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The MIT License (MIT) Copyright (c) 2015 Joseph Paggi Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. ######################################################### This module can be invoked using either the command line or by importing this module directly. ######################################################### To use via command line, use the following command: python <reads> <output> <bowtie_options> <motif> <length> <threshold> <strand> Where arguments are defined as follows: reads: path to file where single-end, stranded RNA-seq reads in fastq format are located output: desired basename of output files bowtie_options: bowtie options you wish to be used for alignment of reads after splitting. See the bowtie manual for details. Recommend "-y -p 2 -v 0 -X 5000 -m 1 <index>" MUST BE PUT IN QUOTES motif: list of dictionaries representing 5'ss motif position weight matrix. Each dictionary has a key for each nucleotide, with a float of the probability as keys. Write in PYTHON format and PUT IN QUOTES. length: lowest acceptable number of bases used to align a fragment of a read. threshold: float of the lowest acceptable probability that a sequence would be sampled from the given martrix in order to attempt mapping. Recommend 0.0 unless many false positives strand: str either 'first' if reads are first-stranded or 'second' if reads are second-stranded Will right reads with valid alignment to <output>.bed. Information recorded in paired-end bed format. Reads with no valid alignment are written to <output>_no_alignment.fastq in the paired-end tab- deliminated format described in the bowtie manual. Reads are split as they were attempted to be aligned. Below is an example command: python findbps/findbps.py /path/to/reads /path/to/output_files "-y -p 2 -v 0 -X 5000 -m 1 index/path" '[{"A":0,"T":0,"C":0,"G":1},{"A":0,"T":.95,"C":.05,"G":0},{"A":1,"T":0,"C":0,"G":0},{"A":.02,"T":.8,"C":.18,"G":0},{"A":0,"T":0,"C":0,"G":1}]' 10 0 second ####################################################### In order to use this module directly as a python library, you must add this directory to your python path. This can easily be done temporarily by using the command: sys.path.append(<path to this directory>). You can then import the function findbps() using: from findbps import findbps You can then use the findbps function directly using: findbps(reads, output, bowtie_options, motif, length, threshold, strand) Arguments are the same as described above, except that arguments should be entered as thier respective types instead of as strings. Below is an example: from sys import path path.append('~/findbps') from findbps import findbps #specify reads you want to process reads = '/path/to/reads' #specify basename of output file here output = 'path/to/output_files' #specify bowtie options bowtie_options = "-y -p 2 -v 0 -X 5000 -m 1 index/path" #specify 5'SS weight matrix motif = [{"A":0,"T":0,"C":0,"G":1}, {"A":0,"T":.95,"C":.05,"G":0}, {"A":1,"T":0,"C":0,"G":0}, {"A":.02,"T":.8,"C":.18,"G":0}, {"A":0,"T":0,"C":0,"G":1}, {"A":.05,"T":.9,"C":.05,"G":0}] #specify shortest acceptable mapping length length = 10 #specify lowest probability that a reads best # 5'SS was sampled from the given matrix threshold = 0 strand = 'second' findbps(reads, output, bowtie_options, motif, length, threshold, strand)
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