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import sys

sys.path.append('/bioware/pythonmodules/fastalib/')

import fastalib as u

fasta = u.SequenceSource(sys.argv[1])
output = u.FastaOutput(sys.argv[1] + '-with-gaps')

longest_read = 0

meren

import sys
import Oligotyping.lib.fastalib as u

fasta = u.SequenceSource(sys.argv[1])
output = u.FastaOutput(sys.argv[1] + '-QIIME-READY')


# H12DL4_12 B022DACXX4110133892403 orig_bc=GATCAG new_bc=GATCAG bc_diffs=0
sample_read_counter = {}

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# coding: utf-8

import sys
from Oligotyping.utils.utils import generate_ENVIRONMENT_file
from Oligotyping.utils.utils import get_oligos_sorted_by_abundance
from Oligotyping.utils.utils import get_unit_counts_and_percents
from Oligotyping.utils.utils import generate_MATRIX_files
from Oligotyping.utils.utils import get_filtered_samples_dict
from Oligotyping.utils.utils import get_samples_dict_from_environment_file

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#####################################################################################
# Q-Q plot in ggplot2
# taken from http://stackoverflow.com/questions/4357031/qqnorm-and-qqline-in-ggplot2
#####################################################################################

require(ggplot2)

vec <- Hg$AMT # whateer

y <- quantile(vec[!is.na(vec)], c(0.25, 0.75))

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# sorry about the terrible code. example use:
#
#     python expand_regex_pattern.py A.T[C,T]AAA.[A,G]AAT[A,T]GACGG
#

import sys

rp = sys.argv[1]
expant = ['']
valid_bases = ['A', 'T', 'C', 'G']

meren

# example fasta defline:
#>147406386-BM_GFKBOSR02F10DX|Bacteria;Actinobacteria;Actinobacteria;Actinomycetales;Micrococcaceae;Rothia

import sys
import Oligotyping.lib.fastalib as u
from Oligotyping.utils.utils import generate_ENVIRONMENT_file
from Oligotyping.utils.utils import get_sample_name_from_defline
from Oligotyping.utils.utils import get_oligos_sorted_by_abundance
from Oligotyping.utils.utils import get_unit_counts_and_percents
from Oligotyping.utils.utils import generate_MATRIX_files

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meren ~/tmp/sample-run $ ls mock-env-aligned-c2-s1-a1.0-A0-M0/
COLORS                      MATRIX-PERCENT.txt          OLIGOS.nexus
ENVIRONMENT.txt             NETWORK.gexf                READ-DISTRIBUTION.txt
FIGURES/                    OLIGO-REPRESENTATIVES/      RUNINFO
FIGURES.cPickle             OLIGO-REPRESENTATIVES.fasta RUNINFO.cPickle
MATRIX-COUNT.txt            OLIGOS.fasta                RUNINFO.log

meren

library('ape')
library('vegan')
library('ade4')


raw_data <- t(data.matrix(read.table('YOUR TAB DELIMITED TRANSCRIPTOMIC DATA MATRIX', header = TRUE, row.names = 1, sep="\t")))

drows<-vegdist(t(raw_data), method='euclidean', na.rm=TRUE)
hc <- hclust(drows, method='ward')
phy <- hclust2phylog(hc, add.tools = TRUE)

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import sys
import IlluminaUtils.lib.fastqlib as u
import IlluminaUtils.lib.fastalib as f
from IlluminaUtils.utils.helperfunctions import reverse_complement

# call this script like this:
#
# python demultiplex.py barcode_to_sample_name_file index_fastq_file quality_filtered_fasta_file
#
# expected file formats are shown below. 

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library(ggplot2)
library(maps)
require(ggmap)
library(vegan)
require(mapproj)
library(maptools)

#######################################################################################################################
#######################################################################################################################
#