BOL: Related items

PRICE (Paired-Read Iterative Contig Extension), a de novo genome assembler implemented in C++.

Surabhi Chaudhary — Mon, 11 Jun 2018 03:08:26 -0500

We are pleased to release PRICE (Paired-Read Iterative Contig Extension), a de novo genome assembler implemented in C++. Its name describes the strategy that it implements for genome assembly: PRICE uses paired-read information to iteratively increase the size of existing contigs. Initially, those contigs can be individual reads from a subset of the paired-read dataset, non-paired reads from sequencing technologies that provide non-paired data, or contigs that were output from a prior run of PRICE or any other assembler. http://derisilab.ucsf.edu/software/price/

Address of the bookmark: http://derisilab.ucsf.edu/software/price/

The Extensive de novo TE Annotator (EDTA)

Abhimanyu Singh — Thu, 08 Aug 2019 04:05:36 -0500

The EDTA package was designed to filter out false discoveries in raw TE candidates and generate a high-quality non-redundant TE library for whole-genome TE annotations. Selection of initial search programs were based on benckmarkings on the annotation performance using a manually curated TE library in the rice genome.

Address of the bookmark: https://github.com/oushujun/EDTA

LAMSA: fast split read alignment with long approximate matches

Jit — Tue, 15 May 2018 04:44:42 -0500

LAMSA (Long Approximate Matches-based Split Aligner) is a novel split alignment approach with faster speed and good ability of handling SV events. It is well-suited to align long reads (over thousands of base-pairs). LAMSA takes takes the advantage of the rareness of SVs to implement a specifically designed two-step strategy. That is, LAMSA initially splits the read into relatively long fragments and co-linearly align them to solve the small variations or sequencing errors, and mitigate the effect of repeats. The alignments of the fragments are then used for implementing a sparse dynamic programming (SDP)-based split alignment approach to handle the large or non-co-linear variants. We benchmarked LAMSA with simulated and real datasets having various read lengths and sequencing error rates, the results demonstrate that it is substantially faster than the state-of-the-art long read aligners; mean-while, it also has good ability to handle various categories of SVs. LAMSA is open source and free for non-commercial use. LAMSA is mainly designed by Bo Liu & Yan Gao and developed by Yan Gao in Center for Bioinformatics, Harbin Institute of Technology, China.

Address of the bookmark: https://github.com/hitbc/LAMSA

TULIP - The Uncorrected Long read Itegration Pipeline

Jit — Thu, 23 Nov 2017 09:30:01 -0600

#Running TULIP (The Uncorrected Long-read Integration Process), version 0.4 late 2016 (European eel)

TULIP currently consists of to Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow.
Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures. Tulipbulb adds long read sequencing data to these.

https://github.com/Generade-nl/TULIP

Address of the bookmark: https://github.com/Generade-nl/TULIP

TULIP - The Uncorrected Long read Integration Pipeline

Jit — Tue, 15 May 2018 09:06:37 -0500

TULIP currently consists of two Perl scripts, tulipseed.perl and tulipbulb.perl. These are very much intended as prototypes, and additional components and/or implementations are likely to follow. Tulipseed takes as input alignments files of long reads to sparse short seeds, and outputs a graph and scaffold structures.

Address of the bookmark: https://github.com/Generade-nl/TULIP

Run miniasm assembler on nanopore reads !

Jit — Mon, 18 Dec 2017 04:07:50 -0600

Miniasm is a very fast OLC-based de novo assembler for noisy long reads. It takes all-vs-all read self-mappings (typically by minimap) as input and outputs an assembly graph in the GFA format. Different from mainstream assemblers, miniasm does not have a consensus step. It simply concatenates pieces of read sequences to generate the final unitig sequences. Thus the per-base error rate is similar to the raw input reads.

Find the detail of the reads repeats:

fq2fa ONT_A.fastq ONT_A.fasta

minimap2 -xava-ont ONT_A.fasta ONT_A.fasta -t10 -X > AONT.paf

awk '{if($1==$6){print}}' AONT.paf > AONTself.paf

awk '$5=="-"' AONTself.paf | awk '{print $1}'| sort|uniq > invertedrepeat.list

Generated a few palindrome and repeats plots (highlighting only repeats largest than 10, 20 and 30 kb)

minidot -f 5 -m 30000 AONTself.paf > AONTself30000.eps
sed 's/_template_pass_FAH31515//' AONTself30000.eps > AONTself30000final.eps

minidot -f 5 -m 20000 AONTself.paf > AONTself20000.eps
sed 's/_template_pass_FAH31515//' AONTself20000.eps > AONTself20000final.eps

minidot -f 5 -m 10000 AONTself.paf > AONTself10000.eps
sed 's/_template_pass_FAH31515//' AONTself10000.eps > AONTself10000final.eps

Assemble with miniasm:

miniasm -f ONT_A.fasta AONT.paf > AONT.gfa
grep '^S' AONT.gfa |awk '{print ">"$2"\n"$3}' > AONT_miniasm.fasta

minimap2 -xasm10 AONT_miniasm.fasta AONT_miniasm.fasta -t1 -X > AONT_miniasm.paf

awk '{if($1==$6){print}}' AONT_miniasm.paf > AONT_miniasm_self.paf

minidot -f 5 -m 10000 AONT_miniasm_self.paf > AONT_miniasm_self10000.eps

Njoy the assembly !

TAREAN: A computational tool for identification and characterization of satellite DNA from unassembled short reads

Surabhi Chaudhary — Tue, 15 May 2018 02:53:11 -0500

TAndem REpeat ANalyzer -TAREAN – is a computational pipeline for unsupervised identification of satellite repeats from unassembled sequence reads. The pipeline uses low-pass whole genome sequence reads and performs their graph-based clustering. Resulting clusters, representing all types of repeats, are then examined for the presence of circular structures and putative satellite repeats are reported.

How to use TAREAN:

Install a local instance of the pipeline using its source code available from bitbucket repository.
Use public Galaxy-based server at https://repeatexplorer-elixir.cerit-sc.cz/. The server is provided in frame of the Elixir CZ project and is maintained by CESNET and CERIT-SC. Simple registration is required to use this service.

Development of TAREAN was supported by ELIXIR CZ research infrastructure project (MEYS Grant No: LM2015047).

References

Novak, P., Avila Robledillo, L., Koblizkova, A., Vrbova, I., Neumann, P., Macas, J. (2017) – TAREAN: a computational tool for identification and characterization of satellite DNA from unassembled short reads. Nucleic Acids Res., doi:10.1093/nar/gkx257

Address of the bookmark: https://bitbucket.org/petrnovak/repex_tarean

BlasR Mapping single molecule sequencing reads using Basic Local Alignment with Successive Refinement (BLASR): Theory and Application,

Jit — Wed, 23 May 2018 06:54:32 -0500

BLASR (Basic Local Alignment with Successive Refinement) for mapping Single Molecule Sequencing (SMS) reads that are thousands to tens of thousands of bases long with divergence between the read and genome dominated by insertion and deletion error.

Here is how I use the blasr to align PacBio reads to the contigs (target.fasta). The “target.fasta.sa” is the suffix array from “target.fasta” generated by sawriter.

blasr query.fa ./target.fasta -sa ./target.fasta.sa -bestn 40 -maxScore -500 -m 4 -nproc 24 -out target.m4 -maxLCPLength 15

the output format option “-m 4″ generate the alignment coordinate. Not fully documented, but I can explain that to you.

I use a 24 cores / 48G ram server for the alignment. It took about 2 to 3 hours aligning 3G PacBio Reads to 10^6 sequences of short read contigs with a mean 3.5kbp length.

Address of the bookmark: http://bix.ucsd.edu/projects/blasr/

npScarf: real-time scaffolder using SPAdes contigs and Nanopore sequencing reads

Shruti Paniwala — Mon, 11 Jun 2018 05:14:57 -0500

npScarf (jsa.np.npscarf) is a program that connect contigs from a draft genomes to generate sequences that are closer to finish. These pipelines can run on a single laptop for microbial datasets. In real-time mode, it can be integrated with simple structural analyses such as gene ordering, plasmid forming.

Address of the bookmark: http://japsa.readthedocs.io/en/latest/tools/jsa.np.npscarf.html

SimLoRD: A read simulator for third generation sequencing reads

Aaryan Lokwani — Wed, 22 Aug 2018 10:40:27 -0500

SimLoRD is a read simulator for third generation sequencing reads and is currently focused on the Pacific Biosciences SMRT error model.

Reads are simulated from both strands of a provided or randomly generated reference sequence.

The reference can be read from a FASTA file or randomly generated with a given GC content. It can consist of several chromosomes, whose structure is respected when drawing reads. (Simulation of genome rearrangements may be incorporated at a later stage.)
The read lengths can be determined in four ways: drawing from a log-normal distribution (typical for genomic DNA), sampling from an existing FASTQ file (typical for RNA), sampling from a a text file with integers (RNA), or using a fixed length
Quality values and number of passes depend on fragment length.
Provided subread error probabilities are modified according to number of passes
Outputs reads in FASTQ format and alignments in SAM format

Address of the bookmark: https://bitbucket.org/genomeinformatics/simlord/