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--- | |
title: "Why use KEGG?" | |
author: "Mark Ziemann" | |
date: "`r Sys.Date()`" | |
output: | |
html_document: | |
toc: true | |
toc_float: true | |
fig_width: 7 | |
fig_height: 7 |
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#!/bin/bash | |
# Download | |
URL="ftp://ftp.ensemblgenomes.org/pub/bacteria/release-42/fasta/bacteria_0_collection/escherichia_coli_str_k_12_substr_mg1655/cds/Escherichia_coli_str_k_12_substr_mg1655.ASM584v2.cds.all.fa.gz" | |
# unzip | |
if [[ ! -r $FA ]] ; then | |
wget -N $URL | |
gunzip -kf $FA.gz | |
fi |
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--- | |
title: "rslurm example workflow" | |
author: "Mark Ziemann" | |
date: "`r Sys.Date()`" | |
output: | |
html_document: | |
toc: true | |
toc_float: true | |
fig_width: 7 | |
fig_height: 7 |
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#!/bin/bash | |
x(){ | |
echo "========================================================" | |
} | |
export -f x | |
node_dash(){ | |
clear | |
echo -n "BITCOIN NODE INFO " |
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library(rvest) | |
library(dplyr) | |
url="https://www.broadinstitute.org/files/shared/metabolism/mitocarta/human.mitocarta3.0.path_.html" | |
webpage <- read_html(url) | |
tbls <- html_nodes(webpage, "table") | |
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--- | |
title: "Compare DEG tools" | |
author: "Mark Ziemann" | |
date: "`r Sys.Date()`" | |
output: | |
html_document: | |
toc: true | |
theme: cosmo | |
--- |
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--- | |
title: "Macsue proteomic/methylation mitch analysis" | |
author: "Mark Ziemann" | |
date: "`r Sys.Date()`" | |
output: | |
html_document: | |
toc: true | |
theme: cosmo | |
--- |
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# unwrap_fasta.pl | |
# https://chk.ipmb.sinica.edu.tw/wiki/doku.php/tutorials/perl/unwrap_fasta.pl | |
# Read a fasta file, unwrap the sequences | |
# (i.e., remove all extra line breaks), | |
# and save the result to an output file. | |
my $in_file = shift; | |
my $out_file = shift; | |
my %seq_hash; # key = seq_name, value = seq; | |
{ |
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# create the control data | |
IID <- paste("CTRL",1:20000,sep="") | |
ctrl <- as.data.frame(IID) | |
ctrl$GENO <- "AA" | |
ctrl[19209:19992,2] <- "AC" | |
ctrl[19993:20000,2] <- "CC" | |
ctrl$GENO <- as.factor(ctrl$GENO) | |
ctrl$PHENO <- "CONTROL" | |
# create the RA data |
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library(RColorBrewer) | |
library(gplots) | |
# Generate some random data | |
N_SAMPLES=20 | |
N_GENES=30 | |
x<- matrix(data = rnorm(600), nrow = N_GENES, ncol = N_SAMPLES) | |
rownames(x) <- paste("genes",1:N_GENES) | |
colnames(x) <- paste("sample",1:N_SAMPLES) | |
head(x) |
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