EN
123 Scheme introduction


What is gene cloud analysis solution?

Scale sequencing (the second generation sequencing, next-generation sequencing, NGS) technology is mature gradually, One time can be measured in millions to tens of millions of short nucleotide sequences, but dealing with the mass sequence results has become a problem.

As for sequencing analysis results, there are lots of problems all the time such as long-standing results show low rate, false positives more than false negatives, and measured results of different instruments are difficult to reproduce, so much so that Nature published review with words: "Most of the results based on sequencing cannot be verified, repeat, adopted or educated, resulting in an extremely urgent repeatable crisis ".

Nowadays due to the standard of the sequencing instruments and experimental process, the key of the above-mentioned problem is the data analysis.\

  1.  The existing algorithms are poor in accuracy, robustness and repeatability;
  2.  The software is complex, set up is complex, it is very difficult for many biologists to use;
  3.  The large amount of calculation and demands high performance computer are unbearable for
  ordinary laboratory;
  4.  Standardisation is poor, the results between different sequencing batch does not have the
  comparability and be unable to verify.

No professional project planning and strategy design, the project will be killed off by the experts easily, so hard for several months.

Now the situation is over! Professionals will help you the project plan at the outset, save your precious time, energy, money and samples, with the highest cost-effectiveness ratio and cost-time to achieve your research purpose.



What is gene cloud analysis solution?

Eight major advantages of FANSe2 algorithm:

1.  High precision. Error rate below one over one million, almost guarantee 100% accuracy in practical application cases.

2.  Strong robustness. Error rate can be calculated in advance before estimates, making it easy for users to adjust the appropriate parameters to achieve the precision of the actual demand. The precision of other algorithms cannot effectively estimate, and the difference of different data sets and species is remarkable.

3.  Strong fault tolerance. Response to 12% of the sequencing error rate or sequence variation perfectly. For higher sequencing error rates (up to 20% or more) or variation degree, we can deal with successive progressive method perfectly. Traditional algorithm will lost accuracy when sequencing error rate or sequence variation degrees reach 2%, if 4% that most algorithms has been completely lose the practical significance. However, sequencing error rate of numerous sequencing machines is as high as 2-4%, some even as high as 13%.

4.  Verifiable results. Related papers have published a series of experimental test results, all demonstrate the validity of the FANSe2 analysis results, there is no false positive or false negative. So far, just reported experiment alone have verified hundreds of gene expression quantitative condition and thousands of mutations identified condition, experimental verification results (either quantitative or qualitative) is identical with both FANSe2 analysis results, even no one mistake. While the false positive rate and false negative rate of the other algorithms is relatively higher than FANSe2

5.  Reduce the cost of sequencing dramatically. The human proteome project has proved that FANSe2 need only 100M base sequencing flux to accurate quantitative more than 11000 genes in human cells, while the traditional algorithm need to 2~4g bases, so the sequencing cost can save 50~100 times. For the key pathway node gene of tumor, sequencing flux can reduce 10 times again.

6.  Compatible with all kinds of sequenator. For the sequencing data from different manufacturers or different models of the market sales sequenator, the traditional algorithm can’t to deal with. However, the accuracy of FANSe2 is very high, and it is not sensitive to the manufacturer and model of sequenator, so it can deal with the data of different sequenator, and it is convenient to do a long-term research and the integration of other data.

7.  Can be corresponding to the gene chip data. The sequencing data processed by the traditional method could not correspond to the gene chip, which makes the previous research results based on gene chip can not be used. And now using the FANSe2 algorithm to deal with the sequencing data, you can linear corresponding with the gene chip data, then make use of the data.

8.  Can effectively deal with non model species. For example, various clinical isolates, animal infectious specimens, organism with no genome, etc..

Six major advantages of the cloud platform:

1.   Quick Analysis. In the high performance server and super computer platform to complete the analysis, the speed is far faster than the single computer analysis.

2.  Simple Operation. In the visual interface, just click the mouse to complete the original complex parameter setting. Most of the parameters are automatically generated, and you can complete the whole process easily with no need for professional background.

3.  Strong Scalability. On the basis of the existing basic analysis module and advanced module, We will constantly develop more and more powerful application module according to scientific research and practical needs. Existing algorithms and reference libraries will continue to optimize.

4.  Save Hardware and Bandwidth Costs. Only on the most common PC machine running on the client, you can complete the complexity data analysis which have high requirement of operation performance, and do not need to purchase high performance hardware equipment. Cloud platform uses the efficient compression algorithm, as for as possible to save the user's bandwidth usage.

5.  Analysis Process Automation. After data analysis request is submitted, the whole analysis process (which may be used in multiple computing modules) can be automatically completed by itself, and provide a good result for download at any time.

6.  Batch Analysis. Cloud platform provide batch upload, batch setting, batch analysis and other functions for data, to meet the needs of the use of large amounts of data for gene sequencing companies, large scientific research or medical projects, and also save time and manpower for all users.