For use case 1 we obtained the following ENCODE and ROADMAP datasets https://www.encodeproject.org/files/ENCFF446WOD/@@download/ENCFF446WOD.bed.gz, https://www.encodeproject.org/files/ENCFF546PJU/@@download/ENCFF546PJU.bam, https://www.encodeproject.org/files/ENCFF059BEU/@@download/ENCFF059BEU.bam. Blacklisted regions were obtained from http://mitra.stanford.edu/kundaje/akundaje/release/blacklists/hg38-human/hg38.blacklist.bed.gz. The human genome version hg38 was obtained from http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz.

For use case 2 we used the set of narrowPeak files summarized in https://github.com/wkopp/janggu_usecases/tree/master/extra/urls.txt (archived version v1.0.1). The human genome version hg19 was obtained from http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.fa.gz

For use case 3 we used the ENCODE datasets https://www.encodeproject.org/files/ENCFF591XCX/@@download/ENCFF591XCX.bam, https://www.encodeproject.org/files/ENCFF736LHE/@@download/ENCFF736LHE.bigWig, https://www.encodeproject.org/files/ENCFF177HHM/@@download/ENCFF177HHM.bam as we as the GENCODE annotation v29 from ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_29/gencode.v29.annotation.gtf.gz.

Address of the bookmark: http://mitra.stanford.edu/

Local installation:

You can install Ribbon locally from Github by following the instructions here: https://github.com/MariaNattestad/Ribbon

Address of the bookmark: http://genomeribbon.com/

See http://mash.readthedocs.org for more information.

Address of the bookmark: https://github.com/marbl/Mash/releases

If you are interested in gene prediction, have a look at GenomeThreader.

Address of the bookmark: http://genometools.org/

Using AlignGraph

AlignGraph --read1 reads_1.fa --read2 reads_2.fa --contig contigs.fa --genome genome.fa --distanceLow distanceLow --distanceHigh distancehigh --extendedContig extendedContigs.fa --remainingContig remainingContigs.fa [--kMer k --insertVariation insertVariation --coverage coverage --part p --fastMap --ratioCheck --iterativeMap --misassemblyRemoval --resume]

Address of the bookmark: https://github.com/baoe/AlignGraph

➜ bloomfilter git:(master) ✗ swig -Wall -c++ -perl5 BloomFilter.i
➜ bloomfilter git:(master) ✗ g++ -c BloomFilter_wrap.cxx -I/home/urbe/anaconda3/lib/perl5/5.22.0/x86_64-linux-thread-multi/CORE/ -fPIC -Dbool=char -O3
BloomFilter_wrap.cxx:1892:30: fatal error: ../BloomFilter.hpp: No such file or directory
compilation terminated.
➜ bloomfilter git:(master) ✗ cd swig
➜ swig git:(master) ✗ g++ -c BloomFilter_wrap.cxx -I/home/urbe/anaconda3/lib/perl5/5.22.0/x86_64-linux-thread-multi/CORE/ -fPIC -Dbool=char -O3
In file included from BloomFilter_wrap.cxx:1877:0:
../BloomFilter.hpp: In member function ‘void BloomFilter::loadHeader(FILE*)’:
../BloomFilter.hpp:141:59: warning: ignoring return value of ‘size_t fread(void*, size_t, size_t, FILE*)’, declared with attribute warn_unused_result [-Wunused-result]
fread(&header, sizeof(struct FileHeader), 1, file);
^
➜ swig git:(master) ✗ g++ -Wall -shared BloomFilter_wrap.o -o BloomFilter.so -O3
➜ swig git:(master) ✗ cd ..
➜ bloomfilter git:(master) ✗ cd ..
➜ lib git:(master) ✗ cd ..
➜ bin git:(master) ✗ ./LINKS
Usage: ./LINKS [v1.8.6]
-f sequences to scaffold (Multi-FASTA format, required)
-s file-of-filenames, full path to long sequence reads or MPET pairs [see below] (Multi-FASTA/fastq format, required)
-m MPET reads (default -m 1 = yes, default = no, optional)
! DO NOT SET IF NOT USING MPET. WHEN SET, LINKS WILL EXPECT A SPECIAL FORMAT UNDER -s
! Paired MPET reads in their original outward orientation <- -> must be separated by ":"
>template_name
ACGACACTATGCATAAGCAGACGAGCAGCGACGCAGCACG:ATATATAGCGCACGACGCAGCACAGCAGCAGACGAC
-d distance between k-mer pairs (ie. target distances to re-scaffold on. default -d 4000, optional)
Multiple distances are separated by comma. eg. -d 500,1000,2000,3000
-k k-mer value (default -k 15, optional)
-t step of sliding window when extracting k-mer pairs from long reads (default -t 2, optional)
Multiple steps are separated by comma. eg. -t 10,5
-o offset position for extracting k-mer pairs (default -o 0, optional)
-e error (%) allowed on -d distance e.g. -e 0.1 == distance +/- 10% (default -e 0.1, optional)
-l minimum number of links (k-mer pairs) to compute scaffold (default -l 5, optional)
-a maximum link ratio between two best contig pairs (default -a 0.3, optional)
*higher values lead to least accurate scaffolding*
-z minimum contig length to consider for scaffolding (default -z 500, optional)
-b base name for your output files (optional)
-r Bloom filter input file for sequences supplied in -s (optional, if none provided will output to .bloom)
NOTE: BLOOM FILTER MUST BE DERIVED FROM THE SAME FILE SUPPLIED IN -f WITH SAME -k VALUE
IF YOU DO NOT SUPPLY A BLOOM FILTER, ONE WILL BE CREATED (.bloom)
-p Bloom filter false positive rate (default -p 0.001, optional; increase to prevent memory allocation errors)
-x Turn off Bloom filter functionality (-x 1 = yes, default = no, optional)
-v Runs in verbose mode (-v 1 = yes, default = no, optional)

Error: Missing mandatory options -f and -s.

ERROR fixed

perl: symbol lookup error: /home/urbe/Tools/LINKS_new/bin/./lib/bloomfilter/swig/BloomFilter.so: undefined symbol: Perl_Gthr_key_ptr

java -Xms2G -Xmx4G -jar GenomeFinisher.jar  \
    -i target_contigs.fasta  \
    -ds alternative_assemblies.fasta -ref reference.fasta  \
    -o outputDirectory

Address of the bookmark: http://gfinisher.sourceforge.net

Address of the bookmark: http://mitos.bioinf.uni-leipzig.de/index.py

Since ASCIIGenome does not require a graphical interface it is particularly useful for quickly visualizing genomic data on remote servers while offering flexibility similar to popular GUI viewers like IGV.

Documentation is at readthedocs/asciigenome.

Address of the bookmark: https://github.com/dariober/ASCIIGenome