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params.prefix="output."
params.bamlist=""
params.sites="https://github.com/brentp/somalier/files/3412453/sites.hg19.vcf.gz"
params.help=false
params.pedigree="NO_FILE"

def helpMessage() {
  log.info"""

=========================================

pythseq

params.directories="."
params.headsize=100000
params.extensions="bam bai"
params.help=false
params.extrafind=""
params.lines = 1000
params.publishDir="."

def helpMessage() {
  log.info"""

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#!/usr/bin/env snakemake

# Requires Python3.6 or greater

rule align_A:
  output:
    outfile = "align__A/{sample}.bam"
  shell:
    '''
    mkdir -p $(dirname {output.outfile})

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library(tibble)
library(jsonlite)
library(curl)
as_tibble(jsonlite::fromJSON(curl('https://api.omicidx.cancerdatasci.org/sra/studies/ERP009142/runs?size=500'))$hits)

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#! /bin/bash

# Make a directory to hold local libs and bins
mkdir -p ~/usr/local

# Get protobuf
wget https://protobuf.googlecode.com/files/protobuf-2.5.0.tar.gz
# Extract protobuf
tar -xvzf protobuf-2.5.0.tar.gz
cd protobuf-2.5.0

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Running OrthoMCL on a set of protein annotations from various species

OrthoMCL is the leading piece of software for inferring orthologs across several organisms. In this tutorial I will provide detailed instructions for running a set of protein annotations through OrthoMCL.

Software and Data

1. OrthoMCL, and it's dependencies, must be installed. Detailed information on this tool and its installation can be found here. I actually used a slightly modified version of OrthoMCL that was made available by the author of the orthomcl-pipeline (see below). There isn't much details on the ways this is different from the existing OrthoMCL, but this is available here.
2. orthmcl-pipeline must also be installed, as this is how we will automate the OrthoMCL process. Detailed information on this tool and its installation can be found [here](https

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GNU Parallel for Bioinformatics: A primer

Installation:

A quick installation does not require root access, as shown:

(wget -O - pi.dk/3 || curl pi.dk/3/ || fetch -o - http://pi.dk/3) | bash

For other installation options see http://git.savannah.gnu.org/cgit/parallel.git/tree/README

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+ bash getStats.sh chm13_pergrine_p_ctg_cns.fasta
Checking attempted with maximum distance from contig end of 1000 bp..Done
******************* BAC SUMMARY ******************
 TOTAL    : 341
 BP       : 51532183
************** Statistics for: chm13_p_ctg_cns.fasta ****************
BACs closed: 321 (94.1349); BACs attempted: 333 %good = 96.3964; BASES 48527269 (94.1689)
Median:          99.9878
MedianQV:        39.1364
Mean:            99.94864

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The initial source comes from sdcuike/issueBlog#4

http://greenteapress.com/wp/

https://papers.nips.cc

https://github.com/PacktPublishing free to download books code by Packet

https://github.com/EbookFoundation/free-programming-books Very immense

pythseq

Jetson Xavier basecalling notes

initial basecalling runs

'fast' flip-flop calling on the Jetson Xavier

guppy_basecaller --disable_pings --compress_fastq -c dna_r9.4.1_450bps_fast.cfg -i flongle_fast5_pass/ -s flongle_test2 -x 'auto' --recursive