pythseq pythseq

## extract_transcript_intron.sh
## requirement bed tools
BIN='/home/hirak/bedtools2/bin'
## Gencode
## gencode.v29.chr_patch_hapl_scaff.annotation.gtf
GTF_FILE="gencode.v29.chr_patch_hapl_scaff.annotation.gtf"

# extract transcript boundaries
cat $GTF_FILE | awk 'BEGIN{OFS="\t";} $3=="transcript" {print $1,$4-1,$5,$12}' | tr -d "\"" | tr -d ";" | $BIN/sortBed > gencode_transcript_intervals.bed

# merge exon boundaris

## My_data.tsv

          
            Class
            Repeatmasking
            Assembly
            Count

            
              CNL
              before
              B. napus
              23

            
              CNL
              after
              B. napus
              13

            
              CNL
              before
              B. rapa
              20

            
              CNL
              after
              B. rapa
              10

            
              CN
              before
              B. napus
              47

            
              CN
              after
              B. napus
              25

            
              CN
              before
              B. rapa
              16

            
              CN
              after
              B. rapa
              5

            
              N
              before
              B. napus
              92

## Parallel download of blast databases using rsync and GNU Parallel.md

      
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                pythseq
                / Parallel download of blast databases using rsync and GNU Parallel.md
            
            
              Created
              January 28, 2019 16:17
                — forked from ppflrs/Parallel download of blast databases using rsync and GNU Parallel.md
            
              
                Parallel download of blast databases using rsync+GNU Parallel
              
          
Select which database you want to download, here I will use the nucleotide database: nt.


Using rsync we will retrieve the name of the files composing the database from the NCBI server


rsync --list-only rsync://ftp.ncbi.nlm.nih.gov/blast/db/nt*.gz

Using grep we filter the Warning/Welcome message and retain only the compressed files

rsync --list-only rsync://ftp.ncbi.nlm.nih.gov/blast/db/nt*.gz | grep '.tar.gz'

  
## makeSummaryTable.py
# assuming that all results tables of BLINK are in the current folder, and assuming that all results tables were gzipped
# usage: python makeSummaryTable.py > Summary_Table.tsv

# this script will make one large summary table in the format rMVP requires, SNP, chrom, position, and then x columns for x phenotypes - each cell one p-value
# use grep -v to kick out regions of the genome you don't want to plot (unplaced contigs etc.)

import glob
import gzip
from collections import OrderedDict
all_phenos = ['SNP','chr','pos']

## highcov.c
/**
Author: Pierre Lindenbaum PhD. 2019

This tools calculate the mean depth of a bam (ignoring the non-covered bases)
and output a BED file of the regions covered more than mean-depth*FACTOR

compilation: gcc -o a.out -O3 -Wall -I../htslib highcov.c -L../htslib  -lm -lpthread -lhts -lz -llzma -lbz2

 */


## bedtools_cheatsheet.md

      
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                pythseq
                / bedtools_cheatsheet.md
            
            
              Created
              May 6, 2019 14:04
                — forked from ilevantis/bedtools_cheatsheet.md
            
              
                Bedtools cheatsheet
              
          
    Bedtools Cheatsheet

General:


Tools
Description


flank
Create new intervals from the flanks of existing intervals.


slop
Adjust the size of intervals.


shift
Adjust the position of intervals.


subtract
Remove intervals based on overlaps b/w two files.


## Genomics_A_Programmers_Guide.md

      
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                pythseq
                / Genomics_A_Programmers_Guide.md
            
            
              Created
              May 17, 2019 16:37
                — forked from andy-thomason/Genomics_A_Programmers_Guide.md
            
              
                Genomics a programmers introduction
              
          
    Genomics - A programmer's guide.

Andy Thomason is a Senior Programmer at Genomics PLC.
He has been witing graphics systems, games and compilers since
the '70s and specialises in code performance.
https://www.genomicsplc.com


## README.md

      
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                pythseq
                / README.md
            
            
              Created
              June 28, 2019 12:04
                — forked from lindenb/README.md
            
              
                https://twitter.com/sjackman/status/748259285151293440 ( flex ) Who's got a command for me to output coordinates of FASTA scaffolds gaps as a BED file? Looking for a one-liner.
              
          
    $ flex input.l && gcc -O3 lex.yy.c && curl -s "http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/chr22.fa.gz" | gunzip -c | ./a.out 
chr22	0	16050000
chr22	16697850	16847850
chr22	19178139	19178140
chr22	19178159	19178160
chr22	19178161	19178164
chr22	19178165	19178167

  
## wheeler_graphs.txt
Wheeler graphs

Gagie, Manzini, Siren
Theoretical Computer Science, 2017
https://www.sciencedirect.com/science/article/pii/S0304397517305285

Notes of a whiteboard presentation to the Bonsai team in Lille.
These notes largely follow the paper.
Rayan Chikhi, 2019

## ggmModSelect.Rnw
\documentclass{article}

\usepackage[
    paperwidth=27cm,paperheight=13cm,
    margin=1cm,
    ]{geometry}

\usepackage{amsmath}
\usepackage{amsfonts}
\usepackage{amssymb}
	## requirement bed tools
	BIN='/home/hirak/bedtools2/bin'
	## Gencode
	## gencode.v29.chr_patch_hapl_scaff.annotation.gtf
	GTF_FILE="gencode.v29.chr_patch_hapl_scaff.annotation.gtf"

	# extract transcript boundaries
	cat $GTF_FILE \| awk 'BEGIN{OFS="\t";} $3=="transcript" {print $1,$4-1,$5,$12}' \| tr -d "\"" \| tr -d ";" \| $BIN/sortBed > gencode_transcript_intervals.bed

	# merge exon boundaris
Class	Repeatmasking	Assembly	Count
CNL	before	B. napus	23
CNL	after	B. napus	13
CNL	before	B. rapa	20
CNL	after	B. rapa	10
CN	before	B. napus	47
CN	after	B. napus	25
CN	before	B. rapa	16
CN	after	B. rapa	5
N	before	B. napus	92
	# assuming that all results tables of BLINK are in the current folder, and assuming that all results tables were gzipped
	# usage: python makeSummaryTable.py > Summary_Table.tsv

	# this script will make one large summary table in the format rMVP requires, SNP, chrom, position, and then x columns for x phenotypes - each cell one p-value
	# use grep -v to kick out regions of the genome you don't want to plot (unplaced contigs etc.)

	import glob
	import gzip
	from collections import OrderedDict
	all_phenos = ['SNP','chr','pos']
	/**
	Author: Pierre Lindenbaum PhD. 2019

	This tools calculate the mean depth of a bam (ignoring the non-covered bases)
	and output a BED file of the regions covered more than mean-depth*FACTOR

	compilation: gcc -o a.out -O3 -Wall -I../htslib highcov.c -L../htslib -lm -lpthread -lhts -lz -llzma -lbz2

	*/
Tools	Description
flank	Create new intervals from the flanks of existing intervals.
slop	Adjust the size of intervals.
shift	Adjust the position of intervals.
subtract	Remove intervals based on overlaps b/w two files.
	Wheeler graphs

	Gagie, Manzini, Siren
	Theoretical Computer Science, 2017
	https://www.sciencedirect.com/science/article/pii/S0304397517305285

	Notes of a whiteboard presentation to the Bonsai team in Lille.
	These notes largely follow the paper.
	Rayan Chikhi, 2019
	\documentclass{article}

	\usepackage[
	paperwidth=27cm,paperheight=13cm,
	margin=1cm,
	]{geometry}

	\usepackage{amsmath}
	\usepackage{amsfonts}
	\usepackage{amssymb}