igv.org 的前十大競爭對手

broadinstitute.org

The Broad Institute’s mission is to understand the roots of disease and close the gap between new biological insights and impact for patients. Here’s how our research — much of it federally funded — is improving human health and accelerating biomedical discoveries.

genviz.org

There are at least three primary graphics programs available within the R environment. A package for base R graphics is installed by default and provides a simple mechanism to quickly create graphs. lattice is another graphics package that attempts to improve on base R graphics by providing better defaults and the ability to easily display multivariate relationships. In particular, the package supports the creation of trellis graphs - graphs that display a variable or the relationship between variables, conditioned on one or more other variables. Finally, ggplot2 is a graphics program based on the grammar of graphics ideology, and will be the primary focus of this course. In this module, we will explore basic use of ggplot2 to plot genomic data. For illustration, we will use a set of mutation data from Supplemental Table S5 of the paper “Recurrent somatic mutations affecting B-cell receptor signaling pathway genes in follicular lymphoma”. You can download a cleaned up version of Supplemental Table S5 at http://genomedata.org/gen-viz-workshop/intro_to_ggplot2/ggplot2ExampleData.tsv. These data come in TSV format, and consist of ~5000 lines, each with a somatic tumor genome variant and various annotations describing the variant (e.g. affected individual, predicted consequence, read counts, etc.). Introducing ggplot2 syntax ggplot is based on a system of layering graphical objects to create a final plot. We will start by installing and loading the ggplot2 library. Next, it is important to know that ggplot expects the data passed to it to be of class data.frame. After importing our data (‘ggplot2ExampleData.tsv’), we will modify this data frame to include a ‘coverage’ (tumor_COV) variable. Then we can call the variantData data frame in our ggplot() function and compare the coverage variable to the variant allele frequency (tumor_VAF). # install the ggplot2 library and load it install.packages("ggplot2") library(ggplot2) # load Supplemental Table S5 # note that in the fo

htslib.org

samtools

itol.embl.de

phylogenetic tree viewer and annotation tool

kbase.us

Developed for bench biologists and bioinformaticians, The Department of Energy Systems Biology Knowledgebase (KBase) is a software and data science platform designed to meet the grand challenge of systems biology: predicting and designing biological function.

seqanswers.com

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