CN107808073A - High-flux microorganism functional gene microarray processing method and electronic equipment - Google Patents

High-flux microorganism functional gene microarray processing method and electronic equipment Download PDF

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Publication number
CN107808073A
CN107808073A CN201711046082.3A CN201711046082A CN107808073A CN 107808073 A CN107808073 A CN 107808073A CN 201711046082 A CN201711046082 A CN 201711046082A CN 107808073 A CN107808073 A CN 107808073A
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probe
subarray
value
signal
microarray
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CN107808073B (en
Inventor
石舟
周集中
杨云锋
束文圣
邓晔
叶脉
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Guangdong Meige Gene Technology Co Ltd
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Guangdong Meige Gene Technology Co Ltd
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    • GPHYSICS
    • G16INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16BBIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
    • G16B25/00ICT specially adapted for hybridisation; ICT specially adapted for gene or protein expression

Abstract

The present invention, which discloses a kind of high-flux microorganism functional gene microarray processing method and electronic equipment, method, to be included:According to the number of selected function gene probe, selection includes the minimum default specification of the number of selected function gene probe as current specifications, obtain the signal value of multiple probes in the microarray of current specifications, the microarray is divided into multiple subarrays, the probe of each subarray includes gene probe and polytype control probe, and the control probe comprises at least:Background value control probe, positive control probe, negative control probe and global control probe;Background value processing, Denoising disposal and standardization are carried out to acquired signal value.The present invention can build microarray automatically and carry out Signal Pretreatment, so as to successfully manage due to the interference of various environmental factors and manual operation suffered by high flux microarray hybridization experiment in reality, and the signal value of covered objective function gene is obtained as precisely as possible.

Description

High-flux microorganism functional gene microarray processing method and electronic equipment
Technical field
The present invention relates to environmental microorganism metagenomics and bioinformatics research field, particularly a kind of high flux is micro- Biological function gene microarray processing method and electronic equipment.
Background technology
High-flux microorganism functional gene microarray is widely used in analyzing complicated microbiologic population, and numerous studies put into practice exhibition Show that it is quantifying to detect microbial function composition, structure and contacts each side at diversity between external environmental factor It is high-effect.With molecular biology, the fast development of genomics, bioinformatics, microbial function gene microarray Flux more and more higher, at the same remain its detect it is high special possessed by microbial function, it is high sensitive, high quantization and high repeat Characteristic, it is contemplated that will persistently be played an important role in the research practice of solution analyzing soil microbial community.
High-flux microorganism functional gene microarray is needed tens of thousands of hundreds of thousands individual functional probe arrangements even up to a million On one piece of small-sized matrix slide, due in reality the experiment of high flux microarray hybridization unavoidably can by various environmental factors and The interference of manual operation, the structure of microarray can not be only that the probe random distribution elected is formed microarray, and need Abnormal conditions as more as possible are considered to ensure that hybrid experiment data are as accurate as possible and are easy to handle.Otherwise, some are small Abnormal conditions (such as experiment hybrid dna inequality) may cause subsequent treatment and analyze hard to carry on.
Firstly, since original microarray hybridization results can not generally avoid substantial amounts of noise signal, therefore the structure of microarray Build and have to consider how to set negative positive and global control probe effectively to distinguish actual signal and noise signal Come.Meanwhile the result of single microarray hybridization is likely to be influenceed by ambient impurities, so as to produce different value signal (this A little signals are typically saturated uneven).Therefore how effectively the structure of array must account for differentiates and to remove these different Value signal.Furthermore the layout of structure especially its probe of microarray has to consider that recurrent hybridization is not in experiment Uniform situation, including different microarrays may be overall higher or relatively low, and part is higher or relatively low in same microarray.Battle array The mode of the structure of row allows for being advantageous to carry out the signal value standardization inside microarray and between microarray.Reality Be so it is complicated and changeable so that micro-array construction in itself be challenge it is heavy, and further to formulate a set of flow will be whole It is even more extremely difficult, it is necessary to largely test and calculate that individual building process standardization and automation take into account subsequent result analysis simultaneously The experience of aspect could be carried out effectively.
The content of the invention
Based on this, it is necessary to test easily suffered various environmental factors for the high flux microarray hybridization of prior art And the technical problem of the interference of manual operation, there is provided a kind of high-flux microorganism functional gene microarray processing method and electronics Equipment.
The present invention provides a kind of high-flux microorganism functional gene microarray processing method, including:
According to the number of selected function gene probe, selection includes the minimum of the number of selected function gene probe and preset Specification obtains the signal value of multiple probes in the microarray of current specifications, the microarray is divided into multiple as current specifications Subarray, the probe of each subarray include gene probe and polytype control probe, and the control probe at least wraps Include:Background value control probe, positive control probe, negative control probe and global control probe;
Background value processing, Denoising disposal and standardization are carried out to acquired signal value.
Further, the control probe for each subarray, is planned in the following way:
The multiple background value control probes of random distribution;
The multiple negative control probes of random distribution;
In the multiple positive control probes of the start of line of subarray first and the distribution of footline end;
In subarray center radial probes are controlled to the multiple overall situations of corner diffusion profile.
Further, it is described to go background value to handle, specifically include:
To each subarray:
The signal value average of all background value control probes in the subarray is calculated, the background value is controlled into probe Background value of the signal value average as the subarray;
Background value of subarray, obtains each probe where the probe signals value of each probe in the subarray is subtracted into it True signal value.
Further, the Denoising disposal, is specifically included:
The signal of each probe is calculated than level of noise and value for coefficient of variation;
Calculate the signal value average of all interior negative control probes of each subarray;
Value for coefficient of variation in each subarray is marked as different value signal more than the probe of default outlier threshold and removed;
It is more than for each subarray setting signal than noise threshold, the signal than noise threshold 95% in the subarray Signal is marked as making an uproar by the signal of feminine gender control probe less than the signal than level of noise than level of noise than the probe of noise threshold Acoustical signal simultaneously removes.
Further, the standardization, is specifically included:
The signal value average of all calibrated probes in each subarray is calculated, the calibrated probe is the positive Control probe and/or the global control probe;
The signal value average of calibrated probe maximum in all subarrays is selected as standardization average;
For each subarray, the standardization average divided by the signal value average of the calibrated probe of the subarray are made For the normalization factor of the subarray;
The signal value of probe in the subarray in addition to calibrated probe is multiplied by the normalization factor and obtains standard Probe signals value after change.
The present invention provides a kind of electronic equipment, including:
At least one processor;And
The memory being connected with least one processor communication;Wherein,
The memory storage has can be by the instruction of one computing device, and the instruction is by least one place Manage device to perform, so that at least one processor can:
According to the number of selected function gene probe, selection includes the minimum of the number of selected function gene probe and preset Specification obtains the signal value of multiple probes in the microarray of current specifications, the microarray is divided into multiple as current specifications Subarray, the probe of each subarray include gene probe and polytype control probe, and the control probe at least wraps Include:Background value control probe, positive control probe, negative control probe and global control probe;
Background value processing, Denoising disposal and standardization are carried out to acquired signal value.
Further, the control probe for each subarray, is planned in the following way:
The multiple background value control probes of random distribution;
The multiple negative control probes of random distribution;
In the multiple positive control probes of the start of line of subarray first and the distribution of footline end;
In subarray center radial probes are controlled to the multiple overall situations of corner diffusion profile.
Further, it is described to go background value to handle, specifically include:
To each subarray:
The signal value average of all background value control probes in the subarray is calculated, the background value is controlled into probe Background value of the signal value average as the subarray;
Background value of subarray, obtains each probe where the probe signals value of each probe in the subarray is subtracted into it True signal value.
Further, the Denoising disposal, is specifically included:
The signal of each probe is calculated than level of noise and value for coefficient of variation;
Calculate the signal value average of all interior negative control probes of each subarray;
Value for coefficient of variation in each subarray is marked as different value signal more than the probe of default outlier threshold and removed;
It is more than for each subarray setting signal than noise threshold, the signal than noise threshold 95% in the subarray Signal is marked as making an uproar by the signal of feminine gender control probe less than the signal than level of noise than level of noise than the probe of noise threshold Acoustical signal simultaneously removes.
Further, the standardization, is specifically included:
The signal value average of all calibrated probes in each subarray is calculated, the calibrated probe is the positive Control probe and/or the global control probe;
The signal value average of calibrated probe maximum in all subarrays is selected as standardization average;
For each subarray, the standardization average divided by the signal value average of the calibrated probe of the subarray are made For the normalization factor of the subarray;
The signal value of probe in the subarray in addition to calibrated probe is multiplied by the normalization factor and obtains standard Probe signals value after change.
The present invention can build microarray automatically and carry out Signal Pretreatment, so as to successfully manage due to high flux in reality The interference of various environmental factors and manual operation suffered by microarray hybridization experiment, and obtain covered as precisely as possible Objective function gene signal value.
Brief description of the drawings
Fig. 1 is a kind of high-flux microorganism functional gene microarray processing method of the present invention;
Fig. 2 is the hardware architecture diagram of a kind of electronic equipment of the present invention.
Embodiment
The present invention will be further described in detail with specific embodiment below in conjunction with the accompanying drawings.
It is as shown in Figure 1 a kind of high-flux microorganism functional gene microarray processing method of the present invention, including:
Step S101, according to the number of selected function gene probe, selection includes the number of selected function gene probe Minimum default specification obtains the signal value of multiple probes in the microarray of current specifications, the microarray as current specifications Multiple subarrays are divided into, the probe of each subarray includes gene probe and polytype control probe, the control Probe comprises at least:Background value control probe, positive control probe, negative control probe and global control probe;
Step S102, background value processing, Denoising disposal and standardization are carried out to acquired signal value.
Specifically, the present invention presets four kinds of specifications, can accommodate altogether about 60,000,180,000,400,000 and 100 respectively Ten thousand DNA probes.Most covering comprehensive microbial function gene microarray in the world about includes 160,000 functional genes at present Probe, therefore the default specification of the present embodiment can be in a very long time in future still meet demand.Then, according to selected work( The number of energy gene probe, the present embodiment will select default specification automatically as micro-array construction carrier.It is if for example, constructed Microarray need to include the probe of 50,000 or so, then 60,000 default specifications will be chosen automatically;If array needs to include 100000 probes, then 180,000 default specifications will be selected.And then, for the microarray of each different size, journey Automatic virtualization is partitioned into the subarray of varying number, containing about 250 probes of each subarray by sequence.So 60,000 default specifications 240 subarrays will be included altogether, 180,000 default specifications will include 720 subarrays altogether, and 400,000 default specifications will be total Include 1600 subarrays altogether, 1,000,000 default specifications will include 4000 subarrays altogether.
Background value control probe uses the negative control probes of Agilent;Feminine gender control probe is derived from eight unusual rings Very rare thermophilic bacteria strain in border;Positive control probe uses 16S conservative regions;Overall situation control probe is then COR Universal probes.
The present invention can build microarray automatically and carry out Signal Pretreatment, so as to successfully manage due to high flux in reality The interference of various environmental factors and manual operation suffered by microarray hybridization experiment, and obtain covered as precisely as possible Objective function gene signal value.
In one of the embodiments, the control probe for each subarray, is planned in the following way:
The multiple background value control probes of random distribution;
The multiple negative control probes of random distribution;
In the multiple positive control probes of the start of line of subarray first and the distribution of footline end;
In subarray center radial probes are controlled to the multiple overall situations of corner diffusion profile.
Specifically, in each subarray, in addition to functional gene probe, automatic planning is made it to comprise at least by program Four kinds of different control probes, including background value control probe, positive control probe, feminine gender control probe and global control are visited Pin.Wherein background value control probe (2 to 3) and negative control probe (8 to 10) random distribution, positive control probe (16 It is individual) be located at the start of line of subarray first (8) and footline end (8), overall situation control probe (5) positioned at subarray center into It is radial to be spread to corner.
The present embodiment has used the division of subarray, processing mode at least two benefits of this refinement.It is first, every Every signal value processing of one probe can be carried out based on the control probe in subarray, because miscellaneous suffered by closely located probe The actual conditions influence of friendship is relatively similar, so it is possible to prevente effectively from the signal value of probe is handled by the control probe of hypertelorism Influence, so as to improve the accuracy of pretreatment.Second, it is possible that local higher or inclined in same microarray in crossover process Low situation, and by dividing subarray and setting control pointer can be extremely effective in the identical relative position of each subarray Ground standardizes the signal value in same microarray, and the standardization of signal value provides a more accurately basis between microarray.
In one of the embodiments, it is described to go background value to handle, specifically include:
To each subarray:
The signal value average of all background value control probes in the subarray is calculated, the background value is controlled into probe Background value of the signal value average as the subarray;
Background value of subarray, obtains each probe where the probe signals value of each probe in the subarray is subtracted into it True signal value.
The present embodiment is the calculating of the true signal value of single subarray background value and probe.The present invention is in each submatrix In row, the signal value average of background value control probe is calculated, and using the signal value average as each spy in the subarray The background value of pin.Then, the Part Methods will calculate the true signal value of each probe, and calculation is the probe signals The background value of subarray where value subtracts it.
The present embodiment employs the special environment value and controls probe as static background value, so as to be advantageous to calculate each spy The true signal value of pin, it is not easily susceptible to the influence of sample DNA concentration difference.
In one of the embodiments, the Denoising disposal, is specifically included:
The signal of each probe is calculated than level of noise and value for coefficient of variation;
Calculate the signal value average of all interior negative control probes of each subarray;
Value for coefficient of variation in each subarray is marked as different value signal more than the probe of default outlier threshold and removed;
Signal in each subarray is marked as noise signal less than preset signals than level of noise than the probe of noise threshold And remove or negative control probe to have normal signal be the automatic setting signal of standard than level of noise threshold must not exceed 10% Value.
The present embodiment is the different value processing of Microarray signals and denoising.Specifically, the signal of each probe is calculated Than level of noise and value for coefficient of variation, and feminine gender controls the average of probe in each subarray, and whole array signal is entered The different value processing of row and denoising.Different value processing is based primarily upon value for coefficient of variation, if the value for coefficient of variation of some probe exceedes 0.8, then it will be marked as different value signal and be removed.Denoising is more negative than in level of noise and subarray by basis signal The average combination of probe is controlled to carry out.The present invention can both set a default experience signal than noise threshold (generally 2) with All probes less than the threshold value are marked as noise signal and are removed, can also must not exceed 5% negative control probe has normally Signal is that the next automatic setting signal of standard compares noise threshold.
The present embodiment controls probe by calculating probe signals than level of noise and value for coefficient of variation, and using negative, should Method not only can effectively remove different value signal and effectively actual signal and microarray hybridization experiment can not generally can also be kept away Exempt from substantial amounts of noise signal to make a distinction.
In one of the embodiments, the standardization, is specifically included:
The signal value average of all calibrated probes in each subarray is calculated, the calibrated probe is the positive Control probe and/or the global control probe;
The signal value average of calibrated probe maximum in all subarrays is selected as standardization average;
For each subarray, the standardization average divided by the signal value average of the calibrated probe of the subarray are made For the normalization factor of the subarray;
The signal value of probe in the subarray in addition to calibrated probe is multiplied by the normalization factor and obtains standard Probe signals value after change.
The present embodiment is that signal value standardizes between the standardization of overall signal value and microarray inside microarray.Calculate each The positive average for controlling probe and global control probe in subarray, so as between microarray inside overall signal value and microarray Signal value standardization not only can be based on the former average but also can be based on the latter or the combination of the two.It is comprised the following steps that:It is first Positive control probe or global control probe average highest one are first found from all subarrays.Then, calculate each Normalization factor corresponding to individual subarray, computational methods be with the positive control probe of highest or global control probe average divided by The positive control probe of this subarray or global control probe average.Then, the standardization drawn by being multiplied by previous step The factor is with the overall signal value for lifting each subarray.Finally, if handling multiple microarrays simultaneously, this method will be entered automatically Signal value standardizes between row microarray, and its specific method and phase on the methodological principle of microarray inside overall signal value standardization Together.During implementation, each microarray is by the subarray in corresponding microarray internal normalization, and the positive in each microarray The average of control probe and global control probe will act as the key value of signal value standardization.
The present embodiment is worked along both lines using positive control probe and global control probe, so as to frequent in micro- experiment The uneven situation of the microarray hybridization of generation is normalized into same level and is compared so that analysis result is more accurate.
The hardware architecture diagram of a kind of electronic equipment of the present invention is illustrated in figure 2, including:
At least one processor 201;And
The memory 202 communicated to connect with least one processor 201;Wherein,
The memory 202 is stored with can be by the instruction of one computing device, and the instruction is by described at least one Individual processor 201 performs, so that at least one processor 201 can:
According to the number of selected function gene probe, selection includes the minimum of the number of selected function gene probe and preset Specification obtains the signal value of multiple probes in the microarray of current specifications, the microarray is divided into multiple as current specifications Subarray, the probe of each subarray include gene probe and polytype control probe, and the control probe at least wraps Include:Background value control probe, positive control probe, negative control probe and global control probe;
Background value processing, Denoising disposal and standardization are carried out to acquired signal value.
In Fig. 2 by taking a processor 202 as an example.
Server can also include:Input unit 203 and output device 204.
Processor 201, memory 202, input unit 203 and display device 204 can pass through bus or other modes Connect, in figure exemplified by being connected by bus.
Memory 202 is used as a kind of non-volatile computer readable storage medium storing program for executing, available for storage non-volatile software journey Sequence, non-volatile computer executable program and module, as the high-flux microorganism functional gene in the embodiment of the present application is micro- Programmed instruction/module corresponding to array processing method, for example, the method flow shown in Fig. 1.Processor 201 is stored by running Non-volatile software program, instruction and module in memory 202, so as to perform at various function application and data Reason, that is, realize the high-flux microorganism functional gene microarray processing method in above-described embodiment.
Memory 202 can include storing program area and storage data field, wherein, storing program area can store operation system Application program required for system, at least one function;Storage data field can be stored according to the micro- battle array of high-flux microorganism functional gene Column processing method uses created data etc..In addition, memory 202 can include high-speed random access memory, may be used also With including nonvolatile memory, a for example, at least disk memory, flush memory device or the storage of other nonvolatile solid states Device.In certain embodiments, memory 202 is optional including relative to the remotely located memory of processor 201, these are long-range Memory can pass through network connection to the device for performing high-flux microorganism functional gene microarray processing method.Above-mentioned network Example include but is not limited to internet, intranet, LAN, mobile radio communication and combinations thereof.
The user that input unit 203 can receive input clicks on, and produces and high-flux microorganism functional gene microarray The signal input that the user of processing method is set and function control is relevant.Display device 204 may include that the displays such as display screen are set It is standby.
It is stored in one or more of modules in the memory 202, when by one or more of processing When device 201 is run, the high-flux microorganism functional gene microarray processing method in above-mentioned any means embodiment is performed.
In one of the embodiments, the control probe for each subarray, is planned in the following way:
The multiple background value control probes of random distribution;
The multiple negative control probes of random distribution;
In the multiple positive control probes of the start of line of subarray first and the distribution of footline end;
In subarray center radial probes are controlled to the multiple overall situations of corner diffusion profile.
In one of the embodiments, it is described to go background value to handle, specifically include:
To each subarray:
The signal value average of all background value control probes in the subarray is calculated, the background value is controlled into probe Background value of the signal value average as the subarray;
Background value of subarray, obtains each probe where the probe signals value of each probe in the subarray is subtracted into it True signal value.
In one of the embodiments, the Denoising disposal, is specifically included:
The signal of each probe is calculated than level of noise and value for coefficient of variation;
Calculate the signal value average of all interior negative control probes of each subarray;
Value for coefficient of variation in each subarray is marked as different value signal more than the probe of default outlier threshold and removed;
It is more than for each subarray setting signal than noise threshold, the signal than noise threshold 95% in the subarray Signal is marked as making an uproar by the signal of feminine gender control probe less than the signal than level of noise than level of noise than the probe of noise threshold Acoustical signal simultaneously removes.
In one of the embodiments, the standardization, is specifically included:
The signal value average of all calibrated probes in each subarray is calculated, the calibrated probe is the positive Control probe and/or the global control probe;
The signal value average of calibrated probe maximum in all subarrays is selected as standardization average;
For each subarray, the standardization average divided by the signal value average of the calibrated probe of the subarray are made For the normalization factor of the subarray;
The signal value of probe in the subarray in addition to calibrated probe is multiplied by the normalization factor and obtains standard Probe signals value after change.
Embodiment described above only expresses the several embodiments of the present invention, and its description is more specific and detailed, but simultaneously Therefore the limitation to the scope of the claims of the present invention can not be interpreted as.It should be pointed out that for one of ordinary skill in the art For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to the guarantor of the present invention Protect scope.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.

Claims (10)

  1. A kind of 1. high-flux microorganism functional gene microarray processing method, it is characterised in that including:
    According to the number of selected function gene probe, selection includes the minimum default specification of the number of selected function gene probe As current specifications, the signal value of multiple probes in the microarray of current specifications is obtained, the microarray is divided into multiple submatrixs Row, the probe of each subarray include gene probe and polytype control probe, and the control probe comprises at least: Background value control probe, positive control probe, negative control probe and global control probe;
    Background value processing, Denoising disposal and standardization are carried out to acquired signal value.
  2. 2. high-flux microorganism functional gene microarray processing method according to claim 1, it is characterised in that for every The control probe of individual subarray, is planned in the following way:
    The multiple background value control probes of random distribution;
    The multiple negative control probes of random distribution;
    In the multiple positive control probes of the start of line of subarray first and the distribution of footline end;
    In subarray center radial probes are controlled to the multiple overall situations of corner diffusion profile.
  3. 3. high-flux microorganism functional gene microarray processing method according to claim 1, it is characterised in that described to go Background value processing, is specifically included:
    To each subarray:
    The signal value average of all background value control probes in the subarray is calculated, the background value is controlled to the letter of probe Number background value of the value average as the subarray;
    Background value of subarray, obtains the true of each probe where the probe signals value of each probe in the subarray is subtracted into it Real signal value.
  4. 4. high-flux microorganism functional gene microarray processing method according to claim 1, it is characterised in that described to go Noise processed, specifically include:
    The signal of each probe is calculated than level of noise and value for coefficient of variation;
    Calculate the signal value average of all interior negative control probes of each subarray;
    Value for coefficient of variation in each subarray is marked as different value signal more than the probe of default outlier threshold and removed;
    It is more than in the subarray 95% feminine gender than noise threshold than noise threshold, the signal for each subarray setting signal Control the signal of probe that signal is marked as into noise letter than the probe of noise threshold less than the signal than level of noise than level of noise Number and remove.
  5. 5. high-flux microorganism functional gene microarray processing method according to claim 1, it is characterised in that the mark Quasi-ization processing, is specifically included:
    The signal value average of all calibrated probes in each subarray is calculated, the calibrated probe is the positive control Probe and/or the global control probe;
    The signal value average of calibrated probe maximum in all subarrays is selected as standardization average;
    For each subarray, the standardization average divided by the signal value average of the calibrated probe of the subarray are regard as this The normalization factor of subarray;
    The signal value of probe in the subarray in addition to calibrated probe is multiplied by after the normalization factor obtains standardization Probe signals value.
  6. 6. a kind of electronic equipment, it is characterised in that including:
    At least one processor;And
    The memory being connected with least one processor communication;Wherein,
    The memory storage has can be by the instruction of one computing device, and the instruction is by least one processor Perform, so that at least one processor can:
    According to the number of selected function gene probe, selection includes the minimum default specification of the number of selected function gene probe As current specifications, the signal value of multiple probes in the microarray of current specifications is obtained, the microarray is divided into multiple submatrixs Row, the probe of each subarray include gene probe and polytype control probe, and the control probe comprises at least: Background value control probe, positive control probe, negative control probe and global control probe;
    Background value processing, Denoising disposal and standardization are carried out to acquired signal value.
  7. 7. electronic equipment according to claim 6, it is characterised in that the control probe for each subarray, using such as Under type is planned:
    The multiple background value control probes of random distribution;
    The multiple negative control probes of random distribution;
    In the multiple positive control probes of the start of line of subarray first and the distribution of footline end;
    In subarray center radial probes are controlled to the multiple overall situations of corner diffusion profile.
  8. 8. electronic equipment according to claim 6, it is characterised in that it is described to go background value to handle, specifically include:
    To each subarray:
    The signal value average of all background value control probes in the subarray is calculated, the background value is controlled to the letter of probe Number background value of the value average as the subarray;
    Background value of subarray, obtains the true of each probe where the probe signals value of each probe in the subarray is subtracted into it Real signal value.
  9. 9. electronic equipment according to claim 6, it is characterised in that Denoising disposal, specifically include:
    The signal of each probe is calculated than level of noise and value for coefficient of variation;
    Calculate the signal value average of all interior negative control probes of each subarray;
    Value for coefficient of variation in each subarray is marked as different value signal more than the probe of default outlier threshold and removed;
    It is more than in the subarray 95% feminine gender than noise threshold than noise threshold, the signal for each subarray setting signal Control the signal of probe that signal is marked as into noise letter than the probe of noise threshold less than the signal than level of noise than level of noise Number and remove.
  10. 10. electronic equipment according to claim 6, it is characterised in that the standardization, specifically include:
    The signal value average of all calibrated probes in each subarray is calculated, the calibrated probe is the positive control Probe and/or the global control probe;
    The signal value average of calibrated probe maximum in all subarrays is selected as standardization average;
    For each subarray, the standardization average divided by the signal value average of the calibrated probe of the subarray are regard as this The normalization factor of subarray;
    The signal value of probe in the subarray in addition to calibrated probe is multiplied by after the normalization factor obtains standardization Probe signals value.
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Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2004044700A2 (en) * 2002-11-12 2004-05-27 Affymetrix, Inc. Methods, compositions and computer software products for interrogating sequence variations in functional genomic regions
WO2005001123A1 (en) * 2003-06-30 2005-01-06 Tsinghua University Dna chip based genetic typing
CN1606695A (en) * 2001-12-21 2005-04-13 阿菲梅特里克斯公司 High throughput resequencing and variation detection using high density microarrays
CN1645136A (en) * 2005-01-11 2005-07-27 中国人民解放军第三军医大学野战外科研究所 Two-dimensional coding marking method for biological chip
CN1688716A (en) * 2002-06-28 2005-10-26 罗斯塔英法美蒂克斯有限责任公司 Methods to assess quality of microarrays
CN101206216A (en) * 2006-12-20 2008-06-25 三星电子株式会社 Oligomer probe array chip, related mask and analysis method
CN101935699A (en) * 2009-06-30 2011-01-05 希森美康株式会社 Methods for detecting nucleic acid with microarray and microarray data analysis apparatus
CN102534013A (en) * 2012-01-18 2012-07-04 李越希 Gene chip for high-flux detection of pathogens and application thereof

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1606695A (en) * 2001-12-21 2005-04-13 阿菲梅特里克斯公司 High throughput resequencing and variation detection using high density microarrays
CN1688716A (en) * 2002-06-28 2005-10-26 罗斯塔英法美蒂克斯有限责任公司 Methods to assess quality of microarrays
WO2004044700A2 (en) * 2002-11-12 2004-05-27 Affymetrix, Inc. Methods, compositions and computer software products for interrogating sequence variations in functional genomic regions
WO2005001123A1 (en) * 2003-06-30 2005-01-06 Tsinghua University Dna chip based genetic typing
CN1645136A (en) * 2005-01-11 2005-07-27 中国人民解放军第三军医大学野战外科研究所 Two-dimensional coding marking method for biological chip
CN101206216A (en) * 2006-12-20 2008-06-25 三星电子株式会社 Oligomer probe array chip, related mask and analysis method
CN101935699A (en) * 2009-06-30 2011-01-05 希森美康株式会社 Methods for detecting nucleic acid with microarray and microarray data analysis apparatus
CN102534013A (en) * 2012-01-18 2012-07-04 李越希 Gene chip for high-flux detection of pathogens and application thereof

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