CN102864499A - Microarray lattice method for biological chip - Google Patents
Microarray lattice method for biological chip Download PDFInfo
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- CN102864499A CN102864499A CN2012102823080A CN201210282308A CN102864499A CN 102864499 A CN102864499 A CN 102864499A CN 2012102823080 A CN2012102823080 A CN 2012102823080A CN 201210282308 A CN201210282308 A CN 201210282308A CN 102864499 A CN102864499 A CN 102864499A
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Abstract
The invention discloses a microarray lattice method for a biological chip. According to the method, quasi-Latin square experimental design is adopted and is divided into three kinds: 1, quasi-Latin square array lattice design in sub squares; 2, quasi-Latin square array lattice design among the sub squares; and 3, quasi-Latin square array lattice design in the sub squares and among the sub squares. By the microarray lattice design of the biological chip, space effect error caused by different factors can be avoided and eliminated to a certain degree, and the accuracy of biological experiments or experimental results is improved to a certain degree.
Description
Technical field
The present invention relates to biological technical field, relate to particularly a kind of biochip microarray dot matrix method.
Background technology
The methodological academic report of microarray data analysis mainly concentrates on the normalization at chip-count strong point behind the biochip hybridization and Systematic Error Correction to eliminate the variation error of different sources.Yang YH,Dudoit S,Luu P,Lin DM,Peng V,Ngai J,Speed TP.Normal ization for cDNA microarray data:a robust composite method addressing single and multiple slide systematic variation.Nucleic Acids Res 2002,30(4):e15。Tarca AL,Cooke JE,Mackay J.A robust neural networks approach for spatial and intensity dependent normalization of cDNA microarray data.Bioinformatics 2005,21:2674-2683。This mainly is because use the research of microarray technology mostly to be the dna microarray aspect, and used dna microarray chip can be buied from biotech firm, has saved very miscellaneous chip manufacturing process.The making of DNA chip needs preparation several thousand, several ten thousand cDNA, PCR product or oligonucleotide, and will be with their points on chip, and this process is very miscellaneous.Therefore, the methodological academic report of microarray data analysis seldom relates to the design of chip sample application array, and how to utilize specific dot matrix design to avoid and eliminate some variation errors known or unknown source.Recent years, increasing academic research problem turns to the protein bio-chip technology, is used for detecting various human diseasess with this scientific discovery human diseases biomarker.Chatterjee M,Mohapatra S,Ionan A,Bawa G,Ali-Fehmi R,Wang X,Nowak J,Ye B,Nahhas FA,Lu K,Witkin SS,Fishman D,Munkarah A,Morris R,Levin NK,Shirley NN,Tromp G,Abrams J,Draghici S,Tainsky MA.Diagnostic markers of ovarian cancer by high-throughput antigen cloning and detection on arrays.Cancer Res.2006;66:1181-90.Chatterjee,M.Ionan,A.Draghici,S.and Tainsky,MA.Epitomics:Global Profiling of Immune Response to Disease Using Protein Microarrays,OMICS:A Journal of Integrative Biology,200610:499-506.Chen C.,Wang X,Yu,J.,et a.Autoantibody Profiles Reveal Ubiquilin1as a Humoral Immune Response Target in Lung Adenocarcinoma,2007.Cancer Research 67,3461-3467.Draghici S,Chatterjee M,Tainsky MA.Epitomics:serum screening for the early detection of cancer on microarrays using complex panels of tumor antigens.Expert Rev Mol Diagn.2005.5:735-43.Wang X,Yu J,Sreekumar A,Varambally S,Shen R,Giacherio D,Mehra R,Montie JE,Pienta KJ,Sanda MG,Kantoff PW,Rubin MA,Wei JT,Ghosh D,Chinnaiyan AM.Autoantibody signatures in prostate cancer.N Engl J Med.2005353:1224-35.Zhong L,Hidalgo GE,Stromberg AJ,Khattar NH,Jett JR,Hirschowitz EA.Using protein microarray as a diagnostic assay for non-small cell lung cancer.Am J Respir Crit Care Med.2005172:1308-14。Different from the DNA chip, the dietary protein origin of protein chip is than more diversification of DNA, and different research is with different albumen, so each research team needs own making protein chip, optimize the protein chip dot matrix and arrange the variation error that can reduce different sources, improve the accuracy of experimental result.
In the micro-array biochip data analysis, the signal variation can come from different factors.These factors comprise: the hybridization conditions the when sample on the uniformity coefficient of chip list facial mask, point needle, point sample order, the chip is hybridized with target sample, scanner, etc.These variations generally show with ranks steric effect, point needle effect, point sample order effect.Tarca AL,Cooke JE,Mackay J.A robust neural networks approach for spatial and intensity dependent normalization of cDNA microarray data.Bioinformatics 2005,21:2674-2683。These effects usually show gradient in row or column, namely effect becomes gradually large with the increase of row or column or diminishes.Under normal conditions, every kind of biological sample (cDNA, oligonucleotide, PCR product, antibody, antigen or albumen) has several repetitions at same chip, how to utilize and repeat to avoid and eliminate the accuracy that these steric effect errors will be related to data, will have influence on the net result of whole research topic.How to utilize to repeat to avoid and eliminate these steric effect errors be exactly how these to be repeated to be arranged in the dot matrix of chip.Existing method generally is the inferior grid that does not repeat, and in same inferior grid, the point of repetition generally is that these are repeated to be arranged in same row or same delegation in the dot matrix, sometimes even connect together or stack up.Such aligning method there is no the effect of avoiding or eliminating the steric effect error of playing.The present invention will use for reference the principle of Latin square experimental design, design a series of dot matrix aligning methods, and such arrangement can take full advantage of the repetition of the point of biological sample on chip, effectively avoid and eliminate the error that steric effect causes.
The Latin square experimental design is a kind of method of the experimental design of statistics aspect.Yates F. (1933) Theformation of latin square for use in field experiments.Empire J.Exp.Agric.1:235-244. Latin square design is exactly that relevant how the arrangement in isometric two dimensional surface space repeated so that the steric effect error is effectively controlled.In Latin square, line number and columns equate that the factor number that statistical study relates to is identical with line number or columns with the repeat number of each factor, and a factor only repeats once in every delegation and each row.For example, in the Latin square of a 2X2, it is to arrange like this that factors A and B two repeat:
| B | A |
| A | B |
Number of lines and columns all are that 2, the A factor and Factor B only repeat once in row and column; In the Latin square of a 3X3, it is to arrange like this that factors A, B and C three repeat:
| B | A | C |
| A | C | B |
| C | B | A |
Perhaps, the row of going or exchanging wherein of exchanging wherein can form another Latin square:
| A | C | B |
| B | A | C |
| C | B | A |
Similarly Latin square is arranged and is had 12, does not list one by one.In any case but arrange, number of lines and columns all are that 3, the A factor, Factor B and the C factor only repeat once in row and column; In the Latin square of a 4X4, it is to arrange like this that factors A, B, C and D four repeat:
| B | A | D | C |
| A | D | C | B |
| C | B | A | D |
| D | C | B | A |
Perhaps, the row of going or exchanging wherein of exchanging wherein can form another Latin square:
| A | D | C | B |
| B | A | D | C |
| C | B | A | D |
| D | C | B | A |
Similarly Latin square is arranged and is had 576, does not list one by one.In any case but arrange, number of lines and columns all are that 4, the A factor, Factor B, the C factor and the D factor only repeat once in row and column.Also have 5X5,6X6 ..., etc., Latin square.Because each factor has a repetition at every delegation and each row, the mean value that each factor repeats just can effectively be eliminated the error that the steric effect of increasing or decreasing in gradient causes.Although dot matrix design and the Latin square design of micro-array biochip point sample are incomplete same, and similarity is arranged.The present invention uses for reference the Latin square design principle exactly, Latin square design is applied to the dot matrix design of the point sample of biochip.
The point sample of biochip generally is to finish with the point needle that is placed on the point sample needle plate.Point template is done up and down by computer program control and is moved forward and backward.Point template moves to sample disc (being generally 384 porose discs, the biological sample in the every hole) top that fills biological sample and is taken a sample to being displaced downwardly to suitable height in point needle aligning dish hole with point needle, move to chip position point sample on chip again.The dot matrix that every point needle is put out is an inferior grid array.As shown below, if be equipped with 16 point needles on the point template, 16 inferior grids are just arranged on every chip; If be equipped with 32 point needles on the point template, 32 inferior grids are just arranged on every chip.These 16 or 32 inferior grids have formed an inferior grid array, the biological sample array that each inferior grid is comprised of biological sample again.The aligning method of inferior grid array and the aligning method of biological sample array are directly connected to the control of steric effect error.
The array (4X4, Fig. 1) of 16 inferior grids that 16 point needles are pointed out
The array (4X8, Fig. 2) of 32 inferior grids that 32 point needles are pointed out
What the aligning method of the aligning method of existing inferior grid array and biological sample array can not effectively utilize biological sample repeats to avoid and eliminate the error that steric effect causes.In existing method following two characteristics are arranged: 1, the whole repetition of biological sample all is to be arranged in the same inferior grid, do not have the repetition of inferior grid array in the same chip; 2, in an inferior grid, generally be that biological sample is repeated to be arranged in same row or same delegation in the dot matrix, sometimes even connect together or stack up.For example, if with 32 inferior grid arrays of 32 point sample pin marks, get altogether 36 secondary pollutant samples, each biological sample repeats 4 times; So, each inferior grid array just has 144 points; Existing biological sample array is as shown in Figure 3, comprises arranging biological sample to repeat shown in the point sample method of " form A ", " form B " or " form A ".In these three dot matrix, although all be the array of 12X12, but since effectively do not utilize biological sample repeat dot-matrix array design, in the error of the data that the chip of pointing out with these three point sample methods obtains, comprising the steric effect error, the experiment analysis results that impact is final if this research is a research that detects disease, will reduce Detection accuracy to a certain extent.
Summary of the invention
The present invention has seen clearly the defective of above-mentioned dot-matrix array design, use for reference the principle of Latin square experimental design, design a series of class Latin square design dot matrix aligning methods, such arrangement can take full advantage of the repetition of the point of biological sample on chip, effectively avoids and eliminate the error that steric effect causes.
Technical scheme of the present invention is as follows:
A kind of biochip microarray dot matrix method, wherein, described sample microarray dot matrix adopts the class Latin square to arrange.
In a preferred embodiment of the present invention, described microarray dot matrix adopts the design of class Latin square dot matrix in each inferior grid.The dot matrix that " inferior grid " described here pointed out for each point needle.Here " class Latin square " namely is similar to Latin square design as previously mentioned, in the Latin square design, if any n the factor, this n factor is arranged in the array of n*n, and each factor has a repetition in every delegation and each row.The factor here replaces to biological sample.Namely hypothesis has n sample, then it is arranged in the sample array of n*n, and each sample has a repetition in every delegation and each row.
In another preferred embodiment of the present invention, adopt the design of class Latin square array dot matrix in the inferior grid of described microarray dot matrix between inferior grid.
In another embodiment of the present invention, adopt simultaneously the design of class Latin square array dot matrix in the inferior grid of described microarray dot matrix in inferior grid and between inferior grid.
Counting in each inferior grid of the present invention is identical, is arranged in the dot matrix of n*n, and the numerical value of .n depends on the point sample of laboratory sample amount, requirement of experiment and instrument and resolving power etc.For example, n can be 3-1000.
In the present invention, a plurality of inferior grids are lined up class Latin square array, and inferior lattice-array is classified n*n as, and the numerical value of n depends on the quantity of sampling head or sampling probe.For example, n can be 3-100.
Biochip of the present invention comprises DNA chip, RNA chip, iRNA chip, protein chip, antibody chip, antigen chip or carbohydrate chip.
Biochip of the present invention also film or the medium of other ankyrin, the film of fixed nucleic acid (comprising DNA, RNA) or the medium of other fixed nucleic acid of available liquid chip, ankyrin substitutes.
Biochip microarray dot matrix of the present invention design can be avoided and the steric effect error of eliminating the different factors and causing to a certain extent, improves related Bioexperiment or the accuracy of test-results.
Description of drawings
Fig. 1 is the array (4X4) of 16 inferior grids pointing out of 16 point needles;
Fig. 2 is the array (4X8) of 32 inferior grids pointing out of 32 point needles;
Among Fig. 3, A, B, C are respectively the array of prior art form A, form B and form A;
Fig. 4 is array of the present invention;
Fig. 5 is one of array synoptic diagram of the present invention
Fig. 6 is two of array synoptic diagram of the present invention
Fig. 7 is three of array synoptic diagram of the present invention
Fig. 8 is four of array synoptic diagram of the present invention
Embodiment
Describe the present invention in detail hereinafter with reference to embodiment.
Class Latin square design dot matrix of the present invention has been used for reference the principle of Latin square design two levels, and first level is level in the inferior grid; Second level is level between inferior grid.
1, the class Latin square design on the level in the inferior grid
In order to illustrate the Latin square design on the level in the inferior grid, again take above-mentioned identical example as example.If with 32 inferior grid arrays of 32 point sample pin marks, get altogether 36 secondary pollutant samples, each biological sample repeats 4 times; So, each inferior grid array just has 144 points.Biological sample array of the present invention is to arrange biological sample to repeat shown in the point sample method of " form A ", " form B " or " form A " with being different from.As shown below, in this example, with the works dot matrix that the class Latin square design on the level in the inferior grid of the present invention is made, in fact each inferior grid is comprised of 9 Latin square dot matrix, and the 1st, 10,19, No. 28 biological sample forms first Latin square dot matrix; 2nd, 11,20, No. 29 biological samples form second Latin square dot matrix; 3rd, 12,21, No. 30 biological samples form the 3rd Latin square dot matrix; 4th, 13,22, No. 31 biological samples form the 4th Latin square dot matrix; 5th, 14,23, No. 32 biological samples form the 5th Latin square dot matrix; 6th, 15,24, No. 33 biological samples form the 6th Latin square dot matrix; 7th, 16,25, No. 34 biological samples form the 7th Latin square dot matrix; 8th, 17,26, No. 35 biological samples form the 8th Latin square dot matrix; 9th, 18,27, No. 36 biological samples form the 9th Latin square dot matrix.This is first inferior grid dot matrix, and each the inferior grid dot matrix in 32 inferior grids can carry the biological sample of equal amts, but the biological sample that carries is different, and such chip can be put 1152 different biological samples.Can find out that number number of biological sample is sequentially added into, biological sample number why do not carry out randomization, be because randomization when numbering to biological sample.These nine Latin squares have following 2 differences: 1, biological sample is different; 2, residing locus is slightly different on chip.Therefore, these nine Latin squares that are not quite similar are combined, and avoid and eliminate the steric effect error with mean number, and are slightly different from real Latin square design method, but the effect that obtains will be very close, and this also is the reason that is referred to as " class Latin square design ".Certainly, the mode of 4X4 Latin square array can be by each row of transposing or each rank transformation, and 576 all 4X4 Latin square array arrangement modes have same effect.
2, the class Latin square design on the level between inferior grid
In order to illustrate that the class Latin square on the level is established between inferior grid, take following example as example:, see Fig. 5, with 16 inferior grid arrays of 16 point sample pin marks, get altogether 36 secondary pollutant samples, each biological sample repeats 4 times, but 4 are repeated no longer to be arranged in the same inferior grid, but according to Latin square design, be arranged in the different inferior grids.So, as shown below, each inferior grid has comprised 144 different biological samples, and each biological sample only has a repetition in an inferior grid.Four are repeated to be arranged in the different inferior grids.Like this, inferior grid A will comprise biological sample 1 to No. 144; Inferior grid B will comprise biological sample 145 to No. 288; Inferior grid C will comprise biological sample 289 to No. 432; Inferior grid D will comprise biological sample 433 to No. 576.And inferior grid A, B, C, D have four repetitions separately, just in time form the Latin square design dot matrix between the inferior grid of a 4X4.Like this, 144 Latin square dot matrix are just arranged on the chip, the biological sample of these 144 Latin square dot matrix is different, and locus of living in is also not exclusively the same.
As shown in Figure 6, if the area that takes full advantage of on the biochip increases biological sample quantity, can arrange Latin square design array between the inferior grid of two 4X4.So just can put the biological sample of twice quantity, namely 1152 biological samples.
As shown in Figure 7, if the area that takes full advantage of on the biochip improves analysis precision, can arrange Latin square design array between the inferior grid of two identical 4X4.Like this, the repeat number of each in 576 biological samples just can reach 8.The Latin square design array also can be arranged with different Latin square design between the inferior grid of two 4X4
As shown in Figure 8, the Latin square design array also can be arranged with different Latin square design between the inferior grid of two 4X4, and this arrangement perhaps is one and better arranges.
3, comprise simultaneously the class Latin square design on the level between the interior level of inferior grid and inferior grid
If want the precision or the accuracy that reach higher, at the biological sample comparatively small amt or to allow in the situation of enough high reticular densities might be feasible, that is exactly to adopt to comprise simultaneously in the inferior grid class Latin square design on the level between level and inferior grid.The raising of each biological sample precision or accuracy is that the quantity with biological sample is reduced to cost; So this Latin square design is suitable for the situation (for example pass through last round of screening, selected the useful biological sample of comparatively small amt) of biological sample comparatively small amt.If chip comprises Latin square design array between the inferior grid of a 4X4, each biological sample repeat to reach 16 (36 biological samples of each inferior grid, 4 repetitions of each biological sample in the inferior grid array, array has 4 inferior grids to repeat between inferior grid), at this moment a chip can only carry 144 biological samples; If chip comprises Latin square design array between the inferior grid of two 4X4, the Latin square design array comprises identical biological sample between two inferior grids, each biological sample repeat to reach 32 (36 biological samples of each inferior grid, 4 repetitions of each biological sample in the inferior grid array, array has 4 inferior grids to repeat between each inferior grid, array comprises identical biological sample between two inferior grids), at this moment a chip also can only carry 144 biological samples; If chip comprises Latin square design array between the inferior grid of two 4X4, the Latin square design array comprises different biological samples between two inferior grids, at this moment, each biological sample repeat to reach 16 (36 biological samples of each inferior grid, 4 repetitions of each biological sample in the inferior grid array, array has 4 inferior grids to repeat between each inferior grid, and array comprises different biological samples between two inferior grids), at this moment a chip can only carry 288 biological samples.Increase reticular density and can increase biological sample carrying quantity, this will decide as the case may be.The number of iterations that reduces in the inferior grid dot matrix also can increase biological sample carrying quantity, such as, with three repetitions, each inferior grid dot matrix comprises 16 3X3 Latin squares, can increase like this by 1/3rd biological sample quantity.Also can increase simultaneously reticular density and reduce biological sample repeat number in the inferior grid.Can also with different point sample needle plates, form different point needle array (inferior grid array).
3 above-mentioned class Latin square design methods can both reduce the steric effect error more or less, the principle that class Latin square design method of the present invention can reduce the steric effect error is identical with the Latin square design method of standard, that is: because Latin square design repeats to be distributed in every delegation and each row with biological sample, the mean value of these repetitions will be assimilated the steric effect error.And conventional design is owing to repeat to be placed on biological sample with delegation or same row, and these steric effect errors that are not absorbed digestion will be counted the biological sample effect, cause analytical error, make net result depart from actual value.But the class Latin square design is not the Latin square design of standard, and the amount of the steric effect error of assimilating is slightly less than the Latin square design of standard.
The steric effect error of embodiment 1, antigen protein chip Latin square design and conventional design is assimilated comparison
Present embodiment adopts the single creature sample to finish whole embodiment, and this also is unique distinction of the present invention.Adopt same biological sample, can simplify analytic statistics, make target, process, result more clear.Method according to Chatterjee has prepared the antigen protein clone bank, gets a clone from clone bank, has prepared the antigen protein biological sample (these 1152 dish Kong Sheng same clone) of 3 384 porose discs with this clone.Chatterjee M, Mohapatra S, Ionan A, Bawa G, Ali-Fehmi R, Wang X, Nowak J, Ye B, Nahhas FA, Lu K, Witkin SS, Fi shman D, Munkarah A, Morris R, Levin NK, Shirley NN, Tromp G, Abrams J, Draghici S, Tainsky MA.Diagnostic markers of ovarian cancer by high-throughput antigen cloning and detection on arrays.Cancer Res.2006; 66:1181-90. with 12 antigen protein biochips of point needle array point of 4X8, wherein, class Latin square design dot-matrix array point sample in 6 the conventional dot-matrix array aligning method of usefulness point samples, other 6 inferior grids of usefulness.These 12 blank chip are from same box chip, these 12 chips same batch with 3 identical 384 antigen proteins clones sample of making an inventory, revise computer program so that point sample sequentially is: 1st, 4,5,7,9,11 chips are with conventional dot-matrix array method point sample; 2nd, 3,6,8,10,12 chips are with class Latin square design dot-matrix array method point sample in the inferior grid.These 12 antigen protein chips are pressed method and the hybridization of same serum sample of Chatterjee.Chatterjee M, Mohapatra S, Ionan A, Bawa G, Ali-Fehmi R, Wang X, Nowak J, Ye B, Nahhas FA, Lu K, Witkin SS, Fishman D, Munkarah A, Morris R, Levin NK, Shirley NN, Tromp G, Abrams J, Draghici S, Tainsky MA.Diagnostic markers of ovarian cancer by high-throughput antigen cloning and detection on arrays.Cancer Res.2006; 66:1181-90. and with the scanning of Axon4200AL fluorescent scanning instrument, again the image file data that obtains is converted into numerical data with Imagene software.The Cy5 strength of signal of each point is divided by the strength of signal of the Cy3 data as this point.Because that is carrying in these 1152 dish holes is identical antigen protein clone, the biological sample in each hole is the same, still, in order to narrate convenience, and claims each Kong Weiyi biological sample.The steric effect error is assimilated the following parameter test of effect: 1, CV (variation coefficient) size of 4 repetitions of each sample (being actually the sample in each 384 porose disc dish hole); 2, the effect of each chip biological sample room variation size.For CV, these 4 are repeated to distribute more concentratedly, and CV is less, has assimilated fewer steric effect error; These 4 are repeated to distribute and to get overstepping the bounds of propriety loosely, and CV is larger, has assimilated more steric effect errors.For the effect variation of each chip biological sample room, because this 1152 " biological sample " all is from same antigen protein clone, is absorbed and digests fewer steric effect error, the effect variation between biological sample is just larger; Otherwise, being absorbed and digesting more steric effect errors, the effect variation between biological sample is just less.
Table 1, conventional design and class Latin square design effect
CV1
*: the CV of 4 repetitions, on average the drawing of 1152 CV values;
CV2
*: the CV between biological sample value (average 4 repetition after) calculates based on 1152 values.
The statistic analysis result of whole 12 chips shows: 1, all greater than 6 chips of conventional design, the population mean class Latin square design (0.080) of 6 chips is than conventional design (0.047) high about 70% for the mean value of the CV (variation coefficient) of 4 repetitions of whole 1152 " biological samples " of whole 6 class Latin square design chips; CV population mean class Latin square design (0.096) between 2, " biological sample " (average 4 repetition after) is than conventional design (0.127) low about 13%.
Claims (8)
1. a biochip microarray dot matrix method is characterized in that: described sample microarray dot matrix, the arrangement of employing class Latin square.
2. a kind of biochip microarray dot matrix method as claimed in claim 1 is characterized in that: described microarray dot matrix adopts the design of class Latin square array dot matrix in each inferior grid.
3. a kind of biochip microarray dot matrix method as claimed in claim 1 is characterized in that: adopt the design of class Latin square array dot matrix in the inferior grid of described microarray dot matrix between inferior grid.
4. a kind of biochip microarray dot matrix method as claimed in claim 1 is characterized in that: adopt simultaneously the design of class Latin square array dot matrix in the inferior grid of described microarray dot matrix in inferior grid and between inferior grid.
5. such as each described a kind of biochip microarray dot matrix method of claim 1-4, it is characterized in that: the array of the point in the inferior grid is n*n dot matrix, wherein n=2-1000.
6. a kind of biochip microarray dot matrix method as claimed in claim 5 is characterized in that: the array of the point in the inferior grid is n*n dot matrix, wherein n=3-20.
7. such as each described a kind of biochip microarray dot matrix method of claim 1-4, it is characterized in that: a plurality of inferior grids are lined up array, and array is n*n, wherein n=3-100.
8. such as each described a kind of biochip microarray dot matrix method of claim 1-4, it is characterized in that: described biochip comprises DNA chip, RNA chip, iRNA chip, protein chip, antibody chip, antigen chip or carbohydrate chip.
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