Omics Playground platform for Gene Expression Analysis
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Axel Martinelli
Dec 12, 2019, 6:03:40 PM12/12/19
to Bioinformatics
Hi,
I wanted to introduce a new open access platform for the analysis and visualisation of transcriptomics and proteomics data that we recently published in NAR Genomics and Bioinformatics.
The platform is designed for ease of use once installed and requires users to input four flat text files (including a raw read counts file) as input. Examples of the format are provided in the documentation.
Docker: https://hub.docker.com/r/bigomics/omicsplayground
The platform supports both bulk and single cell RNA-seq data. It can perform a wide range of analyses, including statistical comparison with Connectivity Map expression profiles. It can also intersect different algorithms to provide more stringent and reliable hits (for example, at the gene expression level it can intersect the results of up to 8 different methodologies used in EdgeR, Deseq2 and limma) . A more exhaustive list of functions is described in the documentation.
We would appreciate your feedback on the platform.
We are planning to develop an open access web-based version in the near future as well, to make the platform more accessible.
I wanted to introduce a new open access platform for the analysis and visualisation of transcriptomics and proteomics data that we recently published in NAR Genomics and Bioinformatics.
The platform is designed for ease of use once installed and requires users to input four flat text files (including a raw read counts file) as input. Examples of the format are provided in the documentation.
The platform can be installed locally on various operating systems (including Windows) via a docker file, while the source code is available on github:
Docker: https://hub.docker.com/r/bigomics/omicsplayground
The platform supports both bulk and single cell RNA-seq data. It can perform a wide range of analyses, including statistical comparison with Connectivity Map expression profiles. It can also intersect different algorithms to provide more stringent and reliable hits (for example, at the gene expression level it can intersect the results of up to 8 different methodologies used in EdgeR, Deseq2 and limma) . A more exhaustive list of functions is described in the documentation.
We also have a google group where you can contact us with questions:
Google Group: https://groups.google.com/forum/#!forum/omicsplayground
We would appreciate your feedback on the platform.
We are planning to develop an open access web-based version in the near future as well, to make the platform more accessible.
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