Hey guys, I am trying new ways to speed up the Blasting process and have tried splitting my assembled transcriptome into small files and running a local blast with each one. I ran a sample file and it worked a lot faster than any other way I've tried, but I'm having a problem when attempting to load the output file into Blast2Go. Can anyone shed some light on the issue? I was hoping to run all the files, merge them all and load them up into Blast2Go fully blasted and ready to annotate. Thanks in advance for any help.
-
-
Surely people have used Blast+? -
Did you set the blast output to XML (-outfmt 5)?
Can you be more specific than "I'm having a problem when attempting to load the output file into Blast2Go."?Comment
-
No, i didn't enter that command. I have an output file named x after performing Blastx on a file containing contigs. I'm attempting to load the file into Blast2Go software but receive an error saying the file needs to be in gzip format. Will the -outfmt 5 setting allow me to do so?Originally posted by atcghelix View PostComment
-
Are you running Blast2GO locally? Or on a web server somewhere?
I was under the impression that you needed to feed Blast2GO a blast file that was output in XML format, but I may be wrong.Comment
-
nope, I think the only output it can handly is XML since it is the most stable one.Originally posted by atcghelix View PostComment
-
Gzip is a compression format that is separate from BLAST. You can convert your results file to gzip on the Linux or Mac command line, I'm sure there are also Windows tools.Originally posted by Shorash View PostComment
-
Hey,
This is what it work for me so far. Using blast+ or blastall with xml as output. When the number of query seqs is quite high, load them into blas2go takes too much time, so I use blas2gopipe. I'm still working on this workflow, where I have some issues connecting to the database (why blast2go have so many problems with that?). Anyway, if you are able to run it, it will generate a projectfile (.dat) which you can open with blas2go desktop and run the annotation.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...07-31-2026, 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