Welcome to eGPS Cloud

To get started using eGPS Cloud as quickly as possible, this tutorial shows how to use the softeware and some demos show.


BWA is a software package for mapping low-divergent sequences against a large reference genome, such as the human genome. It consists of three algorithms: BWA-backtrack, BWA-SW and BWA-MEM.

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CIRI-full is an accurate, high-throughput approach that uses both BSJ and reverse overlap (RO) features to reconstruct full-length circular RNAs from RNA-seq data sets

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MAP is an useful tool for model-based analysis of proteomic data to detect proteins with significant abundance changes between two samples.

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The XP-CLR package implements a composite likelihood method for detecting selective sweeps via the differentiation of two populations.

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You can click the application name under your application list to submit the task. For more help about how to submit a task, please visit the help tutorial here. When you successfully submit the task , you will forward to the task list page which provides the run status of the task. You can click the task name to view the result and the running time. For more help about how to monitor your task, please visit here.

A demo result URL demo


MALDmef is a powerful tool to estimate multiple-wave population admixed time, which is currently designed to infer the two-way, multiple-wave admixture based on admixture induced LD. This software can deal with genotype data, haplotype data and the data re-coded according to admixture ancestries

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iENA: individual-specific Edge-Network Analysis (iENA) with dynamical network biomarker (DNB) can be used to identify the pre-transition state of each individual in a single-sample manner. In particular, iENA can identify individual-specific biomarkers for the disease prediction, in addition to the traditional disease diagnosis.

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SSN: Sample-Specific Network (SSN) method, is a statistical method to construct individual-specific networks based on molecular expressions of a single sample. This method can characterize various human diseases at a network level. In particular, such SSNs can lead to the identification of individual-specific disease modules as well as driver genes, even without gene sequencing information.

A demo result URL demo
  • Strategic Priority Research Program of the Chinese Academy of Sciences,Grant No. XDB13000000
    Maintained by BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences.