| More recent resolution: | |
| 1. cd ~/../../etc (go to etc folder in WSL). | |
| 2. echo "[network]" | sudo tee wsl.conf (Create wsl.conf file and add the first line). | |
| 3. echo "generateResolvConf = false" | sudo tee -a wsl.conf (Append wsl.conf the next line). | |
| 4. wsl --terminate Debian (Terminate WSL in Windows cmd, in case is Ubuntu not Debian). | |
| 5. cd ~/../../etc (go to etc folder in WSL). | |
| 6. sudo rm -Rf resolv.conf (Delete the resolv.conf file). | |
| 7. In windows cmd, ps or terminal with the vpn connected do: Get-NetIPInterface or ipconfig /all for get the dns primary and | |
| secondary. |
https://github.com/aancel/admin/wiki/VirtualGL-on-Ubuntu
https://virtualgl.org/About/Introduction
When you use ssh with X forwarding, you might have noticed that you cannot execute programs that require 3D acceleration. That's where VirtualGL comes into play.
Ensembl's VEP (Variant Effect Predictor) is popular for how it picks a single effect per gene as detailed here, its CLIA-compliant HGVS variant format, and Sequence Ontology nomenclature for variant effects.
To follow these instructions, we'll assume you have these packaged essentials installed:
## For Debian/Ubuntu system admins ##
sudo apt-get install -y build-essential git libncurses-dev
## For RHEL/CentOS system admins ##
sudo yum groupinstall -y 'Development Tools'
sudo yum install -y git ncurses-devel
Ensembl's VEP (Variant Effect Predictor) is popular for how it picks a single effect per gene as detailed here, its CLIA-compliant HGVS variant format, and Sequence Ontology nomenclature for variant effects.
To follow these instructions, we'll assume you have these packaged essentials installed:
## For Debian/Ubuntu system admins ##
sudo apt-get install -y build-essential git libncurses-dev
## For RHEL/CentOS system admins ##
sudo yum groupinstall -y 'Development Tools'
sudo yum install -y git ncurses-devel
Ensembl's VEP (Variant Effect Predictor) is popular for how it picks a single effect per gene as detailed here, its CLIA-compliant HGVS variant format, and Sequence Ontology nomenclature for variant effects.
To follow these instructions, we'll assume you have these packaged essentials installed:
sudo yum install -y curl rsync tar make perl perl-core
## OR ##
sudo apt-get install -y curl rsync tar make perl perl-base
VEP requires Perl 5.10 or newer, but I'd strongly recommend at least 5.18. If your system Perl is outdated, then follow this gist to set up Perl 5.22. Once that's done, set temporary shell variables pointing to where Perl and its libraries live. Change this as needed for y
| #!/usr/bin/env perl | |
| # | |
| # Downloaded from http://www.uppmax.uu.se/system/files/fastqFormatDetect.pl_.txt on Jan 19, 2016. | |
| # | |
| # Author: Martin Dahlo / modified Jacques Dainat | |
| # | |
| # Usage: perl scriptname.pl <infile> [-a -t <max seconds to search>] | |
| # ex. | |
| # perl scriptname.pl reads.fq | |
| # perl scriptname.pl reads.fq -a |
| import csv | |
| import requests | |
| import bs4 | |
| import argparse | |
| # parser = argparse.ArgumentParser(description='Process a list of search terms.') | |
| # parser.add_argument('terms', metavar='N', type=str, nargs='+', | |
| # help='comma separated list of terms to search for') | |
| # args = parser.parse_args() |
| ERCC-00002 ERCC exon 1 1061 0.000000 + . gene_id "ERCC-00002"; transcript_id "DQ459430"; | |
| ERCC-00003 ERCC exon 1 1023 0.000000 + . gene_id "ERCC-00003"; transcript_id "DQ516784"; | |
| ERCC-00004 ERCC exon 1 523 0.000000 + . gene_id "ERCC-00004"; transcript_id "DQ516752"; | |
| ERCC-00009 ERCC exon 1 984 0.000000 + . gene_id "ERCC-00009"; transcript_id "DQ668364"; | |
| ERCC-00012 ERCC exon 1 994 0.000000 + . gene_id "ERCC-00012"; transcript_id "DQ883670"; | |
| ERCC-00013 ERCC exon 1 808 0.000000 + . gene_id "ERCC-00013"; transcript_id "EF011062"; | |
| ERCC-00014 ERCC exon 1 1957 0.000000 + . gene_id "ERCC-00014"; transcript_id "DQ875385"; | |
| ERCC-00016 ERCC exon 1 844 0.000000 + . gene_id "ERCC-00016"; transcript_id "DQ883664"; | |
| ERCC-00017 ERCC exon 1 1136 0.000000 + . gene_id "ERCC-00017"; transcript_id "DQ459420"; | |
| ERCC-00019 ERCC exon 1 644 0.000000 + . gene_id "ERCC-00019"; transcript_id "DQ883651"; |
| def splitDataFrameList(df,target_column,separator): | |
| ''' df = dataframe to split, | |
| target_column = the column containing the values to split | |
| separator = the symbol used to perform the split | |
| returns: a dataframe with each entry for the target column separated, with each element moved into a new row. | |
| The values in the other columns are duplicated across the newly divided rows. | |
| ''' | |
| def splitListToRows(row,row_accumulator,target_column,separator): | |
| split_row = row[target_column].split(separator) |
| #!bin/python | |
| import gzip | |
| import io | |
| import sys | |
| import os | |
| # This file will generate a bedfile of the masked regions a fasta file. | |
| # STDIN or arguments |