Commit 1db9a920 authored by Mathieu Giraud's avatar Mathieu Giraud

doc/algo.org: correct the examples in the documentation

Thanks to the previous commit, see #1284.
parent b7f281a3
......@@ -694,19 +694,19 @@ applicable being removed:
* Examples of use
All the following examples are on a IGH VDJ recombinations : they thus
require either the =-G germline/IGH= option, or the multi-germline =-g germline= option.
require either the =-g germline/homo-sapiens-g:IGH= option, or the multi-germline =-g germline= option.
** Basic usage: PCR-based datasets, with primers in the V(D)J regions (such as BIOMED-2 primers)
#+BEGIN_SRC sh
./vidjil -G germline/IGH -3 data/Stanford_S22.fasta
./vidjil -g germline/homo-sapiens.g:IGH -3 data/Stanford_S22.fasta
# Cluster the reads into clones, based on windows overlapping IGH CDR3s.
# Assign the VDJ genes and try to detect the CDR3 of each clone.
# Summary of clones is available both on stdout, in out/Stanford_S22.vdj.fa and in out/Stanford_S22.vidjil.
#+END_SRC
#+BEGIN_SRC sh
./vidjil -g germline -i -2 -3 -d data/reads.fasta
./vidjil -g germline -2 -3 -d data/Stanford_S22.fasta
# Detects for each read the best locus, including an analysis of incomplete/unusual and unexpected recombinations
# Cluster the reads into clones, again based on windows overlapping the detected CDR3s.
# Assign the VDJ genes (including multiple D) and try to detect the CDR3 of each clone.
......@@ -717,7 +717,7 @@ require either the =-G germline/IGH= option, or the multi-germline =-g germline=
** Basic usage: Whole RNA-Seq or capture datasets
#+BEGIN_SRC sh
./vidjil -g germline -i -2 -U data/reads.fasta
./vidjil -g germline -2 -U data/Stanford_S22.fasta
# Detects for each read the best locus, including an analysis of incomplete/unusual and unexpected recombinations
# Cluster the reads into clones, again based on windows overlapping the detected CDR3s.
# Assign the VDJ genes and try to detect the CDR3 of each clone.
......@@ -733,13 +733,13 @@ This file will be relatively small (a few kB or MB) and can be taken again as an
** Advanced usage
#+BEGIN_SRC sh
./vidjil -c clones -G germline/IGH -r 1 ./data/clones_simul.fa
./vidjil -c clones -g germline/homo-sapiens.g:IGH -r 1 ./data/clones_simul.fa
# Extracts the windows with at least 1 read each (-r 1, the default being -r 5)
# then cluster them into clones
#+END_SRC
#+BEGIN_SRC sh
./vidjil -c clones -G germline/IGH -r 1 -n 5 ./data/clones_simul.fa
./vidjil -c clones -g germline/homo-sapiens.g:IGH -r 1 -n 5 ./data/clones_simul.fa
# Window extraction + clone clustering,
# with automatic clustering, distance five (-n 5)
# The result of the automatic clustering is in the .vidjil file
......@@ -747,13 +747,13 @@ This file will be relatively small (a few kB or MB) and can be taken again as an
#+END_SRC
#+BEGIN_SRC sh
./vidjil -c segment -g germline -i -2 -3 -d data/segment_S22.fa
./vidjil -c segment -g germline/homo-sapiens.g -2 -3 -d data/segment_S22.fa
# Detailed V(D)J designation, including multiple D, and CDR3 detection on all reads, without clone clustering
# (this is slow and should only be used for testing, or on a small file)
#+END_SRC
#+BEGIN_SRC sh
./vidjil -c germlines file.fastq
./vidjil -c germlines -g germline/homo-sapiens.g data/Stanford_S22.fasta
# Output statistics on the number of occurrences of k-mers of the different germlines
#+END_SRC
......
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