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.
A demo result URL
demo
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
A demo result URL
demo
MAP is an useful tool for model-based analysis of proteomic data to detect proteins with significant
abundance changes between two samples.
A demo result URL
demo
The XP-CLR package implements a composite likelihood method for detecting selective sweeps via the
differentiation of two populations.
A demo result URL
demo
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
iMAAPs 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
A demo result URL
demo
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.
A demo result URL
demo
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