jsqtl's Introduction
---------------------- Copyright ---------------------- Copyright (c) 2019, Ruize Liu, Hailiang Huang and Mark J Daly, Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston MA All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: 1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. 2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. The views and conclusions contained in the software and documentation are those of the authors and should not be interpreted as representing official policies, either expressed or implied, of the FreeBSD Project. ---------------------- Synopsis ---------------------- This is a pipline for junction-skipping QTL (jsQTL) analysis. The method is desiged to identify junction-skipping events in the RNA-seq data from GTEx and their regulatory variants. Method details available at: https://www.biorxiv.org/content/10.1101/804039v1 ---------------------- Prerequisites ---------------------- Linux system is required for this analysis pipline. e.g.: Ubuntu 16.04 Softwares or packages required: python >= 2.7.9 python packages: HTSeq >= 0.7.2 numpy 1.14.3 pandas >=0.18.1 matplotlib 2.0.2 plink 1.9 Install time on desktop computer: < 5 minuters (depend on network conditions) ---------------------- Usage ---------------------- The small demo data are: junct_bed/*.bed : individual junction reads data in bed format generated using "junction extract" in regtools (https://regtools.readthedocs.io/en/latest/) toy.bed toy.bim toy.fam : genotype data generated using the --make-bed option in PLINK (HTTP://pngu.mgh.harvard.edu/~purcell/plink/). toy.geno : Customizing genotype data format including: CHROM:chromosome, POS:postion, ID:snp id, REF: reference allele, ALT: alternative allele, QUAL: quality same as in VCF, FILTER: filter type, INFO:information, EXP_FREQ_A1:reference allele frequency, MISS: missing, SampleID1, SampleID2, ..., SampleIDn". The python scripts for analysis are in the py folder: py/*.py Results of demo are in "result/" folder: result/ The detail analysis steps are all in the "pipline_run.sh" file. jsQTL analysis can be performed by calling sh pipline_run.sh in bash. It may take less than 2 minuters. jsQTL analysis test results are in "chrAll_SK_np_mw/" folder. The test p-value results are in "*.geno_gp_p.txt" files. jsQTL Fine-mapping results are in "tissue1_asj_chrAll_p0.01_n0.05_r2/" folder. Fine-mapping post-probability results are in "*_geno_gp_p_sorted_uniq_np_top95.txt" Run time for demo on desktop computer: < 2 minuters
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