milospjanic

bigWigLiftOver

bigWigLiftOver will convert genomics coordinates of a bigwig file mapped to hg18 genome to the hg19 genome, via converting bigwig to bedgraph, and performing liftover, followed by conversion back of a bedgraph to bigwig.

ChIPSeqFPro

ChIPSeqFPro (beta) is a script for full processing of ChIPSeq data starting from fastq files. It performs fastqc quality control, mapping to the human genome hg19 or mouse mm10 using bwa, sam to bam conversion, peak calling with MACS, creates bigwig files from bam files using bam2bigwig.

chrPos2rsID

chrPos2rsID is a script to convert a list of genomics positions in a format: chrno_position_allele1_allele2 to SNP rsIDs. Script will append rsIDs as a column to an existing file. chrPos2rsID is useful for quick conversion of to SNP rsIDs for various downstream analysis and lookups.

fisherTestForGenomicOverlapsMilosPjanicMod

Combined bash/R script performs specialized Fisher's exact test and generates p-value that shows significance for the overlap of two sets of genomic regions. Statistical test includes genomic background i.e. combined ENCODE set of open chromatin regions to calculate constituents of the Fisher exact test contingency matrix.

GTExExtractor.2

GTExExtractor.2 is a script that will download and parse individual-level GTEx data set for all tissues and GTEx sample IDs. It will show the distribution of expression for a single gene in a multiple GTEx tissue that are selected by the user, and the script will automate this process for a list of input genes.

gwasanalytics

Gwasanalytics consists of a series of scripts that will analyze Gwas Catalog phenotypes and the input bed file from e.g. ChIP-Seq/ATAC-Seq experiment. Gwasanalytics scripts will calculate standard and modified binomial statistics, p-values and fold change for genomic overlaps between the input and various parsed GWAS categories.

IntegrativeFunctionalGenomics

Collection of scripts used in Miller and Pjanic et al, 2016, Nature Communications and Kim and Pjanic et al, 2017, Plos Genetics.

matrixeQTL2LocusZoom

Script will use three parameters as inputs, 1) Gene ID from ENSEMBL annotation, 2) chromosome number where the gene is located 3) eQTL file from matrixeQTL and generate output for visualization with LocusZoom Plot containing rsIDs and p-values as columns 1 and 2.

rnaSeqFPro

rnaSeqFPro (beta) is a script for full processing of RNASeq data starting from fastq files. It performs fastqc quality control, mapping to the human genome hg19 using STAR second pass, counting with featurecounts using GENCODE gtf annotation, creates master table, performs differential analysis using DESeq2, generates graphs in gglot2.

rsID2Bed

rsID2Bed is a script to convert SNP rsIDs to a list of genomics positions in a bed format: chr, position, position+1. Script is useful for quick conversion of SNPs to a bed format for downstream analysis (e.g. overlaps with bedtools).

milospjanic/rnaSeqFPro

rnaSeqFPro (beta) is a script for full processing of RNASeq data starting from fastq files. It performs fastqc quality control, mapping to the human genome hg19 using STAR second pass, counting with featurecounts using GENCODE gtf annotation, creates master table, performs differential analysis using DESeq2, generates graphs in gglot2.

milospjanic/gwasanalytics

Gwasanalytics consists of a series of scripts that will analyze Gwas Catalog phenotypes and the input bed file from e.g. ChIP-Seq/ATAC-Seq experiment. Gwasanalytics scripts will calculate standard and modified binomial statistics, p-values and fold change for genomic overlaps between the input and various parsed GWAS categories.

milospjanic/GTExExtractor.2

GTExExtractor.2 is a script that will download and parse individual-level GTEx data set for all tissues and GTEx sample IDs. It will show the distribution of expression for a single gene in a multiple GTEx tissue that are selected by the user, and the script will automate this process for a list of input genes.

milospjanic/bigWigLiftOver

bigWigLiftOver will convert genomics coordinates of a bigwig file mapped to hg18 genome to the hg19 genome, via converting bigwig to bedgraph, and performing liftover, followed by conversion back of a bedgraph to bigwig.

milospjanic/fisherTestForGenomicOverlapsMilosPjanicMod

Combined bash/R script performs specialized Fisher's exact test and generates p-value that shows significance for the overlap of two sets of genomic regions. Statistical test includes genomic background i.e. combined ENCODE set of open chromatin regions to calculate constituents of the Fisher exact test contingency matrix.

milospjanic/PolygenicScoreCAD

PolygenicScoreCAD is a bash/awk/R script for defining causality of a gene for coronary artery disease given the directionality of expression change in HCASMC with the increased global polygenic risk score. Script uses CAD GWAS data (Nelson et al.) and HCASMC eQTL data for regression analysis.

milospjanic/ChIPSeqCompare

ChIPSeqCompare is a combined bash/R script that compares two ChIPSeq data sets, calculates overlapping regions and provides distributions of normalized fold change for overlapping binding sites. It outputs a normalized fold change correlation plot indicating either synergistic or antagonistic binding of two factors, or absence of interaction.

milospjanic/findLDSNPs

findLDSNPs is a bash/mySQL/awk script to obtain SNPs that are in linkage disequilibrium (LD) with the input list of SNPs using a user defined R2 or dprime value in user defined window around the SNP location. LD calculation is based on 1000Genomes phase 3 phased genomes.

milospjanic/GeneCausalityTestCAD

GeneCausalityTest for CAD (coronary artery disease) is a bash/awk/R script for defining causality of a gene for a given trait, in this case CAD, given the directionality of expression change with the increasing number of risk SNPs. Script uses CAD GWAS data (Nelson et al.) and HCASMC eQTL data for regression analysis.

milospjanic/SingleCellPCAplotMultiGene

SingleCellPCAplotMultiGene is an R script for the principal component analysis of single cell RNAseq data. The script will start from the processed mastertable with RPKM values and perform PCA clustering and highlight in a gradient scale the ratio of expression of the 2 genes of interest (provided as the first and second arguments).

milospjanic/chrPos2rsIDdbSNP147CommonPlusRareVariants

This is a script to convert a list of genomics positions in a format: chrno_position_allele1_allele2 to SNP rsIDs, using dbSNP147 all SNP (common plus rare) data set from UCSC Table Browser. Script will append rsIDs as a column to an existing file.

milospjanic/DNAPalindromeRevPalindrome

Python script to check if DNA sequence is palindrome or reverse palindrome

milospjanic/gwasCatalog2Bed2Category

Download GWAS Catalog, convert it to a bed file with "chr position position+1 proxy_gene phenotype", and then take input terms and select entries that match the term, and create separate bed files.

milospjanic/HCASMCeQTLviewer

HCASMCeQTLviewer is a combined bash/R/awk script to view eQTL box/dot plots for a specific gene/SNP cis and trans eQTL association in human coronary artery smooth muscle cells, one of the crucial cell types that are involved in atherosclerotic process of the blood vessel.

milospjanic/indelsconverterdbSNP150

chrN:position:I or chrN:position:D to SNP rsIDs, using dbSNP150 all SNP (common plus rare) data set from UCSC Table Browser. Script will append rsIDs as a column to an existing file.

milospjanic/UniqueHaplotypeTestCAD

UniqueHaplotypeTestCAD is a version of GeneCausalityTest for coronary artery disease that resolves local haplotype structure and averages on samples with unique haplotype structure. The script improves correlations made by GeneCausalityTest for defining causality of a gene for CAD, especially in the local regions of strong linkage disequilibrium. The script outputs the directionality of expression change with the increasing number of risk SNPs and uses CAD GWAS data (Nelson et al.) and HCASMC eQTL data for regression analysis.

milospjanic/bed2GwasCatalogBinomial

Script will download GWAS Catalog, create bed file, parse and uniq with N-1 input arguments. Last argument provided should be a bed file that will be intersected with parsed GWAS Catalog. Number of overlaps and initial number of entries in parsed files are reported. Finally, it will calculate binomial p-values for each overlap.

milospjanic/bed2GwasCatalogBinomialMod1

This is a modified version of bed2GwasCatalogBinomial script and it calculates binomial p-value for genomics overlaps using modified binomial probability. This script will download GWAS Catalog, parse to bed files using input terms, intersects parsed GWAS Catalog with input bed file, calculates modified binomial statistics for each overlap.

milospjanic/DNAcomplement

milospjanic/DNAreverse

milospjanic/DNAreversecomplement

milospjanic/FibonacciDictionary

milospjanic/FibonacciLoop

Python script for printing Fibonacci sequence numbers. up to n-th term where n is provided by the user, using looping

milospjanic/FibonacciRecursion

Python script for printing Fibonacci sequence numbers. up to n-th term where n is provided by the user, using recursion

milospjanic/Files2uniqrecords

milospjanic/gwasCatalog2BedParse

Parse complete GWAS Catalog into unique categories and create bed files. Script will connect to genome.gov, download GWAS Catalog, convert it to a bed file with columns chr;position;position+1;proxy_gene;phenotype, and then create separate bed files for each unique GWAS Catalog category from 5th column.

milospjanic/gwasCatalogFullParseBinomialMod1Ggplot

Script downloads GWAS Catalog, converts it into bed file with columns: chr position position+1 proxy_gene phenotype, then fully parses GWAS Cat. for each unique category, performs modified binomial statistics on overlaps with the input file. Outputs are tables with binomial -log10pvalues and fold changes and graphs in ggplot2.

milospjanic/lncRNADiscoveryPipeline

Beta

milospjanic/VCF_allele_frequency_calc

milospjanic/wig2BigWigLiftOverBedgraphPartition

This is a combined bash/perl script that will convert genomics coordinates of a wig file mapped to hg18 genome to the hg19 genome, via converting wig ti bigwig, bigwig to bedgraph, and performing liftover, followed by partitioning the structure of overlapping intervals in a bedgraph file and conversion back of a bedgraph to bigwig.