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# After Ubuntu 16.04, Systemd becomes the default. | |
# It is simpler than https://gist.github.com/Doowon/38910829898a6624ce4ed554f082c4dd | |
[Unit] | |
Description=Jupyter Notebook | |
[Service] | |
Type=simple | |
PIDFile=/run/jupyter.pid | |
ExecStart=/home/phil/Enthought/Canopy_64bit/User/bin/jupyter-notebook --config=/home/phil/.jupyter/jupyter_notebook_config.py |
Python version of the MATLAB code in this Stack Overflow post: http://stackoverflow.com/a/18648210/97160
The example shows how to determine the best-fit plane/surface (1st or higher order polynomial) over a set of three-dimensional points.
Implemented in Python + NumPy + SciPy + matplotlib.
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# | |
# This script calculates the depth of coverage and breadth of coverage for a given bam. | |
# Outputs a dictionary containing the contig/chromosome names and the depth and breadth of coverage for each | |
# and for the entire genome. | |
# | |
# If you optionally specify the name of the mitochondrial chromosome (e.g. mtDNA, chrM, chrMT) | |
# The script will also generate breadth and depth of coverage for the nuclear genome AND the ratio | |
# of mtDNA:nuclearDNA; which can act as a proxy in some cases for mitochondrial count within an individual. | |
# | |
# Author: Daniel E. Cook |
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def splitDataFrameList(df,target_column,separator): | |
''' df = dataframe to split, | |
target_column = the column containing the values to split | |
separator = the symbol used to perform the split | |
returns: a dataframe with each entry for the target column separated, with each element moved into a new row. | |
The values in the other columns are duplicated across the newly divided rows. | |
''' | |
def splitListToRows(row,row_accumulator,target_column,separator): | |
split_row = row[target_column].split(separator) |
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pigz -d -c in.fastq.gz | | |
| awk 'BEGIN {LN=0; } { if (LN == 1 || LN == 3) { print substr($0, 0, 26) } else { print $0 } ; if (LN == 3) { LN = 0 } else { LN++ } }' \ | |
| pigz -c - > out.fastq.gz |
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# This function sorts the matrix for better visualization of mutual exclusivity across genes | |
memoSort <- function(M) { | |
geneOrder <- sort(rowSums(M), decreasing=TRUE, index.return=TRUE)$ix; | |
scoreCol <- function(x) { | |
score <- 0; | |
for(i in 1:length(x)) { | |
if(x[i]) { | |
score <- score + 2^(length(x)-i); | |
} | |
} |
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#!/usr/bin/env python3 | |
import json | |
import sys | |
def merge(inputs): | |
""" Merges the data in the given input handles and returns the result """ | |
assert len(inputs) > 1 | |
record_ids = set() |
Category | State | SGE Letter Code |
---|---|---|
Pending | pending | qw |
Pending | pending, user hold | qw |
Pending | pending, system hold | hqw |
Pending | pending, user and system hold | hqw |
Pending | pending, user hold, re-queue | hRwq |
Pending | pending, system hold, re-queue | hRwq |
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#!/usr/bin/env python3 | |
""" | |
Running this script is (intended to be) equivalent to running the following Snakefile: | |
include: "pipeline.conf" # Should be an empty file | |
shell.prefix("set -euo pipefail;") | |
rule all: | |
input: |