conda create -n anaCogent5.2 python=2.7 anaconda
source activate anaCogent5.2
conda install -n anaCogent5.2 biopython
conda install -n anaCogent5.2 -c bx-python
conda install -n anaCogent5.2 -c bioconda isoseq3
conda install -n anaCogent5.2 -c bioconda pbccs
conda install -n anaCogent5.2 -c bioconda lima
#The packages below are optional:
conda install -n anaCogent5.2 -c bioconda pbcoretools # for manipulating PacBio datasets
conda install -n anaCogent5.2 -c bioconda bamtools # for converting BAM to fasta
conda install -n anaCogent5.2 -c bioconda pysam # for making CSV reports

Running IsoSeq
Typical workflow:
1. Generate consensus sequences from your raw subread data
$ ccs movie.subreads.bam movie.ccs.bam –noPolish –minPasses 1

2. Generate full-length reads by primer removal and demultiplexing
$ cat primers.fasta
$ lima movie.ccs.bam primers.fasta movie.fl.bam –isoseq –no-pbi

3. Remove noise from FL reads
$ isoseq3 refine movie.fl.P5–P3.bam primers.fasta movie.flnc.bam

4. Cluster consensus sequences to generate unpolished transcripts
$ isoseq3 cluster movie.flnc.bam unpolished.bam –verbose

5. Optionally, polish transcripts using subreads
$ isoseq3 polish unpolished.bam movie.subreads.bam polished.bam

6. Map unpolished or polished transcripts to genome and collapse transcripts based on genomic mapping
$ pbmm2 align unpolished.bam reference.fasta aligned.sorted.bam –preset ISOSEQ –sort
$ isoseq3 collapse aligned.sorted.bam out.gff
or $ isoseq3 collapse aligned.sorted.bam movie.ccs.bam out.gff



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