the performance of detailed time-course studies and thus contribute to the understanding of the molecular events leading to beta cell dysfunction and death in diabetes mellitus. to evaluate the performance of the spotted oligonucleotide array, we presently used two approaches. first we investigated the ability of the individual probes to respond to changes in target concentration. we expected that the m-value would be proportional to the target concentration on a logarithmic scale and that slopes ideally would be close to one. we performed a weighted regression of m on concentration using data from hybridisations at five different target concentrations. next we used ten dissimilar rna samples to compare the gene expression between the spotted array and affymetrix platforms. we expected that this would yield a sufficient number of differentially expressed genes to allow for meaningful conclusions to be drawn about the concordance between the two platforms. our data suggest a good reproducibility for technical replications both within and between chips. high concordance to the affymetrix genechip in terms of relative gene expression indicates that the apochip is a reliable tool for studying the molecular mechanisms involved in beta cell apoptosis.  the model based approach internal replication the results of the internal replicates are shown in table the spot variation was roughly fold as large as the measurement variation. this shows that there are moderate variations in the replicated spots within a chip. the channel variation was of the same order of magnitude as the spot variation except for the lowest target concentration, where it was much larger. the origin of the channel variation remains to be clarified, but it may be due to intensity dependent properties between the two channels. by normalising the two channels against one another, block wise, we obtained only a small reduction in the channel variance. the two chips with the lowest concentration generally showed higher variance values than at the higher concentrations, and may reflect that the target concentration for the test sample is close to the lower detection limit of this system, a hypothesis supported by the substantial increase in "bad" and "not found" calls around this concentration. the first column σωm is the average measurement error, the second σs is the spot variation, and the third σc is the channel variation. the fourth column is the median fold-change, exp, between the two channels. the last column is the ratio of median fold-change to median fold-change for concentration external replication the first column is the additional variance where a positive value indicates additional variance. the last column is the variance of the measurement error obtained from table and is included for comparison. the spot variance provides information on the difference between using a one-colour system as opposed to a two-colour system. in a two-colour system the spot variance terms for each channel within a chip cancel when using ratios. thus a log fold-change obtained from two chips in a one colour system will have a variance of at least 2σs + 2σ2ω compared to a two colour system where it is 2σs. as depicted in table the estimated one-colour variance was comparable to the spot variance when print-tip differences were accounted for in the normalisation. in the first column a global median centering is used, and in the second a median centering for each of the blocks is used. the last column gives 2σs for comparison. fold-change regression the result of the regression is illustrated in figure if the fold-change is proportional to the concentration the slope β in the regression of log fold-changes is as can be seen in figure most slopes are in the range –. interestingly, there seems to be a spread around suggesting that each gene has its own sensitivity to changes in the concentration. a formal test at level 5% for the slope being equal to one gives acceptance in only 25% of the genes. furthermore, as the lower left subplot of figure shows, when the signal intensity is very high all slopes are either larger than or very small. also, a small value of the slope does not imply that the probe does not respond at all, rather the sensitivity to changes in the concentration is limited. the physical origin of these phenomena is unclear. using the linear relation between the measured log fold-changes and the log concentration we may ask for which probes are we able to detect a true fold-change of a certain size. using average properties and considering only internal replication we found in our experiments that for a true log2fold-change λ the measured log fold-change is roughly normally distributed with mean βλ and standard deviation. if we want the measured log fold-change to be larger than αλ, for some chosen value of α, the probability of this event is the probability that a standard normal variate is bigger than λ/. as an example, if we require this latter probability to be bigger than, we find that we can use the probes with β > α. elaborating on this example, if we take α =, there are in our experiment % of the probes satisfying β >, with probes only left out. as depicted in table we observed a discrepancy between the log concentration and the median log fold-change. this may partly be accounted for by the scanner settings which were set to fixed but arbitrary values. considering the self-self hybridisations it is evident that the settings for the test channel were too high compared to the settings for the reference channel. this effect may be minimized by using automated settings generated by the scanning software. however, the ratios between two consecutive concentrations are close to the expected values except for the highest concentration where it is lower than expected. cross platform comparison we compared the relative expression of genes present on both the apochip and affymetrix genechip 230a arrays. these genes, corresponding to probes on the apochip, were used to compare the relative gene expression profiles in ten rat rna samples. on average, % of the spots were called "good" by the scanarray express software and % was called either "bad" or "not found". the samples and the pooled reference was analysed separately on genechip 230a arrays, since this system utilizes single colour hybridisations. normalised m-values were calculated for each probe set on the array using rma and affymetrix mas algorithm that compares signal intensity from perfect-match and mis-match 25-mers. on average, % of the genes surveyed on these arrays were called "present" and % were called "absent" and the remainder "marginal" using mas. this software also reports calls for "increased", "decreased" and "no change" for the relative gene expression. to take into account possible differences due to normalisation methods we compared the results obtained by our approach to those obtained using rma and a lowess procedure implemented in midas. we found similar results particularly when low intensity data was excluded, as described below. as low intensity data are prone to increased variation and therefore less reliable we set the following criteria for the comparison: a. affymetrix array: for "nc" calls both test and reference pool signal should be called "present", for "i" calls the test signal value should be called "present", for "d" calls the reference pool signal should be called "present"; b. apochip: measurements associated with "not found" or "bad" were excluded. we then focused on the remaining probes that fulfilled the above criteria in all ten measurements on both platforms. the results are listed in table and illustrated in figure and figure the first column show the different steps of the data filtering, the second show the number of probes and genes compared, and the third show the median coefficient of correlation. without this quality filtering of the probes the median of the weighted pearson correlation was, whereas the filtering increased this value to. a further filtering of the probes may be relevant. if a gene has no differential expression between the ten samples there is no possibility of estimating the correlation. similarly, if the probe does not respond at all in one of the two platforms, the estimated correlation is unreliable. in an attempt to avoid this we removed probes that had a low variation over the ten samples in either one or both of the two platforms. the affymetrix genechips showed the largest range of the log ratios. to compare a large number of probes and include only the most varying we set an arbitrary cut-off of for the affymetrix platform. to include a similar number of probes for the apochip we set an arbitrary cut-off of for the variance of this platform. this reduced the number of probes to. for this reduced set of probes the median correlation was, indicating a tight concordance between the two array types. the distribution of the genes excluded from the analyses is illustrated in figure of the most varying genes, gave discordant results exhibiting a negative correlation. further analysis of these genes revealed that in most instances the signal intensities were below the mean signal intensity on either one or both platforms. moreover, two of these genes displayed variations close to the lower limits for one or both platforms as described above, indicating that the correlations obtained for these genes may be less reliable. to further address this issue we performed a blast search based on the long oligonucleotide sequences. we then mapped these probes and corresponding affymetrix probe-sets to the mrna sequence on which the apochip probe was based. second, we checked for sequence overlap between the probes of the corresponding platforms. as depicted in table we found that six of the affymetrix probe-sets mapped to the apochip mrna but only one probe-set showed overlap with the apochip oligonucleotide probe sequence. for two of the remaining probes the affymetrix probes did not properly match the apochip mrna, suggesting that these sequences interrogate different sequences for these genes. for the last apochip probe the mrna annotation was changed and the 60-mer did not match the transcript perfectly. in cases where both platform sequences align perfectly to the apochip mrna other factors such as differences in specificity and sensitivity, rna splice variants, and rna structure of the probes may be important. a. low signal intensity; b. affymetrix and long oligonucleotide probes mapped to the apochip target mrna; c. affymetrix and long oligonucleotide probes mapped partly or not at all to the apochip target mrna; d. probes exhibiting variation close to the lower limits shown in figure *. new annotation obtained by blast. discussion microarrays have been widely used for expression profiling, discovery of gene function, pathway dissection, classification of clinical samples as well as investigation of rna splice variants. several studies have been conducted comparing gene expression across platforms with varying results. whereas quantitative rt-pcr are usually found to agree well with corresponding array data concerns have been raised in some studies comparing different array formats. thus, kuo et al. compared cdna and affymetrix 25-mer arrays and reported little concordance. the data in this study, however, was originated from two different laboratories and it is not clear whether the poor agreement was due to differences in the array types. moreover, these results were based on absolute measurements which may be misleading. li et al. and kothapalli et al. also used cdna and affymetrix arrays and in both cases found substantial discrepancies; based on these findings, it was inferred that cdna arrays often fail to identify differentially expressed genes. on the other hand, strong support for the use of long oligonucleotide microarrays comes from two independent studies, and several recent studies suggest a robust concordance between the different microarray platforms. hughes et al. reported high concordance utilizing data from 60-mer oligonucleotide arrays synthesized by an ink-jet oligonucleotide synthesizer, cdna arrays and affymetrix genechip arrays. barczak et al. compared relative gene expression measurements of a large collection of spotted 70-mers against affymetrix genechips and found good agreement. although, the majority of the most differentially expressed probes yielded high correlations, there were exceptions. there was also a group of genes exhibiting relatively large log fold-change variation in one, but not the other, platform. these findings may partly be explained by differences in sensitivity and specificity and other probe specific effects. of note, in some cases differences in transcript annotation and/or rna splicing may be more important than discrepancies in array performance. several factors may influence the reproducibility when comparing data across platforms. proper gene identification is essential as genes can only be compared if they are accurately identified on both platforms. this can be difficult as transcript information often comes from different sources and are continuously being improved. the starting material must be consistent and procedures for rna handling standardized. there are several labelling procedures in use, amplification versus no amplification, direct versus indirect dye incorporation which may contribute to downstream biases. in this study the samples were treated identically prior to rna amplification and similar amplification and labelling protocols were used for both array types. pre-processing and methods for data handling may also influence the final results. as stated in the results section, there were differences using different spot identification software and normalisation algorithms, but these differences were substantially reduced by removing low intensity data and by comparing only the most varying genes. moreover, when comparing gene expression data across platforms it is essential to do so using relative measurements, since absolute measurements are affected by probe and platform specific properties that may cause misleading interpretations. as discussed above, low signal intensities are prone to increased variation a phenomenon that is well established for most array formats, including spotted mer arrays, in situ synthesized mer arrays and genechips. thus, it was not surprising to find that the correlation between differential measurements improved significantly when low-intensity measurements were excluded. although intensities between two identical samples labelled to different dyes are rarely equal across all spots, we find that much of this variation is removed after proper normalisation. two-colour hybridisations are generally used for spotted arrays, and many study designs involve comparison of the test sample to a common reference sample. accurate quantification of a particular gene requires that the reference sample contains sufficient rna to produce a clear signal for the corresponding probe. reference samples may be generated from a pool of several cell lines, or as here, by pooling of all samples obtained from different tissues. the rationale for pooling the samples is that differentially expressed transcripts will also be present in the reference. reference pools may not always produce sufficient signal intensity to allow for accurate quantification of some of the probes. when using affymetrix mas software to analyse the pool reference for the subset of genes associated to both platforms, % of the probe sets were called "present", as compared to % "present" calls on average in the present data. different designs such as a reference-free setup where pairs of test samples are compared directly may be preferable depending on the application. oligonucleotide probe design may also be important for signal intensity and for measuring differential gene expression. oligonucleotide probes are designed on the basis of sequence. several criteria, such as gc content and melting point, are used in the design but it is not possible to accurately account for differences in structure which may lead to unwanted steric effects. we observed that there were sometimes large numerical differences in the signal intensity of different spotted probes corresponding to the same gene a phenomenon that has been noted by others. in a few cases long oligonucleotides representing the same gene gave discordant results. such differences between probes may depend on several factors, including low sensitivity of some probes, alternative splicing, nucleic acid structure, distance from the 3' end of the rna transcripts, gc content, and cross-hybridisation to unknown or poorly characterized mrnas including pseudo genes and non-coding rnas. hence, the use of standardised sets of probes and protocols is an important issue when data from different laboratories and array platforms are compared. selection of a suitable microarray platform is influenced by several considerations. the affymetrix system has been widely used for several applications and holds the advantage of standardisation in terms of probes and hybridisation protocols and, to some extent, data quantification. however, this technology has been limited by cost considerations for projects involving a large number of samples. spotted arrays are labour intensive, but they can be made in large quantities by individual laboratories at a lower cost. moreover, sequences with high homology to other genes can be avoided and probes for novel genes and gene variants may readily be designed. in conclusion, we have constructed and validated the apochip, a spotted microarray designed for the study of beta cell death in diabetes mellitus that may be of use to the scientific community. designing and printing in-house arrays offers a flexible mean to carry out combinations of extensive multipoint and detailed time course gene expression analysis, following exposure of pancreatic beta-cells to different pro-apoptotic stimuli. we expect that this array will help research in the field enabling the performance of more detailed and complete experiments.  we have validated a rat oligonucleotide microarray constructed for the study of beta cell death in diabetes mellitus. we evaluated the technical reproducibility of the array by estimating the variance associated with the internal and external replication. we then used a fold-change regression model to estimate the ability of the probes to respond to changes in target concentration. finally, we used ten dissimilar rna samples to compare the relative gene expression between the spotted array and affymetrix platforms. we found a high reproducibility for technical replications both within arrays and between arrays, with most oligonucleotide probes responding to target concentration in a manner close to that predicted by the model. there was a clear relation between successive data filtering and concordance between the two array types; by comparing only the most variable genes on both platforms we found that there was a high concordance between the apochip and the genechip platform, supporting the validity of this approach. 
by using simple rules for comparison of data between platforms we found strong correlations between relative gene expression measurements made with spotted probes and in situ-synthesized 25-mer probe sets. in conclusion our data suggest that there is a high reproducibility of the apochip in terms of technical replication and that relative gene expression measurements obtained with the apochip compare well to the affymetrix genechip. the apochip is available to the scientific community and is a useful tool to study the molecular mechanisms regulating beta-cell apoptosis. type diabetes mellitus is a autoimmune disease caused by a long-term negative balance between immune-mediated beta-cell damage and beta-cell repair/regeneration. based on the information obtained by the analysis of several microarray experiments of beta-cells exposed to pro-apoptotic conditions and cytokines), we have developed a spotted rat oligonucleotide microarray, the apochip, containing 60-mer probes for genes selected for the study of beta-cell apoptosis.
 type diabetes mellitus is a autoimmune disease caused by a long-term negative balance between immune-mediated beta-cell damage and beta-cell repair/regeneration. following immune-mediated damage the beta-cell fate depends on several genes up- or down-regulated in parallel and/or sequentially. based on the information obtained by the analysis of several microarray experiments of beta-cells exposed to pro-apoptotic conditions and cytokines), we have developed a spotted rat oligonucleotide microarray, the apochip, containing 60-mer probes for genes selected for the study of beta-cell apoptosis.  the apochip was validated by a combination of approaches. first we performed an internal validation of the spotted probes based on a weighted linear regression model using dilution series experiments. second we profiled expression measurements in ten dissimilar rat rna samples for genes that were represented on both the spotted oligonucleotide collection and on the in situ-synthesized 25-mer arrays. internal validation showed that most of the spotted probes displayed a pattern of reaction close to that predicted by the model. by using simple rules for comparison of data between platforms we found strong correlations between relative gene expression measurements made with spotted probes and in situ-synthesized 25-mer probe sets.  in conclusion our data suggest that there is a high reproducibility of the apochip in terms of technical replication and that relative gene expression measurements obtained with the apochip compare well to the affymetrix genechip. the apochip is available to the scientific community and is a useful tool to study the molecular mechanisms regulating beta-cell apoptosis. 