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[{"maxAgeSeconds": 86400, "method": ["GET"], "origin": ["https://wip.lifebit.ai/"], "responseHeader": ["Content-Type"]}]
[{"maxAgeSeconds": 86400, "method": ["GET"], "origin": ["https://staging.lifebit.ai/"], "responseHeader": ["Content-Type"]}]
[{"maxAgeSeconds": 86400, "method": ["GET"], "origin": ["https://cloudos.lifebit.ai/"], "responseHeader": ["Content-Type"]}]
We can make this file beautiful and searchable if this error is corrected: It looks like row 4 should actually have 33 columns, instead of 10. in line 3.
#CHROM POS REF ALT QUAL FILTER GENOTYPE COVERAGE FUNCTIONAL_CLASS HGVS EXOMISER_GENE CADD(>0.483) POLYPHEN(>0.956|>0.446) MUTATIONTASTER(>0.94) SIFT(<0.06) REMM DBSNP_ID MAX_FREQUENCY DBSNP_FREQUENCY EVS_EA_FREQUENCY EVS_AA_FREQUENCY EXAC_AFR_FREQ EXAC_AMR_FREQ EXAC_EAS_FREQ EXAC_FIN_FREQ EXAC_NFE_FREQ EXAC_SAS_FREQ EXAC_OTH_FREQ EXOMISER_VARIANT_SCORE EXOMISER_GENE_PHENO_SCORE EXOMISER_GENE_VARIANT_SCORE EXOMISER_GENE_COMBINED_SCORE CONTRIBUTING_VARIANT
5 54645453 G C 56.28 PASS 1/1 2 coding_transcript_intron_variant MSH3:ENST00000265081.7:c.1763+5985G>C:p.(=) MSH3 0.87123436 . . . . rs545257536 0.17211704 0.01997 . . . . . . . . . 0.8490899 0.7553215 0.8490899 0.9138005 CONTRIBUTING_VARIANT
2 54645456 C CTT 35.48 PASS 1|1 1 splice_donor_variant SPTBN1:ENST00000333896.5:c.4455_4455+1insTT:p.? SPTBN1 . . . . . . 0.0 . . . . . . . . . . 1.0 0.5294758 1.0 0.8020762 CONTRIBUTING_VARIANT
2 1789757 G GGGTTGGAGAGAGGATGCCTTTGGCA 35.48 PASS 1|1 1 splice_region_variant SPTBN1:ENST00000333896.5:c.4455+3_4455+4insGGTTGG
We can make this file beautiful and searchable if this error is corrected: No commas found in this CSV file in line 0.
json
https://gist.github.com/cgpu/5067a3a870ceb7f4f8abaec9e5e89c2b#file-sample-json
[
{
"acmg_annotation.classifications.user_explain": [
"Null variant (frame-shift), in gene FOXO6, for which loss-of-function is a known mechanism of disease (gnomAD Loss-of-Function Observed/Expected = 0.213 is less than 0.763).",
"Variant not found in gnomAD exomes (unable to check gnomAD exomes coverage).",
"Pathogenic computational verdict based on 1 pathogenic prediction from phyloP vs no benign predictions."
],
"acmg_annotation.coding_impact": "frameshift",
"acmg_annotation.gene_id": 8339,
"acmg_annotation.gene_symbol": "FOXO6",
@cgpu
cgpu / finddups.nf
Created June 16, 2021 02:05 — forked from lindenb/finddups.nf
workflow nextflow finding duplicated files and creating a bash script to replace the duplicate with a symbolic link
params.directories="."
params.headsize=100000
params.extensions="bam bai"
params.help=false
params.extrafind=""
params.lines = 1000
params.publishDir="."
def helpMessage() {
log.info"""
@cgpu
cgpu / exomiser.variants.tsv
Created June 14, 2021 06:06
Test data for exomiser
#CHROM POS REF ALT QUAL FILTER GENOTYPE HGVS COVERAGE FUNCTIONAL_CLASS EXOMISER_GENE EXOMISER_VARIANT_SCORE EXOMISER_GENE_PHENO_SCORE EXOMISER_GENE_VARIANT_SCORE EXOMISER_GENE_COMBINED_SCORE CADD(>0.483) POLYPHEN(>0.956|>0.446) MUTATIONTASTER(>0.94) SIFT(<0.06) REMM DBSNP_ID MAX_FREQUENCY DBSNP_FREQUENCY EVS_EA_FREQUENCY EVS_AA_FREQUENCY EXAC_AFR_FREQ EXAC_AMR_FREQ EXAC_EAS_FREQ EXAC_FIN_FREQ EXAC_NFE_FREQ EXAC_SAS_FREQ EXAC_OTH_FREQ CONTRIBUTING_VARIANT
1 16057247 C G 1458.03 PASS 1/1 CLCNKB:ENST00000619181.4:c.1354C>G:p.(Pro452Ala) 47 missense_variant CLCNKB 0.894 0.62300086 0.894 0.8018639 . . . 0.894 . rs1057857 0 . . . . . . . . . . CONTRIBUTING_VARIANT
@cgpu
cgpu / packer-nextflow.yaml
Created March 17, 2021 20:50 — forked from alanbchristie/packer-nextflow.yaml
An example of a Nextflow Packer file in YAML
---
# Packer machine image configuration for a Nextflow/Docker machine.
#
# To use this file (Packer expects a JSON file) you need to
# use the project's yaml2json module to convert it to JSON.
# From this directory and a Suitable Python (see root's requirements.txt)
# you can run...
#
# ../../../yaml2json.py < nextflow.yml > nextflow.json
@cgpu
cgpu / gcloud_accelarator_types.csv
Last active February 7, 2021 21:31
gcloud compute accelerator-types list | grep us-east1
name region type
nvidia-tesla-a100 us-east1-a NVIDIA Tesla A100
nvidia-tesla-k80 us-east1-a NVIDIA Tesla K80
nvidia-tesla-p100 us-east1-a NVIDIA Tesla P100
nvidia-tesla-p100-vws us-east1-a NVIDIA Tesla P100 Virtual Workstation
nvidia-tesla-p4 us-east1-a NVIDIA Tesla P4
nvidia-tesla-p4-vws us-east1-a NVIDIA Tesla P4 Virtual Workstation
nvidia-tesla-t4 us-east1-a NVIDIA Tesla T4
nvidia-tesla-t4-vws us-east1-a NVIDIA Tesla T4 Virtual Workstation
nvidia-tesla-v100 us-east1-a NVIDIA Tesla V100