In Linux you can download it with
wget http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz
and unzip it with
gunzip hg38.fa.gz
Then you have your fasta file.
For my RNA-Seq project, I need to download an entire (full) human genome from any individual. Can anyone provide a URL for a download to accomplish this?
I looked into the Personal Genomics Project (PGP) from Harvard, but I couldn't figure out how to download a full genome.
You can get it e.g. from UCSC: http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz
In Linux you can download it with
wget http://hgdownload.cse.ucsc.edu/goldenPath/hg38/bigZips/hg38.fa.gz
and unzip it with
gunzip hg38.fa.gz
Then you have your fasta file.
Thank you for your answer
Sorry is this a link for whole genome fasta for yeast please?
No it is for human genome as David already said above.
If you need yeast genome then use this link: http://hgdownload.soe.ucsc.edu/goldenPath/sacCer3/bigZips/chromFa.tar.gz
David has already provided the commands to download and unpack the file.
If you truly want a defined individual genome then you can get Dr. Craig Venter's: ftp://ftp.ncbi.nih.gov/pub/TraceDB/Personal_Genomics/Venter/
Additional resources: http://huref.jcvi.org/
The iGenomes project has reference genomes and reference transcriptome annotations that have been set up to support RNA-seq analysis:
http://cole-trapnell-lab.github.io/cufflinks//igenome_table/index.html
http://support.illumina.com/sequencing/sequencing_software/igenome.html
Illumina has generously provided a set of freely downloadable packages that contain everything you need to get started working with TopHat and Cufflinks. These packages contain Bowtie indexes for the human, mouse, and fly genomes as well as many others. The packages also contain annotation files (in GTF format) from UCSC, Ensembl, NCBI, and other sources. These files are augmented with the special attributes Cufflinks needs to perform differential splicing and promoter analysis. We strongly encourage users to download and try these packages!
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There are some great RNA-seq tutorials out there that start with the basics (like understanding reference genomes and transcriptomes). For example, http://www.rnaseq.wiki.