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--- | |
title: "Sequencing run summary" | |
date: "Generated on: `r Sys.Date()`" | |
output: | |
html_document: | |
toc: true | |
toc_depth: 3 | |
toc_float: true | |
self_contained: yes | |
theme: sandstone |
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#!/usr/bin/env python3 | |
#A simple script to predict gnomAD ancestry using PCA loadings trained on gnomAD V3 datasets | |
#See here for details: https://gnomad.broadinstitute.org/news/2021-09-using-the-gnomad-ancestry-principal-components-analysis-loadings-and-random-forest-classifier-on-your-dataset/ | |
#Author: Anand Mayakonda | |
import sys | |
import os.path | |
import shutil | |
import argparse |
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#!/usr/bin/env bash | |
#Script to subset a bigWig file for user specific loci | |
#MIT License (Anand Mayakonda; [email protected]) | |
function usage (){ | |
echo "Subset a bigWig file for genomic loci. | |
Requires UCSC kentutils bigWigToBedGraph and bedGraphToBigWig to be installed | |
Binaries available from: https://hgdownload.soe.ucsc.edu/admin/exe/ |
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pipeline_dir = "./" | |
echo "Downloading VEP cache.." 1>&2 | |
mkdir -p ${pipeline_dir}/resources/vep_cache/ | |
cd ${pipeline_dir}/resources/vep_cache/ | |
curl -O https://ftp.ensembl.org/pub/release-107/variation/indexed_vep_cache/homo_sapiens_vep_107_GRCh38.tar.gz | |
tar -xzf homo_sapiens_vep_107_GRCh38.tar.gz -C ./ | |
wget https://ftp.ensembl.org/pub/release-107/fasta/homo_sapiens/dna/Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz | |
gunzip -c Homo_sapiens.GRCh38.dna.primary_assembly.fa.gz | bgzip > Homo_sapiens.GRCh38.dna.primary_assembly.fa.bgzip |
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#!/usr/bin/env bash | |
#A minimal project template structure that I use for my Bioinformatic projects | |
#MIT License (Anand Mayakonda; [email protected]) | |
function usage() { | |
echo "createproject.sh - Create a project template directory structure | |
Usage: createproject.sh [option] <project_name> |
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#Wrapper around goseq | |
#'@param assayedGenes total gene IDs that were measured | |
#'@param deGenes DE gene IDs | |
#'@param source_id Can be `ensGene` or `geneSymbol` | |
#'@param hyperGeo Dfault TRUE. Set to FALSE for rna-seq data | |
goseq_wrapper = function(assayedGenes, deGenes, source_id = "ensGene", hyperGeo = TRUE){ | |
gene_vector = as.integer(assayedGenes %in% deGenes) | |
names(gene_vector)= assayedGenes | |
pwf = suppressWarnings(suppressMessages(goseq::nullp(DEgenes = gene_vector, genome = "hg19", id = source_id, plot.fit = FALSE))) |
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#################################################################################### | |
# | |
# Best-practice 450k/EPIC QC and preprocessing workflow for the PPCG project | |
# | |
# creator: Pavlo Lutsik | |
# | |
# 30.01.2021 | |
#################################################################################### | |
library(RnBeads) |
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//A minimal program to extract nucelotide counts of selected genomic loci from the BAM file | |
//gcc -g -O3 -pthread ntcounts.c -lhts -Ihts -o ntcounts | |
//MIT License | |
//Copyright (c) 2021 Anand Mayakonda <[email protected]> | |
#include <unistd.h> | |
#include <stdio.h> |
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# Get the COSMIC variant file from here: https://cancer.sanger.ac.uk/cosmic/download (for. ex: CosmicCompleteTargetedScreensMutantExport.tsv.gz) | |
# You will have to register and sign in | |
# Readin only these selected columns: `Gene name GENOMIC_MUTATION_ID Mutation AA Mutation Description Mutation genome position SNP FATHMM prediction HGVSG` | |
cosm = data.table::fread(cmd = "zcat CosmicCompleteTargetedScreensMutantExport.tsv.gz | cut -f 1,17,21,22,26,28,30,40 | sed 1d | sort -k1,2", header = FALSE) | |
csom = cosm[!V2 %in% ""] | |
csom = csom[!V4 %in% "Substitution - coding silent"] #Remove silent variants | |
csom = csom[!V4 %in% ""] #Remove vars with no sub. type variants | |
csom[, id := paste0(V2, ":", V3)] |
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