These instructions are intended for Linux.
- Install Miniconda 3.
- Create conda environment using the attached
environment.ymlfile:conda env create -n vep -f environment.yml - Download VEP cache and decompress the TAR archive:
| #!/bin/bash | |
| # | |
| # This script uploads your public SSH key ('id_ed25519' by default) | |
| # to the home directories of 'ec2-user' and 'ssm-user'. While both | |
| # users are configured, it's recommended to use 'ec2-user' for SSH. | |
| # Written by Bruno Grande. | |
| # | |
| # Script usage: | |
| # |
| name: docker-ci | |
| on: | |
| push: | |
| branches: [main] | |
| tags: ['v[0-9]*', '[0-9]+.[0-9]+*'] # Match tags that resemble a version | |
| workflow_dispatch: # Allow manually triggering the workflow | |
| jobs: | |
| docker-build: |
| patient,gender,status,sample,lane,fastq_1,fastq_2 | |
| S000,XX,0,S000-1234N,S000-1234N_M1,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.1.AGTTGCTT_R1_xxx.fastq.gz,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.1.AGTTGCTT_R2_xxx.fastq.gz | |
| S001,XX,0,S001-1234N,S001-1234N_M2,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.2.AGTTGCTT_R1_xxx.fastq.gz,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.2.AGTTGCTT_R2_xxx.fastq.gz | |
| S002,XX,0,S002-1234N,S002-1234N_M4,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C09DF_N_111207.4.AGTTGCTT_R1_xxx.fastq.gz,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C09DF_N_111207.4.AGTTGCTT_R2_xxx.fastq.gz | |
| S003,XX,0,S003-1234N,S003-1234N_M5,https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/n |
| S000 | XX | 0 | S000-1234N | S000-1234N_M1 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.1.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.1.AGTTGCTT_R2_xxx.fastq.gz | |
|---|---|---|---|---|---|---|---|
| S001 | XX | 0 | S001-1234N | S001-1234N_M2 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.2.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.2.AGTTGCTT_R2_xxx.fastq.gz | |
| S002 | XX | 0 | S002-1234N | S002-1234N_M4 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C09DF_N_111207.4.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C09DF_N_111207.4.AGTTGCTT_R2_xxx.fastq.gz | |
| S003 | XX | 0 | S003-1234N | S003-1234N_M5 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/D0F23_N_111212.1.AGTTGCTT_R1_xxx.fastq.gz | ht |
| S000 | XX | 0 | 1234N | 1234N_M1 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.1.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.1.AGTTGCTT_R2_xxx.fastq.gz | |
|---|---|---|---|---|---|---|---|
| S002 | XX | 0 | 1234N | 1234N_M2 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.2.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C097F_N_111207.2.AGTTGCTT_R2_xxx.fastq.gz | |
| S002 | XX | 0 | 1234N | 1234N_M4 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C09DF_N_111207.4.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/C09DF_N_111207.4.AGTTGCTT_R2_xxx.fastq.gz | |
| S003 | XX | 0 | 1234N | 1234N_M5 | https://raw.githubusercontent.com/nf-core/test-datasets/sarek/testdata/manta/normal/D0F23_N_111212.1.AGTTGCTT_R1_xxx.fastq.gz | https://raw.githubusercontent.com/nf-core/ |
| # Set up Synapse client and JSON Schema service | |
| import synapseclient | |
| syn = synapseclient.login() | |
| syn.get_available_services() # Output: ['json_schema'] | |
| js = syn.service("json_schema") | |
| # Create, manage, and delete a JSON Schema organization | |
| my_org = js.JsonSchemaOrganization("bgrande.test.new") | |
| my_org # Output: JsonSchemaOrganization(name='bgrande.test.new') | |
| my_org.create() |
| Variable | Level | |
|---|---|---|
| Something | Lorem ipsum dolor | |
| Something | Lorem ipsum dolor sit | |
| Something | Lorem ipsum dolor sit amet | |
| Something | Lorem ipsum dolor sit amet consectetur | |
| Something | Lorem ipsum dolor sit amet consectetur adipiscing |
library(ggplot2)
data <- data.frame(x = rnorm(1000, 1))
ggplot(data, aes(x)) +
geom_histogram(binwidth = 0.3, boundary = 0) +
geom_vline(xintercept = 0)| library(ggplot2) | |
| library(cowplot) # For better ggplot2 theme | |
| library(ggbeeswarm) # For geom_quasirandom() | |
| set.seed(1) | |
| data <- data.frame(value = c(rnorm(100, -1.8), rnorm(100, 1.8))) | |
| extra <- list(scale_x_discrete(labels = NULL, name = NULL), | |
| scale_y_continuous(name = NULL)) |