Added installation guide in README (5df3677e) · Commits · github_fork / ZUMIs

ExampleData/barcoderead_HEK.1mio.fq.gz

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ExampleData/cDNAread_HEK.1mio.fq.gz

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README.md

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		@@ -8,6 +8,54 @@ The input to this pipeline is paired-end fastq files, where one read contains th

		You can read more about zUMIs in our [biorxiv preprint](http://www.biorxiv.org/content/early/2017/06/22/153940)!

		## Installation
		zUMIs is a wrapper around shell using scripts written in perl, shell and R. zUMIs can be installed by cloning and installing the dependencies as given below.

		```
		git clone https://github.com/sdparekh/zUMIs.git

		```

		### Dependencies
		#### General
		- [samtools :wrench:](http://samtools.sourceforge.net/)
		- [STAR :star2:](https://github.com/alexdobin/STAR)
		- [R :computer:](https://www.r-project.org/)
		- [pigz :pig:](http://zlib.net/pigz/)

		#### R
		To install R dependencies, please run the following:

		```R
		ipak <- function(pkg, repository = c("CRAN", "Bioconductor", "github")) {
		new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
		if (length(new.pkg)) {
		if (repository == "CRAN") {
		install.packages(new.pkg, dependencies = TRUE)
		}
		if (repository == "Bioconductor") {
		source("https://bioconductor.org/biocLite.R")
		biocLite(new.pkg, dependencies = TRUE, ask = FALSE)
		}
		if (repository == "github") {
		devtools::install_github(pkg, build_vignettes = FALSE)
		}
		}
		}

		#CRAN packages
		cranpackages <- c("dplyr","tidyr","parallel","reshape2","data.table","optparse","cowplot","pastecs")
		ipak(cranpackages, repository = "CRAN")

		# BIOCONDUCTOR packages
		biocpackages <- c("AnnotationDbi","Rsubread","GenomicRanges","GenomicFeatures","GenomicAlignments")
		ipak(biocpackages, repository = "Bioconductor")

		# GITHUB packages
		githubpackages <- c("hadley/multidplyr")
		ipak(githubpackages, repository = "github")

		```

		## Usage example

		@@ -16,7 +64,6 @@ bash zUMIs-master.sh -f barcoderead.fastq -r cdnaread.fastq -n test -g hg38_STAR

		```


		## Input keys

		### Required parameters
		@@ -86,47 +133,6 @@ As an example, data with many splice junctions (eg at sequencing depths >500M re
		-x "--limitOutSJcollapsed 2000000 --limitSjdbInsertNsj 2000000"
		```

		## Dependencies
		### General
		- [samtools :wrench:](http://samtools.sourceforge.net/)
		- [STAR :star2:](https://github.com/alexdobin/STAR)
		- [R :computer:](https://www.r-project.org/)
		- [pigz :pig:](http://zlib.net/pigz/)

		### R
		To install R dependencies, please run the following:

		```R
		ipak <- function(pkg, repository = c("CRAN", "Bioconductor", "github")) {
		new.pkg <- pkg[!(pkg %in% installed.packages()[, "Package"])]
		if (length(new.pkg)) {
		if (repository == "CRAN") {
		install.packages(new.pkg, dependencies = TRUE)
		}
		if (repository == "Bioconductor") {
		source("https://bioconductor.org/biocLite.R")
		biocLite(new.pkg, dependencies = TRUE, ask = FALSE)
		}
		if (repository == "github") {
		devtools::install_github(pkg, build_vignettes = FALSE)
		}
		}
		}

		#CRAN packages
		cranpackages <- c("dplyr","tidyr","parallel","reshape2","data.table","optparse","cowplot","pastecs")
		ipak(cranpackages, repository = "CRAN")

		# BIOCONDUCTOR packages
		biocpackages <- c("AnnotationDbi","Rsubread","GenomicRanges","GenomicFeatures","GenomicAlignments")
		ipak(biocpackages, repository = "Bioconductor")

		# GITHUB packages
		githubpackages <- c("hadley/multidplyr")
		ipak(githubpackages, repository = "github")

		```

		## Output

		zUMIs' output is structured in three subdirectories:
		@@ -158,6 +164,7 @@ zUMIs is compatible with these single-cell UMI protocols:
		- DroNc-seq (Habib et al., 2017)
		- SPLiT-seq (Rosenberg et al., 2017)
		- STRT-2i (Hochgerner et al., 2017)
		- Quartz-seq2 (Sasagawa et al., 2017)

		For InDrops compatibility, users need to preprocess the barcode and UMI read because of variable length cell barcodes.

_config.yml

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zUMIs-dge.R

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		@@ -40,7 +40,7 @@ opt = parse_args(opt_parser);

		print("I am loading useful packages...")
		print(Sys.time())
		packages <-c("multidplyr","dplyr","tidyr","reshape2","data.table","optparse","parallel","Rsubread","methods","GenomicRanges","GenomicFeatures","GenomicAlignments","AnnotationDbi","ggplot2","cowplot","tibble","pastecs")
		packages <-c("multidplyr","dplyr","tidyr","reshape2","data.table","optparse","parallel","Rsubread","methods","GenomicRanges","GenomicFeatures","GenomicAlignments","AnnotationDbi","ggplot2","cowplot","tibble")
		paks<-lapply(packages, function(x) suppressMessages(require(x, character.only = TRUE)))
		rm(paks)

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