Displaying 1 to 12 from 12 results

Biorezonanta Dr. Alexandru Olga 0040723347034


biorezonanta medicina bioresonance imaging scan dr. alexandru olga 0040723347034 biofeedback medical investigation with bioresonance . investigatii, diagnostic si tratament prin biorezonanta . http://www.medicinabiorezonanta.blogspot.com

ci4cc-informatics-resources - Community-maintained list of resources that the CI4CC organization and the larger cancer informatics community have found useful or are developing


This is a community-maintained list of resources that the CI4CC organization and larger cancer informatics have found useful or are developing. Contributions welcome...

Sarek - Detect germline or somatic variants from normal or tumour/normal whole-genome sequencing data


Previously known as the Cancer Analysis Workflow (CAW), Sarek is a workflow tool designed to run analyses on WGS data from regular samples or tumour / normal pairs, including relapse samples if required. It's built using Nextflow, a bioinformatics domain specific language for workflow building. Software dependencies are handled using Docker or Singularity - container technologies that provide excellent reproducibility and ease of use. Singularity has been designed specifically for high-performance computing environments. This means that although Sarek has been primarily designed for use with the Swedish UPPMAX HPC systems, it should be able to run on any system that supports these two tools.




GenomicDataCommons - Provide R access to the NCI Genomic Data Commons portal.


The National Cancer Institute's (NCI's) Genomic Data Commons (GDC) is a data sharing platform that promotes precision medicine in oncology. It is not just a database or a tool; it is an expandable knowledge network supporting the import and standardization of genomic and clinical data from cancer research programs. The GDC contains NCI-generated data from some of the largest and most comprehensive cancer genomic datasets, including The Cancer Genome Atlas (TCGA) and Therapeutically Applicable Research to Generate Effective Therapies (TARGET). For the first time, these datasets have been harmonized using a common set of bioinformatics pipelines, so that the data can be directly compared.

civic-client - Web client for CIViC: Clinical Interpretations of Variants in Cancer


Developing for CIViC involves setting up a development environment. To get started quickly, we recommend launching an AWS EC2 instance from our pre-configured and maintained AMI (getting started wiki page). Alternatively, you may set up your own local development environment using the following setup instructions.

civic-server - Backend Server for CIViC Project


This repository contains the server component of the CIViC. It is a Ruby on Rails application that serves JSON data to power the frontend website and API. Developing for CIViC involves setting up a development environment.

IARC-nf - List of IARC bioinformatics nextflow pipelines


Install java JRE if you don't already have it (7 or higher). Install nextflow.


pancancer - Building classifiers using cancer transcriptomes across 33 different cancer-types


A transcriptome can describe the total state of a tumor at a snapshot in time. In this repository, we use cancer transcriptomes from The Cancer Genome Atlas PanCancerAtlas project to interrogate gene expression states induced by deleterious mutations and copy number alterations. The code in this repository is flexible and can build a Pan-Cancer classifier for any combination of genes and cancer-types using gene expression, mutation, and copy number data. In this repository, we provide examples for building classifiers to detect aberration in TP53 and Ras signalling.

AGFusion - Python package to annotate and visualize gene fusions.


You can additionally plot the wild-type proteins and exon structures for each gene with --WT flag. By default AGFusion only plots the canonical gene isoforms, but you can tell AGFusion to include non-canonical isoform with the --noncanonical flag.

mageri - MAGERI - Assemble, align and call variants for targeted genome re-sequencing with unique molecular identifiers


Molecular tagging approach has revolutionized the field of high depth genome re-sequencing by allowing detection of ultra-rare mutations. This pipeline aims at filling the gap in software for analysis of UMI-tagged data. MAGERI implements consensus assembly, alignment and variant calling and allows to process datasets into ready SAM and VCF files in a single command. Its main purpose is to analyze targeted region genome re-sequencing data for tumor heterogeneity and circulating tumor DNA studies, however it can be also applied to other tasks that require accurate rare variant detection. See mageri-paper repository for examples and supplementary data.

datamicroarray - A collection of small-sample, high-dimensional microarray data sets to assess machine-learning algorithms and models


The R package datamicroarray provides a collection of scripts to download, process, and load small-sample, high-dimensional microarray data sets to assess machine learning algorithms and models. For each data set, we include a small set of scripts that automatically download, clean, and save the data set. Each data set is listed below by the first author on the original paper. The data sets are organized them by category; note that most of the data sets are cancer-related. Click a data set to see its description, a link to the original paper, and additional information.