camillescott

dammit

a tool for easy de novo transcriptome annotation

by Camille Scott

v1.0.dev0, 2016

submodule: annotate

Dependency Check

darogan

#!/bin/bash
# Usage: deinterleave_fastq.sh < interleaved.fastq f.fastq r.fastq [compress]
# 
# Deinterleaves a FASTQ file of paired reads into two FASTQ
# files specified on the command line. Optionally GZip compresses the output
# FASTQ files using pigz if the 3rd command line argument is the word "compress"
# 
# Can deinterleave 100 million paired reads (200 million total
# reads; a 43Gbyte file), in memory (/dev/shm), in 4m15s (255s)
# 

pmelsted

#!/usr/bin/perl 

my $cmd = 'strace -e trace=mmap,munmap,brk ';
for my $arg (@ARGV) {
    $arg =~ s/'/'\\''/g;
    $cmd .= " '$arg'";
}
$cmd .= ' 2>&1 >/dev/null';
open( PIPE, "$cmd|" ) or die "Cannot execute command \"$cmd\"\n";

application2000

These commands are based on a askubuntu answer http://askubuntu.com/a/581497
To install gcc-6 (gcc-6.1.1), I had to do more stuff as shown below.
USE THOSE COMMANDS AT YOUR OWN RISK. I SHALL NOT BE RESPONSIBLE FOR ANYTHING.
ABSOLUTELY NO WARRANTY.

If you are still reading let's carry on with the code.

sudo apt-get update && \
sudo apt-get install build-essential software-properties-common -y && \
sudo add-apt-repository ppa:ubuntu-toolchain-r/test -y && \

ar0ch

#!/bin/bash
j=$(basename $1)
/usr/bin/makeblastdb -in $1 -dbtype $2 -title $j
killall sequenceserver
/usr/bin/screen -dmS ss /usr/local/bin/sequenceserver -d=/home//blast/public/blast/ -H 127.0.0.1 -p 4567 > /dev/null
exit

GDKO

Preface

This is my recommended pipeline for assembly and annotation of small eukaryotic genomes (50 - 500 Mb).

All small scripts are available at CGP-scripts. For the programs a link is provided.

Please cite if you found the pipeline useful!

kantale

#!/usr/bin/python

import sys

'''
Just a simple tool that adds the line number at
the end of each line
'''

with open(sys.argv[1]) as f_in, open(sys.argv[2], 'w') as f_out:

arundurvasula

import gzip
import csv
import argparse
import sys

parser = argparse.ArgumentParser(description="script to convert an all sites vcf to sweepfinder format. FASTA description will be the sample name in the VCF header.Only does one chromosome/region at a time.")
parser.add_argument("-v", "--vcf", action="store", required=True, help="Input VCF file. Should be a multisample vcf, though it should theoretically work with a single sample.")
parser.add_argument("-o", "--out", action="store", required=True, help="Output filename")
parser.add_argument("-c", "--chromosome", action="store", required=True, help="Chromosome to output. Should be something in the first column of the vcf.")
parser.add_argument("-g", "--gzip", action="store_true", required=False, help="Set if the VCF is gzipped.")

webbedfeet

credplot.gg <- function(d){
  # d is a data frame with 4 columns
  # d$x gives variable names
  # d$y gives center point
  # d$ylo gives lower limits
  # d$yhi gives upper limits
  require(ggplot2)
  p <- ggplot(d, aes(x=x, y=y, ymin=ylo, ymax=yhi))+
    geom_pointrange()+

macmanes

About 12% faster streaming sambamba view/sort than if using samtools..

Going from 50M raw pe reads to a sorted BAM file in 15 minutes is pretty sweet.

samtools 1.2

bwa index -p index bwa.Trinity.fasta