who are using Euler SR , can give some suggestions? i assembly 75bp reads with it .
-
provide my best services for you -
What questions do you have?Originally posted by xzk421 View Post -
A few recommendations for assembling Illumina reads with euler-sr:
1. Pre-filter for A-saturated reads:
$EUSRC/assembly/$MACHTYPE/filterIllumina reads.fasta reads.fasta.filt
2. Put all reads to assemble into one file. Every fasta title should be unique in this file.
3. If your reads are paired (and they are stored in a file reads.fasta), check the reads.fasta.mates to see if the regular expressions used to match reads worked. If no reads were matched, all entries will be "-1 -1".
4. Assembly quality varies with the following:
1. error rate
2. repeat content of the genome
3. coverage
To check to see if you had low coverage, or a very high error rate that fragmented the genome, run the graph summary program:
$EUSRC/assembly/$MACHTYPE/printGraphSummary matetransformed/reads.fasta -sources
This will print all the lengths of contigs that are fragmented due to low coverage or sequencing errors (probably low coverage). If this high relative to the number of contigs in the assembly, either use a smaller vertex size for assembly, or run more reads.Comment
-
CRISPR/Cas9 sparked the gene editing revolution for both research and therapeutics.1 But this system still showed severe issues that limited its applications. The most prominent were the heavy reliance on PAM sequences, delivery limitations, double-stranded breaks that prompt unintended edits and cell death, and editing inefficiency (both in targeting and in knock-in reliability).
Despite this, “CRISPR helped turn genome editing from a specialized technique into...Today, 11:01 AM -
Proteomics platforms are evolving rapidly, with advances in mass spectrometry and affinity-based approaches expanding what researchers can detect and at what scale. As the field moves toward deeper proteome coverage and clinical applications, scientists face an increasingly complex landscape of tools. This article will explore how researchers are navigating these choices to find the right platform for their work.
The systematic characterization of the human proteome has...07-20-2026, 11:48 AM -
Genomics studies in neuroscience face a special challenge due to the brain’s complexity and scarcity of samples. Mapping changes in cell type and state using conventional next-generation sequencing methods remains challenging. Advances in technologies like single-cell sequencing, spatial transcriptomics, and long-read sequencing have opened the door to deeper studies of the brain and diseases like Alzheimer’s, amyotrophic lateral sclerosis (ALS), and schizophrenia.
...07-09-2026, 11:10 AM
Comment