Postagens

script para o uso do trimmomatic - Projeto FLOR

#!/bin/bash #input = diretório com os arquivos no formato .fastq #outdir = diretóro de saída dos arquivos do Trimmomatic #base_out = diretório de saída input="$1" if [ ! ${input} ] then         echo "Missing input directory"         exit else         if [ ! -d ${input} ]         then                 echo "Wrong input path (${input})."                 exit         fi fi outdir="$2" if [ ! ${outdir} ] then         outdir="." else         if [ ! -d ${outdir} ]         then            ...

MitoBim results

Hi there, I've been using mitobim1.8 to reconstruct mitochondrial genomes from a bird using a related species. It seems to have worked; however I don't quite understand the output. In my last iteration file, there are a number of padded and unpadded fasta files... named, for example: sample-reference-out- AllStrains.padded.fasta sample-reference-out- AllStrains.unpadded.fasta sample-reference-out-sample. padded.fasta sample-reference-out-sample. unpadded.fasta sample-reference-out- reference.padded.fasta sample-reference-out- reference.unpadded.fasta I understand the difference between the unpadded and padded, but not AllStrains vs sample vs reference. Could you please explain this to me? I think I've worked out that the AllStrains is being used as the backbone for the next iteration. However this confuses me, as it also appears that in the info folder from mira, in the assembly.txt file all the tags relate to the sample version. Also, I was wondering if you have ...

Code ML como fazer analise de pressão seletiva

https://evosite3d.blogspot.com.br/2011/09/identifying-positive-selection-in.html

Open Refine

http://openrefine.org/ Planilhas - merge de planilhas - importação de colunas - (...)

Blast tabular format

Column headers: qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore  1.  qseqid  query (e.g., gene) sequence id  2.  sseqid  subject (e.g., reference genome) sequence id  3.  pident  percentage of identical matches  4.  length  alignment length  5.  mismatch  number of mismatches  6.  gapopen  number of gap openings  7.  qstart  start of alignment in query  8.  qend  end of alignment in query  9.  sstart  start of alignment in subject  10.  send  end of alignment in subject  11.  evalue   expect value  12.  bitscore   bit score

Uame-Purple-merge - para listas de fatores de transcricao x qantidade de transcritos

cat Uame-Purple-merged.list.txt | cut -f 2,3 | sed 's,|,\t,g' | cut -f 2,4 | nsort -u | cut -f1 | nsort | uniq -c

R merge

setwd ('/data/project/flowers/orthologous/transcriptional_factors') lista1 <- read.delim(file='TFs.list', header=F, stringsAsFactors=F) lista2 <- read.delim(file='PlantTFDB-allxUame-Purple_assm_id60_moresensitive_cov60', header=F, stringsAsFactors=F) colnames(lista1) <- c('ID', 'Desc') colnames(lista2) <- c('Transcript', 'ID', 'pident', 'length', 'mismatch', 'gapopen', 'qstart', 'qend', 'sstart', 'send', 'evalue', 'bitscore') head (lista1) head (lista2) merged_list <-  merge(x=lista1, y=lista2, by.x='ID', by.y='ID') head (merged_list) dim(merged_list) library(xlsx) #write.xlsx(merged_list, 'Uame-Purple-merged.list.xls') write.table(merged_list, file='Uame-Purple-merged.list.txt', row.names=F, col.names=T, quote=F, sep="\t")