diff --git a/Dockerfile b/Dockerfile
index 6a74d2d..c2de092 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,14 +1,14 @@
-FROM ubuntu:latest as bioinformatics_base
+FROM ubuntu:20.04 as bioinformatics_base
#===============================#
# Docker Image Configuration #
#===============================#
-LABEL vendor="Englander Institute for Precision Medicine" \
- description="ERVmap" \
- maintainer="ans2077@med.cornell.edu" \
- base_image="ubuntu" \
- base_image_version="latest" \
- base_image_SHA256="sha256:fc04b2781f41f76c5b126ec26c0c0c26c7fc047318347a2112856253a88bb01d"
+LABEL org.opencontainers.image.source='https://github.com/eipm/ERVmap' \
+ vendor="Englander Institute for Precision Medicine" \
+ description="ERVmap" \
+ maintainer="ans2077@med.cornell.edu" \
+ base_image="ubuntu" \
+ base_image_version="20.04"
ENV APP_NAME="ERVmap" \
TZ='US/Eastern' \
@@ -19,7 +19,7 @@ RUN apt-get update \
&& apt-get upgrade -y --fix-missing \
&& apt-get install build-essential -y \
&& apt-get install -y \
- vim \
+ vim \
emacs \
bedtools \
wget \
@@ -58,7 +58,6 @@ RUN wget -O STAR-${STAR_VERSION}.tar.gz https://github.com/alexdobin/STAR/archiv
&& make STAR
RUN ln -s ${star_dir}/source/STAR /usr/local/bin/
-
#===========================#
# Production layer #
#===========================#
diff --git a/README.md b/README.md
index ae227d1..7f09a5f 100644
--- a/README.md
+++ b/README.md
@@ -1,21 +1,30 @@
# **ERVmap**
+
ERVmap is one part curated database of human proviral ERV loci and one part a stringent algorithm to determine which ERVs are transcribed in their RNA seq data.
-## Citation
+[](https://github.com/eipm/ERVmap/actions) [](https://github.com/eipm/ERVmap) [](https://hub.docker.com/repository/docker/eipm/ervmap) [](https://github.com/orgs/eipm/packages/container/package/ervmap)
+
+## Citation
+
Tokuyama M. et. al., ERVmap analysis reveals genome-wide transcription of human endogenous retroviruses. Proc Natl Acad Sci USA 2018 Dec 11;115(50):12565-12572. [doi: 10.1073/pnas.1814589115](http:/doi.org/10.1073/pnas.1814589115).
## **How to use it**
### Install
+
This version of the tool consists on 2 steps: 1. alignment to the human genome (GRC38) and 2. quantification of the ERV regions. To download and install ERVmap latest version provided as docker image, simply type:
-```
+
+```bash
docker pull eipm/ervmap:latest
```
+
**NOTE**: for a specific version replace `latest` with the release version.
### **How to run ERVmap**
+
To run ERVmap, you'd need: 1. an indexed genome reference for STAR; 2. A bed file with the curated ERV regions on the human genome (see `ERVmap.bed`); 3. the input FASTQ data (gzipped). Assuming that your sample is called `SAMPLE`, and has 2 FASTQ files (one per read) in the folder `/path/to/input/data`; the reference genome is in `/path/to/genome` and the ERV bed file is in `/path/to/erv/file` here is the command:
-```
+
+```bash
docker run --rm \
-u $(id -u):$(id -g) \
-v /path/to/input/data:/data:ro \
@@ -28,8 +37,10 @@ docker run --rm \
--output SAMPLE/SAMPLE. \
--mode ALL
```
+
This command will generate the alignment files (BAMs) in the `/path/to/output/SAMPLE/` folder and all files will have the prefix `SAMPLE.`. The generated files will be:
-```
+
+```bash
SAMPLE.Aligned.sortedByCoord.out.bam
SAMPLE.Aligned.sortedByCoord.out.bam.bai
SAMPLE.ERVresults.txt
@@ -38,9 +49,11 @@ SAMPLE.Log.out
SAMPLE.Log.progress.out
SAMPLE.SJ.out.tab
```
+
(See [STAR documentation](https://github.com/alexdobin/STAR) for the description of the output files of the STAR aligner ).
The results of ERV quantification will be in the `SAMPLE.ERVresults.txt` file. This is a tab-delimited file with 7 columns from [bedtools](https://bedtools.readthedocs.io/en/latest/). For example:
-```
+
+```bash
1 896176 898458 5803 500 + 70
1 1412251 1418852 5804 500 + 36
1 3801730 3806808 5807 500 + 6
@@ -48,32 +61,34 @@ The results of ERV quantification will be in the `SAMPLE.ERVresults.txt` file. T
```
## The **`--mode`** option
+
This option can only have 3 values: { `ALL`, `STAR`, `BED` }:
+
* `ALL` to run both the STAR aligner and the ERV quantification from start to finish;
* `STAR` to only perform the alignment;
* `BED` to only run the ERV quantification.
-
### <a id='optparam'></a>Optional parameters (*recommended*)
There are a few parameters that can be added to the ERVmap image to make the process more efficient.
+
* `--cpus 20`: if you have a multi-core system (and you should have one), you can specify the number of CPUs to use (e.g. 20);
-* `--limit-ram 48000000000`: this limits the amount of RAM used to avoid overusing the resources
+* `--limit-ram 48000000000`: this limits the amount of RAM used to avoid overusing the resources
You can see the full set of parameters by typing: `docker run --rm ervmap`.
-There are also other parameters from Docker that should be included before `ervmap` in the command line, e.g.
-```
+There are also other parameters from Docker that should be included before `ervmap` in the command line, e.g.
+
+```bash
--memory 50G \
--memory-swap 100G
-```
-
----
+```
-# Nextflow version
+## Nextflow version
To run this pipeline using [Nextflow](https://www.nextflow.io/), simply run the following:
`nextflow -C nextflow.config run main.nf`
where `nextflow.config` include the minimum set of parameters to run ERVmap within the docker container. Specifically:
-```
+
+```bash
params {
genome='/path/to/genome' # external path to the indexed genome for the STAR aligner
inputDir='path/to/input/folder' # external path of the input data
@@ -92,14 +107,15 @@ params {
----
-# Published version
+## Published version
Please note that the instructions hereafter refer to the orignal published version (see [ERVmap on GitHub](https://github.com/mtokuyama/ERVmap))
## **Installing**
### Install dependencies
-```
+
+```bash
bedtools2
cufflinks
bwa-0.7.17
@@ -112,7 +128,8 @@ trim (http://graphics.med.yale.edu/trim/)
```
### Install .pl and r files
-```
+
+```bash
erv_genome.pl
interleaved.pl
run_clean_htseq.pl
@@ -126,19 +143,22 @@ normalize_deseq.r
This step will yield raw counts for cellular genes and ERVmap loci as separate files.
-### For single-end sequences:
-```
+### For single-end sequences
+
+```bash
erv_genome.pl -stage 1 -stage2 6 -fastq /${i}_SS.fastq.gz
```
-### For pair-end sequences:
-```
+### For pair-end sequences
+
+```bash
interleaved.pl --read1 ${i}_R1.fastq.gz --read2 ${i}_R2.fastq.gz > ${i}.fastq.gz
erv_genome.pl -stage 1 -stage2 6 -fastq /${i}.fastq.gz
```
### Store output files
-```
+
+```bash
mkdir -p output
mv ./sample/herv_coverage_GRCh38_genome.txt ./output/erv/${i}.e
mv ./sample/GRCh38/htseq.cnt ./output/cellular/${i}.c
@@ -146,10 +166,10 @@ mv ./sample/GRCh38/htseq.cnt ./output/cellular/${i}.c
## **Clean up data, merge, and normalize**
-These steps will yield normalized ERV read counts based on size factors obtained through DESeq2 analysis.
-Use the output files from above.
+These steps will yield normalized ERV read counts based on size factors obtained through DESeq2 analysis.
+Use the output files from above.
-```
+```bash
run_clean_htseq.pl ./output/cellular c c2 __
merge_count.pl 3 6 e ./output/erv > ./output/erv/merged_erv.txt
merge_count.pl 0 1 c2 ./output/cellular > ./output/cellular/merged_cellular.txt
@@ -161,6 +181,3 @@ normalize_with_file.pl ./output/cellular/normalized_factors ./output/erv/merged_
* Maria Tokuyama
* Yong Kong
-
-
-