| Traceback (most recent call last): | |
| File "pymcjointModel.py", line 148, in <module> | |
| estimateBayesFactor(Data_and_Disp) | |
| File "pymcjointModel.py", line 135, in estimateBayesFactor | |
| H_0, H_1, H_2, H_3 = run_pymc(x_u_r1,y_u_r1,x_t_r1,y_t_r1,r_1,r_2) | |
| File "pymcjointModel.py", line 112, in run_pymc | |
| step = Metropolis() | |
| File "/usr/local/lib/python2.7/dist-packages/pymc3/step_methods/arraystep.py", line 60, in __new__ | |
| step.__init__([var], *args, **kwargs) | |
| File "/usr/local/lib/python2.7/dist-packages/pymc3/step_methods/metropolis.py", line 98, in __init__ |
| a = [1,4,5,10] | |
| cache = {} | |
| for i in a: | |
| cache[i] = 1 | |
| counter = 0 | |
| #okay khub bhalo code hoyeche | |
| def coin(x): | |
| if not x in cache: |
| import argparse | |
| default_prefix = "ftp.sra.ebi.ac.uk/vol1/fastq/" | |
| ascp_prefix = "ftp.sra.ebi.ac.uk:/vol1/fastq/" | |
| default_protocol = "ftp://" | |
| default_suffix = "*.fastq.gz" | |
| default_ascp_line = "ascp -QT -l 300m -i ~/.ssh/asperaweb_id_dsa.openssh anonftp@ftp.ncbi.nlm.nih.gov:{} {}" | |
| def prepare_url(srr_name, prefix): |
SAM and BAM filtering one-liners
@author: David Fredman, david.fredmanAAAAAA@gmail.com (sans poly-A tail)
@dependencies: http://sourceforge.net/projects/bamtools/ and http://samtools.sourceforge.net/
Please extend with additional/faster/better solutions via a pull request!
BWA mapping (using piping for minimal disk I/O)
| #!/bin/bash | |
| #################################### | |
| USAGE: bash auto_sub.sh <QUEUE_LIM> <MAX_JOB_NUM> | |
| ################################### | |
| USER="$(whoami)" | |
| MAX_LIMIT=$1 | |
| MAX_JOB_NUM=$2 |
| from collections import deque | |
| import itertools | |
| # Make dictionary of triplets | |
| i = 0 | |
| triplet_index = {} | |
| inverse_triplet = {} | |
| for x in list(itertools.product(['A','T','G','C'], repeat=3)): | |
| triplet_index[''.join(x)] = i | |
| inverse_triplet[i] = ''.join(x) |
| #From stackoverflow | |
| def get_merged_intervals(intervals): | |
| sorted_by_lower_bound = sorted(intervals, key=lambda tup: tup[0]) | |
| merged = [] | |
| for higher in sorted_by_lower_bound: | |
| if not merged: | |
| merged.append(higher) | |
| else: | |
| lower = merged[-1] |
| #include <iostream> | |
| #include <fstream> | |
| #include <sstream> | |
| #include <functional> | |
| #include <sys/stat.h> | |
| #include <memory> | |
| #include <vector> | |
| #include <numeric> | |
| #include "zstr.hpp" |