Commit 00b4450b authored by hjulienne's avatar hjulienne

fixed issue #1

parent c9e31651
Pipeline #7822 passed with stages
in 1 minute and 23 seconds
......@@ -14,7 +14,6 @@ impute\_jass.windows
format_result_df
impg_like_imputation
in_region
ld_region_centered_window_imputation
parse_region_position
prepare_zscore_for_imputation
print_progression
......
......@@ -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.
Dependancies
Dependencies
============
RAISS require plink version 1.9
RAISS requires plink version 1.9 : `<https://www.cog-genomics.org/plink2>`_
Installation
============
......@@ -39,8 +38,8 @@ Precomputation of LD-correlation
The imputation is based the Linkage desiquilibrium between SNPs.
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
region of approximately LD-independant. For an european ancestry, you can use
performed. To limit the number of SNP pairs, the LD is computed between pairs of
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.
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:
| 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
======================================
......@@ -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
launch_imputation_all_gwas.sh contain an example for SLURM scheduler.
#TODO check command line interface
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 |
+============+===+==+================+=====+=====+================+==================+=========+=========+
......
......@@ -10,8 +10,8 @@ Fast and accurate imputation of summary statistics enhances evidence
of functional enrichment, Bioinformatics, Volume 30, Issue 20, 15 October 2014,
Pages 2906–2914
"""
import numpy as np
import scipy as sc
import scipy.linalg
......
......@@ -2,7 +2,7 @@ from setuptools import setup, find_packages
setup(name='impute_jass',
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',
author='Hanna Julienne',
author_email='hanna.julienne@pasteur.fr',
......
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