Thanks Ivan. actually i use the fastaFromBed utility finally, it runs very fast, i recommend for this tool:)
Best. On Tue, Aug 9, 2011 at 2:39 PM, Ivan Adzhubey < [email protected]> wrote: > Hi Daofeng, > > I suggest using nibFrag for this purpose. I found it generally faster > compared > to twoBitToFa since for each extraction operation it will only read (a much > smaller size) per chromosome nib file instead of a huge 2bit whole genome > one. > Also nibFrag would reverse-complement extracted sequence automatically when > strand=m while twoBitToFa does not have such option. > > The only downside is that you will need to convert downloaded chromosome > .fa.gz files to nib format (UCSC does not provide chromosomes in nib format > for > download). But you only have to do this once. > > Best, > Ivan > > On Tuesday, August 09, 2011 03:27:09 PM Daofeng Li wrote: > > Hi list members, > > > > Is there an effective way for extracting sequence from human genome hg19 > by > > coordinates? > > i have millions of start-end positions, might this huge amount of data > not > > suite for Table browser. > > I was think use the .2bit genome, any suggestions? > > i am also thing using following steps: > > > > ** > > > > * * > > > > *twoBitToFa* > > * > > > > twoBitToFa - Convert all or part of .2bit file to fasta > > > > usage: > > > > twoBitToFa input.2bit output.fa > > > > options: > > > > -seq=name - restrict this to just one sequence > > > > -start=X - start at given position in sequence (zero-based) > > > > -end=X - end at given position in sequence (non-inclusive) > > > > > > > > faToNib > > > > faToNib - Convert from .fa to .nib format > > > > usage: > > > > faToNib in.fa out.nib > > > > > > > > nibFrag > > > > nibFrag - Extract part of a nib file as .fa > > > > usage: > > > > nibFrag file.nib start end strand out.fa > > > > Is this would be the fast way? > > > > Thanks in advance. > > > > Best. > > * > _______________________________________________ > Genome maillist - [email protected] > https://lists.soe.ucsc.edu/mailman/listinfo/genome > -- Daofeng Li Postdoc Research Associate Department of Genetics Washington University in St.Louis School of Medicine 314-556-2832 _______________________________________________ Genome maillist - [email protected] https://lists.soe.ucsc.edu/mailman/listinfo/genome
