jwintersinger

# Code to optimize multi-allele tumor heterogeneity scores (MATH).
# Specifically, we modify an underlying VAF distribution by swapping points
# while maintaining a constant MAD and median, yielding a constant MATH.
using Distributions
using Random
using Statistics

using Gadfly
using Base64
import Cairo, Fontconfig

jwintersinger

# Segfault when running with `example2.txt`
# Compiled with `gcc -g -O0 project_onto_PPM.c' on GCC 7.3.0
# Kernel version: Linux nia-login01.scinet.local 3.10.0-862.14.4.el7.x86_64 #1 SMP Wed Sep 26 15:12:11 UTC 2018 x86_64 x86_64 x86_64 GNU/Linux
jawinter@nia-login01 ~/work/projectppm-problem $ ls
example1.npz  example1.py  example2.sh  example2.txt  phi_fitter_projection.py  projectppm  README.md
jawinter@nia-login01 ~/work/projectppm-problem $ ~/tmp/Efficient-Projection-onto-the-Perfect-Phylogeny-Model/a.out exam
ple2.txt out.txt 1
Segmentation fault

# Backtrace

jwintersinger

import re
import sys
import os
import argparse
import json

sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', 'lib'))
sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
import common
import inputparser

jwintersinger

#!/usr/bin/env python2
import subprocess

def move_window(oldpos, newpos):
  return subprocess.check_output(['tmux', 'move-window', '-s', str(oldpos), '-t', str(newpos)])

def main():
  output = subprocess.check_output(['tmux', 'list-windows'])
  lines = [l.strip() for l in output.split('\n') if l.strip() != '']
  frags = [line.strip().split(': ', 1) for line in output.split('\n') if line.strip() != '']

jwintersinger

from __future__ import print_function
import sys
from collections import defaultdict

def parse(fn):
 loci = set()

 with open(fn) as F:
   for L in F:
     L = L.strip()

jwintersinger

http://prune.da-shiz.net/uploads/jeff/sbf-battlefield-vietnam-world-tournament-recordings/20IDvs.sbf_-_Jun.10.mp3
http://prune.da-shiz.net/uploads/jeff/sbf-battlefield-vietnam-world-tournament-recordings/Pinc.vs.pfg_-_Apr.27.mp3

jwintersinger

Do proportion of SVs plots
See what BAF and logR are of my BP clusters that don't have SVs -- are they subclonal? Do they have smaller deviations?
  We should report these nulls back to PCAWG-6 -- now?
  Can we use our results to help PCAWG-6 -- ask them to look for non-consensus SVs that one or two methods called around our wll-supported BPs

Send list of BPs to PCAWG6, along with CN states upstream and downstream
  Send this list to group, which can check BAF and logR
  Include TRAs, but throw out small SVs

Geoff: Anything < 500 kb is often missed by CN methods for duplications or deletions

jwintersinger

function fetch_packages(db, on_done) {
  // Your code goes here. You must return an array of objects that looks like
  // this (which you can infer from looking at what fields we reference in
  // index.html):
  //
	// [ { sent_on: '2016-06-27 14:31:03',
	//     due_on: '2016-06-28 08:00:00',
	//     received_on: null,
	//     shipper_name: 'Nils Olav',
	//     receiver_name: 'William Windsor',

jwintersinger

CnvParser
  Caller: main()
    Then: grouper.add_cnvs(cn_regions)

CnvFormatter

MultisampleCnvCombiner
  Called by grouper.add_cnvs()

Segmenter

jwintersinger

These are the proportions of variants possessing features used in each question
for the various questions comprising ECE1508 assignment 1.