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# define some colours for pretty output
NC='\033[0m'
RED='\033[0;31m'
YELLOW='\033[0;33m'
GREEN='\033[0;32m'

alias=qstatus="echo -e '${NC}----------' ;\
               echo -e '${GREEN}running:' ;\
               qstat | grep ' r ' | wc -l ;\
               echo -e '${NC}----------' ;\

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sed -i -- "s/current/replacement/g" *

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#!/usr/bin/env python3
from sys import argv
from math import factorial


def parse_fasta(in_file):
    """ return sequence from single fasta """
    seqs = [line for line in open(in_file) if not line.startswith(">")]
    return "".join(seqs).replace("\n", "")

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while read p; do qsub $p; done < to_run.txt




while read p
    do qsub $p
done < to_run.txt

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import pandas as pd
import numpy as np

def find_correlation(df, thresh=0.9):
    """
    Given a numeric pd.DataFrame, this will find highly correlated features,
    and return a list of features to remove

    params:
    - df : pd.DataFrame

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#include <iostream>
#include <algorithm>
using namespace std;

//////////////////////////////////////////////////////////////////////////////
//                        Permute array of integers                         //
//////////////////////////////////////////////////////////////////////////////


// roll your own factorial function