RTPEA is a public database hosting data and results of RetroMiner. There are interactive exploratory components as well as an API to retrieve this data.
RetroMiner uses unbiased proteomic approaches to reanalyse publicly available PRIDE datasets to detect and identify retroelement proteins (see GitHub href).
This helps build a picture of where RT proteins are being expressed from across various tissues and diseases. The aim of this is to contribute towards the understanding of the biological role of retroelements (Brancolab href - https://sites.google.com/site/brancolaboratory/home).
Making these results available via RTPEA allows other researchers to explore the proteomics of RT or branch out to carry out potential further downstream analysis.
The following tabs are the sections on the top of the page allowing users to navigate through the various components of the website.
Home: -Explore the human atlas to view the data available for a highlighted tissue
Browse: -Search the dataset by id, study, tissue or disease
Visualise: - Using Protvista, a viewer for protein sequence features, visualise protein level information
API: -Retrieve data programmatically located on the database for a specific ID
Info: - Further details on the background and technical aspects of RTPEA
Contact Us: -Reach out to us for bugs, suggestions, any features you’d like to see or any specific requests you have
RTPEA is also dedicated to displaying experimental parameters and proteomic metadata for free to use for anyone interested in PRIDE datasets!
This website will also host proteomic data (not just RT data) for these datasets thus be accessible to all types of biologists looking at protein identifications of PRIDE and will allow them to download these in the standard mzIdentML format.
Repetitive DNA accounts for almost half of our genome many of which were composed of retrotransposons that have lost their ability to jump around. Retrotransposons are RNA based mobile genetic elements which have the ability to duplicate themselves in the genome and are thus are found in many locations in eukaryotic genomes.
The most commonly found example is LINE-1, which accounts for almost 17% of the human genome. LINE-1 produces the proteins ORF1p, ORF2p and the recently discovered ORF0 in order to carry out retrotransposition. By mining public proteomic data, we tried to find in which samples these proteins could be identified from in Mass spectrometry-based proteomic experiments.
We also predicted genetic variants of LINE-1 proteins from the human reference genome (hg38) and in silico translated them to protein sequences and appended these to the proteomic search database for protein identification.
The results of these analyses can be found under the various navigation tabs of RTPEA.
Information box
ON HOVER MODE:
Hovering over each tissue changes the bar chart. By default, it displays the metrics for the total database
ON CLICK MODE:
You can select each tissue without the bar charts changing when moved away.
You can also click the graph to transfer you to the table to view the datasets for the tissue type selected.
Below atlas
RTPEA is a public database hosting data and results of RetroMiner. There are interactive exploratory components as well as an API to retrieve this data.
RetroMiner uses unbiased proteomic approaches to reanalyse publicly available PRIDE datasets to detect and identify retroelement proteins (see GitHub href). This helps build a picture of where RT proteins are being expressed from across various tissues and diseases. The aim of this is to contribute towards the understanding of the biological role of retroelements (Brancolab href - https://sites.google.com/site/brancolaboratory/home).
Making these results available via RTPEA allows other researchers to explore the proteomics of RT or branch out to carry out potential further downstream analysis.
The following tabs are the sections on the top of the page allowing users to navigate through the various components of the website.
Home: -Explore the human atlas to view the data available for a highlighted tissue Browse: -Search the dataset by id, study, tissue or disease Visualise: - Using Protvista, a viewer for protein sequence features, visualise protein level information API: -Retrieve data programmatically located on the database for a specific ID Info: - Further details on the background and technical aspects of RTPEA Contact Us: -Reach out to us for bugs, suggestions, any features you’d like to see or any specific requests you have
RTPEA is also dedicated to displaying experimental parameters and proteomic metadata for free to use for anyone interested in PRIDE datasets!
This website will also host proteomic data (not just RT data) for these datasets thus be accessible to all types of biologists looking at protein identifications of PRIDE and will allow them to download these in the standard mzIdentML format.
Repetitive DNA accounts for almost half of our genome many of which were composed of retrotransposons that have lost their ability to jump around. Retrotransposons are RNA based mobile genetic elements which have the ability to duplicate themselves in the genome and are thus are found in many locations in eukaryotic genomes.
The most commonly found example is LINE-1, which accounts for almost 17% of the human genome. LINE-1 produces the proteins ORF1p, ORF2p and the recently discovered ORF0 in order to carry out retrotransposition. By mining public proteomic data, we tried to find in which samples these proteins could be identified from in Mass spectrometry-based proteomic experiments.
We also predicted genetic variants of LINE-1 proteins from the human reference genome (hg38) and in silico translated them to protein sequences and appended these to the proteomic search database for protein identification.
The results of these analyses can be found under the various navigation tabs of RTPEA.
Information box
ON HOVER MODE: Hovering over each tissue changes the bar chart. By default, it displays the metrics for the total database
ON CLICK MODE: You can select each tissue without the bar charts changing when moved away.
You can also click the graph to transfer you to the table to view the datasets for the tissue type selected.