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 ./introntab.pl --format gtf < xxxx-braker.gtf | column -t -s$'\t' | less -S Com o output usar colunas para contar

Entrar pelo google ferramentas do desenvolvedor  When the SVG is integrated as   <svg ...></svg>   markup directly into the HTML page. Right click on the SVG to inspect it in developer tools Find the root of the  <svg>  element and right click to  "Copy element" Go to  https://jakearchibald.github.io/svgomg/  and  "Paste markup" Download your optimized SVG file and enjoy

 Retirado de: https://playingwithgenomics.wordpress.com/2015/07/15/producing-a-bam-file-and-extracting-unique-reads-from-bowtie2-results/ I am always looking for ways to keep my disk usage down. Especially since I’ve been mapping close to 100 Chip-Seq files. I find that 1) piping Bowtie2 output into samtools to create a bam file and 2) keeping only the uniquely mapped reads help a lot. Here is how I do those: I’m dealing with single-end data here. You can modify the command if you are dealing with paired-end data. Text written in red should be substituted according to your data. Converting Bowtie2 output to bam file bowtie2 -x BOWTIE2_INDEX -\ -p NUM_THREADS \ -U INPUT_FILE.fastq.gz | samtools view -bS -t \ YOUR_GENOME_INDEX.fa.fai - > output.bam Counting unique reads You basically can exploit the XS tag that are set by Bowtie2  for reads that can be mapped in multiple places. Therefore, uniquely mapped reads lack the XS tag. The following command exclude u...

  Platanus_trim xxx_1.fastq xxx_2.fastq   Platanus assemble -o Pxut -f ./DRR02167[34]_[12].fastq 2> assemble.log Platanus scaffold -o Pxut -c Pxut_contig.fa -b Pxut_contigBubble.fa -IP1 ./DRR021673_1.fastq ./DRR021673_2.fastq –IP2 ./DRR021674_1.fastq ./DRR021674_2.fastq -OP3 ./DRR021675_1.fastq ./DRR021675_2.fastq ./DRR021676_1.fastq ./DRR021676_2.fastq 2> scaffold.log   Platanus gap_close -o Pxut -c Pxut_scaffold.fa -IP1 ./DRR021673_1.fastq ./DRR021673_2.fastq –IP2 ./DRR021674_1.fastq ./DRR021674_2.fastq -OP3 ./DRR021675_1.fastq ./DRR021675_2.fastq ./DRR021676_1.fastq ./DRR021676_2.fastq 2> gapclose.log    

 cat clt_Uvol_align.sh | awk '{print $1,$2,$3,$4,$5,$6,$7,S8,$6}' > clt_Uvol_align2.sh

Quando: bash: xxxx /usr/bin/xxxx^M: interpretador incorreto: Arquivo ou diretório inexistente sed - i - e 's/\r$//' [nome do script]

Para usar o Hyphy, de preferência compilar da source pois as vezes não acha as bibliotecas necessárias no sistema. Para Hyphy  Kitware now has an APT repository that currently supports Ubuntu 16.04, 18.04 and 20.04 Install Instructions: Remove old version of cmake sudo apt purge --auto-remove cmake Obtain a copy of the signing key wget -O - https://apt.kitware.com/keys/kitware-archive-latest.asc 2>/dev/null | gpg --dearmor - | sudo tee /etc/apt/trusted.gpg.d/kitware.gpg >/dev/null Add the repository to your sources list a. For Ubuntu Focal Fossa (20.04) sudo apt-add-repository 'deb https://apt.kitware.com/ubuntu/ focal main' b. For Ubuntu Bionic Beaver (18.04) sudo apt-add-repository 'deb https://apt.kitware.com/ubuntu/ bionic main' c. For Ubuntu Xenial Xerus (16.04) sudo apt-add-repository 'deb https://apt.kitware.com/ubuntu/ xenial main' Update and install sudo apt update sudo apt install cmake

Pegar arquivos "nome ebps" para a pasta atual ln -s */ebps*.fasta .

Erro: " msa.cc: In function ‘void msa_main(const char*)’: msa.cc:289:22: error: ‘chdir’ was not declared in this scope if (chdir(html_fn)<0) ^ make: *** [mcscanx] Error 1" Para passar esse erro: Colocar a linha:   #include <unistd.h> Nos arquivos: msa.h dissect_multiple_alignment.h detect_collinear_tandem_arrays.h   Preparando arquivo gff3 do Phytozome para gff para o MCScanX:   cat annotation.all_transcripts.all_features.ptr.gff3 | cut -f 1,4,5,9 | sed 's/ID=//g' | sed 's/;/\t/g' | grep "\tid=" | cut -f 1,2,3,4 | awk '{print $1" "$4" "$2" "$3}' > annotation.all_transcripts.all_features.ptr.gff  e cat annotation.all_transcripts.all_features.ptr.gff | sed 's/ /\t/g' > annotation.all_transcripts.all_features.ptr_2.gff   Se for comparar dois genomas tem que colocar os dois gffs no mesmo arquivo?  

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