IGoR: Inference and Generation Of Repertoires
-This repository contains all sources and models useful to infer V(D)J -recombination related processes for TCR or BCR sequencing data using -IGoR
-Quick summary
+IGoR is a C++ software designed to infer V(D)J recombination related @@ -518,7 +586,7 @@
Quick summary
The following paper describes the methodology, performance tests and +
The following article describes the methodology, performance tests and some new biological results obtained with IGoR:
Quick summary
Version
Latest released version: 1.2.0
+Latest released version: 1.3.0
Dependencies
bash
autotools suite, asciidoctor, doxygen and the latex suite if building from +
autotools suite, asciidoctor, pygments (optional), doxygen and the latex suite if building from unpackaged sources
Install
Linux
Widely tested on several Debian related distros. Install gcc/g if not +
Widely tested on several Debian related distros. Install gcc/g++ if not
already installed (note that another compiler could be used). With the
-command line go to IGoR's root directory and simply type `./configure`.
+command line go to IGoR’s root directory and simply type ./configure.
This will make various check on your system and create makefiles
compatible with your system configuration. Many options can be appended
-to ./configure such as `./configure CC=gcc CXX=g` to enforce the use
-of gcc as compiler. Once over, type make to compile the sources (this
+to ./configure such as ./configure CC=gcc CXX=g\+\+ ` to enforce the use
+of gcc as compiler. Once over, type `make to compile the sources (this
will take a few minutes). IGoR’s executable will appear in the igor_src
folder
MacOS
sudo port selfupdate #Update macports database -sudo port install gcc6 #install gcc version 6+
sudo port selfupdate #Update macports database
+sudo port install gcc6 #install gcc version 6MacOS
port select --list gcc #Will list the versions of gcc available on your system -sudo port select --set gcc mp-gcc6 #set the one you wish to have as default call upon using the gcc command+
port select --list gcc #Will list the versions of gcc available on your system
+sudo port select --set gcc mp-gcc6 #set the one you wish to have as default call upon using the gcc commandMacOS
brew install gcc+
brew install gccGeneral commands summary
-set_CDR3_anchors --gene
Load a CSV file containing the indices/offset of +
Load a semicolon separated file containing the indices/offset of the CDR3 anchors for the gene(--V or --J). The index should correspond to the first letter of the cysteine (for V) or tryptophan/phenylalanin (for J) for the nucleotide sequence of the gene. Indices are 0 based.
Outputs
Python utility functions are provided to analyze these outputs in the -pygor.counters submodule.
+pygor.counters submodule.
Best scenarios
@@ -1649,7 +1717,7 @@Command examples
igor -run_demo+
igor -run_demoCommand examples
WDPATH=/path/to/your/working/directory #Let's define a shorthand for the working directory ++#Now generate 100 synthetic sequences from the provided human beta chain model +#This will create the directory bar_generate with the corresponding files containing the generated sequences and their realizations +igor -set_wd $WDPATH -batch bar -species human -chain beta -generate 100WDPATH=/path/to/your/working/directory #Let's define a shorthand for the working directory -#We first read the sequences contained in a text file inside the demo folder -#This will create the align folder in the working directory and the mydemo_indexed_seqs.csv file. -igor -set_wd $WDPATH -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt +#We first read the sequences contained in a text file inside the demo folder +#This will create the align folder in the working directory and the mydemo_indexed_seqs.csv file. +igor -set_wd $WDPATH -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt -#Now let's align the sequences against the provided human beta chain genomic templates with default parameters -#This will create foo_V_alignments.csv, foo_D_alignments.csv and foo_J_alignments.csv files inside the align folder. -igor -set_wd $WDPATH -batch foo -species human -chain beta -align --all +#Now let's align the sequences against the provided human beta chain genomic templates with default parameters +#This will create foo_V_alignments.csv, foo_D_alignments.csv and foo_J_alignments.csv files inside the align folder. +igor -set_wd $WDPATH -batch foo -species human -chain beta -align --all -#Now use the provided beta chain model to get the 10 best scenarios per sequence -#This will create the foo_output and foo_evaluate and the corresponding files inside -igor -set_wd $WDPATH -batch foo -species human -chain beta -evaluate -output --scenarios 10 +#Now use the provided beta chain model to get the 10 best scenarios per sequence +#This will create the foo_output and foo_evaluate and the corresponding files inside +igor -set_wd $WDPATH -batch foo -species human -chain beta -evaluate -output --scenarios 10 -#Now generate 100 synthetic sequences from the provided human beta chain model -#This will create the directory bar_generate with the corresponding files containing the generated sequences and their realizations -igor -set_wd $WDPATH -batch bar -species human -chain beta -generate 100
Command examples
WDPATH=/path/to/your/working/directory #Let's define a shorthand for the working directory -MYCOMMANDS=./igor -set_wd $WDPATH ++$MYCOMMANDS -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt #Read seqs +MYCOMMANDS=$MYCOMMANDS -species human -chain beta #Add chain and species commands +$MYCOMMANDS -batch foo -align --all #Align +$MYCOMMANDS -batch foo -evaluate -output --scenarios 10 #Evaluate +$MYCOMMANDS -batch bar -generate 100 #GenerateWDPATH=/path/to/your/working/directory #Let's define a shorthand for the working directory +MYCOMMANDS=./igor -set_wd $WDPATH -$MYCOMMANDS -batch foo -read_seqs ../demo/murugan_naive1_noncoding_demo_seqs.txt #Read seqs -MYCOMMANDS=$MYCOMMANDS -species human -chain beta #Add chain and species commands -$MYCOMMANDS -batch foo -align --all #Align -$MYCOMMANDS -batch foo -evaluate -output --scenarios 10 #Evaluate -$MYCOMMANDS -batch bar -generate 100 #Generate