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Motif estiamtion #12

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50 changes: 23 additions & 27 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -7,38 +7,16 @@ For further information read the [documentation](https://github.molgen.mpg.de/lo
## Dependencies
* [conda](https://conda.io/docs/user-guide/install/linux.html)
* [Nextflow](https://www.nextflow.io/)
* [MEME-Suite](http://meme-suite.org/doc/install.html?man_type=web)

## Installation
Start with installing all dependencies listed above. It is required to set the [enviroment paths for meme-suite](http://meme-suite.org/doc/install.html?man_type=web#installingtar).
this can be done with following commands:
```
export PATH=[meme-suite instalation path]/libexec/meme-[meme-suite version]:$PATH
export PATH=[meme-suite instalation path]/bin:$PATH
```

Start with installing all dependencies listed above (Nextflow, conda) and downloading all files from the [GitHub repository](https://github.molgen.mpg.de/loosolab/masterJLU2018).

Download all files from the [GitHub repository](https://github.molgen.mpg.de/loosolab/masterJLU2018).
The Nextflow-script needs a conda enviroment to run. Nextflow can create the needed enviroment from the given yaml-file.
On some systems Nextflow exits the run with following error:
```
Caused by:
Failed to create Conda environment
command: conda env create --prefix --file env.yml
status : 143
message:
```
If this error occurs you have to create the enviroment before starting the pipeline.
To create this enviroment you need the yml-file from the repository.
Run the following commands to create the enviroment:
```console
path=[Path to given masterenv.yml file]
conda env create --name masterenv -f=$path
```
When the enviroment is created, set the variable 'path_env' in the configuration file as the path to it.
Every other dependency will be automatically installed by Nextflow using conda. For that a new conda enviroment will be created, which can be found in the from Nextflow created work directory after the first pipeline run.
It is **not** required to create and activate the enviroment from the yaml-file beforehand.

**Important Note:** For conda the channel bioconda needs to be set as highest priority! This is required due to two differnt packages with the same name in different channels. For the pipeline the package jellyfish from the channel bioconda is needed and **NOT** the jellyfisch package from the channel conda-forge!


## Quick Start
```console
nextflow run pipeline.nf --bigwig [BigWig-file] --bed [BED-file] --genome_fasta [FASTA-file] --motif_db [MEME-file] --config [UROPA-config-file]
Expand Down Expand Up @@ -105,6 +83,24 @@ Optional arguments:
All arguments can be set in the configuration files
```

For further information read the [documentation](https://github.molgen.mpg.de/loosolab/masterJLU2018/wiki)

## Known issues
The Nextflow-script needs a conda enviroment to run. Nextflow creates the needed enviroment from the given yaml-file.
On some systems Nextflow exits the run with following error:
```
Caused by:
Failed to create Conda environment
command: conda env create --prefix --file env.yml
status : 143
message:
```
If this error occurs you have to create the enviroment before starting the pipeline.
To create this enviroment you need the yml-file from the repository.
Run the following commands to create the enviroment:
```console
path=[Path to given masterenv.yml file]
conda env create --name masterenv -f $path
```
When the enviroment is created, set the variable 'path_env' in the configuration file as the path to it.

For further information read the [documentation](https://github.molgen.mpg.de/loosolab/masterJLU2018/wiki)
116 changes: 58 additions & 58 deletions bin/bed_to_fasta.R
Original file line number Diff line number Diff line change
@@ -1,58 +1,58 @@
#!/usr/bin/env Rscript
library("optparse")

option_list <- list(
make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input bed-file. Second last column must be sequences and last column must be the cluster_id.", metavar = "character"),
make_option(opt_str = c("-p", "--prefix"), default = "" , help = "Prefix for file names. Default = '%default'", metavar = "character"),
make_option(opt_str = c("-m", "--min_seq"), default = 100, help = "Minimum amount of sequences in clusters. Default = %default", metavar = "integer")
)

opt_parser <- OptionParser(option_list = option_list,
description = "Convert BED-file to one FASTA-file per cluster")

opt <- parse_args(opt_parser)

#' Splitting BED-files depending on their cluster.
#' The Sequences of each cluster are writen as an FASTA-file.
#' @param bedInput <string> BED-file with sequences and cluster-id as last two columns:
#' Sequence: second last column; Cluster ID: last column
#' @param prefix <string> prefix for filenames
#' @param min_seq <INT> min. number of sequences per cluster
#'
#' @author René Wiegandt
#' @contact rene.wiegandt(at)mpi-bn.mpg.de
bed_to_fasta <- function(bedInput, prefix = "", min_seq = 100){

if(is.null(bedInput)){
stop("ERROR: Input parameter cannot be null! Please specify the input parameter.")
}

bed <- data.table::fread(bedInput, header = FALSE, sep = "\t")

# Get last column of data.table, which refers to the cluster, as a vector.
cluster_no <- as.vector(bed[[ncol(bed)]])

# Split data.table bed on its last column (cluster_no) into list of data.frames
clusters <- split(bed, cluster_no, sorted = TRUE, flatten = FALSE)

# For each data.frame(cluster) in list clusters:
discard <- lapply(1:length(clusters), function(i){
clust <- as.data.frame(clusters[i])
# Filter data.tables(clusters), which are to small
if (nrow(clust) >= as.numeric(min_seq) ) {
# Get second last column, which contains the nucleotide sequences
sequences <- as.list(clust[[ncol(clust) - 1]])
# Create filename
outfile <- paste0(prefix,"_cluster_",i - 1,".FASTA")
# Write fasta file
seqinr::write.fasta(sequences = sequences, names = clust[[4]], file.out = outfile, as.string = TRUE)
} else {
print(paste0("Cluster: ",i," is to small"))
}
})
}

# run function bed_to_fasta with given parameteres if not in interactive context (e.g. run from shell)
if (!interactive()) {
bed_to_fasta(opt$input, opt$prefix, opt$min_seq)
}
#!/usr/bin/env Rscript
library("optparse")

option_list <- list(
make_option(opt_str = c("-i", "--input"), default = NULL, help = "Input bed-file. Second last column must be sequences and last column must be the cluster_id.", metavar = "character"),
make_option(opt_str = c("-p", "--prefix"), default = "" , help = "Prefix for file names. Default = '%default'", metavar = "character"),
make_option(opt_str = c("-m", "--min_seq"), default = 100, help = "Minimum amount of sequences in clusters. Default = %default", metavar = "integer")
)

opt_parser <- OptionParser(option_list = option_list,
description = "Convert BED-file to one FASTA-file per cluster")

opt <- parse_args(opt_parser)

#' Splitting BED-files depending on their cluster.
#' The Sequences of each cluster are writen as an FASTA-file.
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#' @param bedInput <string> BED-file with sequences and cluster-id as last two columns:
#' Sequence: second last column; Cluster ID: last column
#' @param prefix <string> prefix for filenames
#' @param min_seq <INT> min. number of sequences per cluster
#'
#' @author René Wiegandt
#' @contact rene.wiegandt(at)mpi-bn.mpg.de
bed_to_fasta <- function(bedInput, prefix = "", min_seq = 100){

if (is.null(bedInput)) {
stop("ERROR: Input parameter cannot be null! Please specify the input parameter.")
}

bed <- data.table::fread(bedInput, sep = "\t")

# Get last column of data.table, which refers to the cluster, as a vector.
cluster_no <- as.vector(bed[[ncol(bed)]])

# Split data.table bed on its last column (cluster_no) into list of data.frames
clusters <- split(bed, cluster_no, sorted = TRUE, flatten = FALSE)

# For each data.frame(cluster) in list clusters:
discard <- lapply(1:length(clusters), function(i){
clust <- as.data.frame(clusters[i])
# Filter data.tables(clusters), which are to small
if (nrow(clust) >= as.numeric(min_seq) ) {
# Get second last column, which contains the nucleotide sequences
sequences <- as.list(clust[[ncol(clust) - 1]])
# Create filename
outfile <- paste0(prefix,"_cluster_",i - 1,".FASTA")
# Write fasta file
seqinr::write.fasta(sequences = sequences, names = clust[[4]], file.out = outfile, as.string = TRUE)
} else {
print(paste0("Cluster: ",i," is to small"))
}
})
}

# run function bed_to_fasta with given parameteres if not in interactive context (e.g. run from shell)
if (!interactive()) {
bed_to_fasta(opt$input, opt$prefix, opt$min_seq)
}
8 changes: 4 additions & 4 deletions bin/get_best_motif.py
Original file line number Diff line number Diff line change
Expand Up @@ -11,11 +11,11 @@ def parse_arguments():
return args

'''
The script has to functions:
The script has two functions:
1. Writing lines of file till certain line (MOTIF + [num])
2. Converting GLAM2 output to minimal meme-format
@params meme STING Path to 'meme' file generated from Meme suite
@parmas output STING Output file
@params meme STRING Path to 'meme' file generated from Meme suite
@parmas output STRING Output file
@params num INT Number of motifs parsed from file

@author René Wiegandt
Expand All @@ -25,7 +25,7 @@ def main():

args = parse_arguments()
out = open(args.output, "w+")

'''
Create pattern where script should stop writing
For Example:
Expand Down
1 change: 0 additions & 1 deletion masterenv.yml
Original file line number Diff line number Diff line change
Expand Up @@ -14,7 +14,6 @@ dependencies:
- r-stringr
- r-optparse
- bioconductor-iranges
- snakemake
- meme
- moods
- biopython
Expand Down
23 changes: 17 additions & 6 deletions pipeline.nf
Original file line number Diff line number Diff line change
Expand Up @@ -9,6 +9,7 @@
params.tfbs_path=""
params.create_known_tfbs_path = "./"
params.help = 0
params.get_path=""
params.out = "./out/"

//peak_calling
Expand Down Expand Up @@ -55,10 +56,10 @@
params.best_motif = 3 // Top n motifs per cluster

//creating_gtf
params.organism="hg38"
params.organism=""
params.tissue=""

if (params.bigwig == "" || params.bed == "" || params.genome_fasta == "" || params.motif_db == "" || params.config == "" || "${params.help}" != "0"){
if (params.bigwig == "" || params.bed == "" || params.organism == "" || params.genome_fasta == "" || params.motif_db == "" || params.config == "" || "${params.help}" != "0"){
log.info """
Usage: nextflow run pipeline.nf --bigwig [BigWig-file] --bed [BED-file] --genome_fasta [FASTA-file] --motif_db [MEME-file] --config [UROPA-config-file]
Expand All @@ -68,14 +69,16 @@ Required arguments:
--genome_fasta Path to genome in FASTA-format
--motif_db Path to motif-database in MEME-format
--config Path to UROPA configuration file
--create_known_tfbs_path Path to directory where output from tfbsscan (known motifs) are stored.
Path can be set as tfbs_path in next run. (Default: './')
--organism Input organism [hg38 | hg19 | mm9 | mm10]
--out Output Directory (Default: './out/')
Optional arguments:
--help [0|1] 1 to show this help message. (Default: 0)
--tfbs_path Path to directory with output from tfbsscan. If given tfbsscan will not be run.
--create_known_tfbs_path Path to directory where output from tfbsscan (known motifs) are stored.
Path can be set as tfbs_path in next run. (Default: './')
--gtf_path Path to gtf-file. If path is set the process which creats a gtf-file is skipped.
Footprint extraction:
--window_length INT This parameter sets the length of a sliding window. (Default: 200)
Expand Down Expand Up @@ -115,7 +118,6 @@ Optional arguments:
--motif_similarity_thresh FLOAT Threshold for motif similarity score (Default: 0.00001)
Creating GTF:
--organism [hg38 | hg19 | mm9 | mm10] Input organism
--tissues List/String List of one or more keywords for tissue-/category-activity, categories must be specified as in JSON
config
All arguments can be set in the configuration files
Expand Down Expand Up @@ -578,14 +580,23 @@ process create_GTF {
publishDir "${params.out}/gtf/", mode: 'copy'

output:
file ('*.gtf') into gtf_for_uropa
file ('*.gtf') into gtf

when:
gtf_path == ""

script:
"""
python ${path_bin}/RegGTFExtractor.py ${params.organism} --tissue ${params.tissues} --wd ${path_bin}
"""
}

if (gtf_path == "") {
gtf_for_uropa = gtf
} else {
gtf_for_uropa = Channel.fromPath(params.gtf_path)
}

/*
bed_for_final_filter.combine(gtf_for_uropa).set {uropa_in}
Expand Down