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Commit 00b4450b authored by hjulienne's avatar hjulienne
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fixed issue #1

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...@@ -14,7 +14,6 @@ impute\_jass.windows ...@@ -14,7 +14,6 @@ impute\_jass.windows
format_result_df format_result_df
impg_like_imputation impg_like_imputation
in_region in_region
ld_region_centered_window_imputation
parse_region_position parse_region_position
prepare_zscore_for_imputation prepare_zscore_for_imputation
print_progression print_progression
......
...@@ -21,10 +21,9 @@ The statistical model used to make the imputation is described in :cite:`Pasaniu ...@@ -21,10 +21,9 @@ The statistical model used to make the imputation is described in :cite:`Pasaniu
The imputation execution time is optimized by precomputing Linkage desiquilibrium between SNPs. The imputation execution time is optimized by precomputing Linkage desiquilibrium between SNPs.
Dependancies Dependencies
============ ============
RAISS require plink version 1.9 RAISS requires plink version 1.9 : `<https://www.cog-genomics.org/plink2>`_
Installation Installation
============ ============
...@@ -39,8 +38,8 @@ Precomputation of LD-correlation ...@@ -39,8 +38,8 @@ Precomputation of LD-correlation
The imputation is based the Linkage desiquilibrium between SNPs. The imputation is based the Linkage desiquilibrium between SNPs.
To save computation the LD is computed and saved perform the imputation is To save computation the LD is computed and saved perform the imputation is
performed. To limit the number of SNP pairs, the LD is computed between SNPs in performed. To limit the number of SNP pairs, the LD is computed between pairs of
region of approximately LD-independant. For an european ancestry, you can use SNPs in a approximately LD-independent regions. For an european ancestry, you can use
the region defined by :cite:`Berisa2015` that are provided in the package data folder. the region defined by :cite:`Berisa2015` that are provided in the package data folder.
To compute the LD you need to specify a reference panel splitted by chromosomes To compute the LD you need to specify a reference panel splitted by chromosomes
...@@ -70,7 +69,8 @@ all in the same folder with the following columns with the same header: ...@@ -70,7 +69,8 @@ all in the same folder with the following columns with the same header:
| rs6548219| 30762 | A | G | -1.133 | | rs6548219| 30762 | A | G | -1.133 |
+----------+-------+------+-----+--------+ +----------+-------+------+-----+--------+
This format can be obtain with the Processing package. This format can be obtain with the `JASS PreProcessing package <https://gitlab.pasteur.fr/statistical-genetics/JASS_Pre-processing>`.
Launching imputation on one chromosome Launching imputation on one chromosome
====================================== ======================================
...@@ -81,14 +81,13 @@ If you have access to a cluster, an efficient way to use RAISS is to launch ...@@ -81,14 +81,13 @@ If you have access to a cluster, an efficient way to use RAISS is to launch
the imputation of each chromosome on a separate cluster node. The script the imputation of each chromosome on a separate cluster node. The script
launch_imputation_all_gwas.sh contain an example for SLURM scheduler. launch_imputation_all_gwas.sh contain an example for SLURM scheduler.
#TODO check command line interface #TODO check command line interface
Output Output
====== ======
The raiss package output imputed GWAS files in the tabular format: The raiss package outputs imputed GWAS files in the tabular format:
#TODO suppress complementary columns
+------------+---+--+----------------+-----+-----+----------------+------------------+---------+---------+ +------------+---+--+----------------+-----+-----+----------------+------------------+---------+---------+
| |A0 |A1| Nsnp_to_impute |Var |Z |condition_number|correct_inversion |ld_score | pos | | |A0 |A1| Nsnp_to_impute |Var |Z |condition_number|correct_inversion |ld_score | pos |
+============+===+==+================+=====+=====+================+==================+=========+=========+ +============+===+==+================+=====+=====+================+==================+=========+=========+
......
...@@ -10,8 +10,8 @@ Fast and accurate imputation of summary statistics enhances evidence ...@@ -10,8 +10,8 @@ Fast and accurate imputation of summary statistics enhances evidence
of functional enrichment, Bioinformatics, Volume 30, Issue 20, 15 October 2014, of functional enrichment, Bioinformatics, Volume 30, Issue 20, 15 October 2014,
Pages 2906–2914 Pages 2906–2914
""" """
import numpy as np import numpy as np
import scipy as sc import scipy as sc
import scipy.linalg import scipy.linalg
......
...@@ -2,7 +2,7 @@ from setuptools import setup, find_packages ...@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
setup(name='impute_jass', setup(name='impute_jass',
version='0.1', version='0.1',
description='Preprocess GWAS summary statistic for JASS', description='Imputation of summary statistics',
url='http:https://gitlab.pasteur.fr/statistical-genetics/JASS_Pre-processing', url='http:https://gitlab.pasteur.fr/statistical-genetics/JASS_Pre-processing',
author='Hanna Julienne', author='Hanna Julienne',
author_email='hanna.julienne@pasteur.fr', author_email='hanna.julienne@pasteur.fr',
......
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