gkarthik

import bjorn_support as bs
import mutations as bm
import pandas as pd


# FASTA must include reference NC_045512.2 (e.g. use cat to add the reference)
fasta_filepath = '2021-02-08_release.fa'
# specify name for output alignment
msa_filepath = 'msa.fa'
# run alignment (uses MAFFT but can be changed from bjorn_support.py)

gkarthik

import numpy as np

nentity = 100
nhidden = 20
nrelations = 10

entity_embedding = np.random.uniform(-10, 10, (nentity, nhidden))
relation_embedding = np.random.uniform(-1, 1, (nrelations, nhidden))

# For every iteration

gkarthik

from datetime import datetime ,timedelta
import sys

given_year = float(sys.argv[1])
base = datetime(int(given_year),1,1)
year_rem = given_year - int(given_year)

calc_date = (base + timedelta(seconds = (base.replace(year = base.year+1) - base).total_seconds() * year_rem ))
print(calc_date.strftime("%d %b %Y"))

gkarthik

# Naming scheme -> <samplename>_R1.fastq.gz and <samplename>_R2.fastq.gz
echo -e "forward\treverse\tsample\tsample_library" > samples.tsv
find /path/to/folder -name "*.fastq.gz" | sort | xargs -n 2 bash -c 'name=$(basename $0 | cut -f 1 -d _);echo -e "$0\t$1\t${name}\t${name}_L1"' >> samples.tsv

gkarthik

import vcf
import os
import pandas as pd
import matplotlib.pyplot as plt

def create_vcf_df(file_name):
    data = []
    csq_fields = ["impact", "aa.pos", "aa.mut", "nuc.pos", "codon.change"]
    vcf_reader = vcf.Reader(open("../data/"+file_name))
    for rec in vcf_reader:

gkarthik

const { Observable, Subject, BehaviorSubject, throwError, forkJoin, of, from, EMPTY } = require('./node_modules/rxjs');
const { map, catchError, tap, mergeMap, reduce, finalize, expand } = require("./node_modules/rxjs/operators");
const { ajax } = require('rxjs/ajax');
const {XMLHttpRequest} = require("xmlhttprequest");

function fetchAllGeneric(endpoint, qParams) {
  return fetchOne(endpoint, qParams).pipe(
    expand((data) => {
        return data.next ? fetchOne(endpoint, data.next) : EMPTY;
      }),

gkarthik

from Bio import Phylo
import datetime
from decimal import Decimal

import numpy as np

import pandas as pd

import matplotlib.gridspec as gridspec
import matplotlib.pyplot as plt

gkarthik

# Using Emacs Restclient Mode to explore the Elasticsearch REST API
# http://www.elasticsearch.org/guide/en/elasticsearch/reference/

:es = http://127.0.0.1:9200

# Cluster Health

GET :es/_cat/health?v

# List of nodes

gkarthik

# BEAST v1.8.4
# Generated Thu Feb 07 22:51:42 PST 2019 [seed=1549608699682]
# -beagle_gpu downsampled_ca.xml
state	Posterior   	Prior       	Likelihood  	downsampled_ca_7.rootHeight	downsampled_ca_6.rootHeight	downsampled_ca_5.rootHeight	downsampled_ca_3.rootHeight	downsampled_ca_1.rootHeight	shared.ucld.mean	location.clock.rate
0	-813839.4208	-30233.6058 	-783605.8150	186.311     	188.566     	386.793     	485.184     	86.8928     	1.00000     	1.00000     	-
Exception in thread "Thread-1" java.lang.ArrayIndexOutOfBoundsException: 353
	at dr.evomodel.tree.TreeModel.getNode(Unknown Source)
	at dr.app.beagle.evomodel.treelikelihood.BeagleTreeLikelihood.handleModelChangedEvent(Unknown Source)
	at dr.inference.model.AbstractModel.modelChangedEvent(Unknown Source)
	at dr.inference.model.Model$ListenerHelper.fireModelChanged(Unknown Source)

gkarthik

bases = "tcag"
codons = [a + b + c for a in bases for b in bases for c in bases]
amino_acids = 'FFLLSSSSYY**CC*WLLLLPPPPHHQQRRRRIIIMTTTTNNKKSSRRVVVVAAAADDEEGGGG'
codon_table = dict(zip(codons, amino_acids))

# To get amino acid 

codon_table['atg']