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Originally posted by Torst View PostThe Intel i7 (Nehalem) processors have another advantage. The SSE2 SIMD pipeline is full width, whereas in previous Core2 CPUs it was half width. This means that i7 can execute SSE2 instructions in a single cycle. This would make SSE2-aware software such as SHRIMP much faster.
Nils
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Originally posted by nilshomer View PostThe Nehelem processors are the best (20% faster for my multi-threading applications).
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Originally posted by allo View PostMemory will depend on the size of the genomes that you are working with. With 32 GB of memory you can do bacterial genomes up to 10 Mb, assuming that you have ~10 million 35bp single-end reads. If you want to do genomes in the 30-50 Mb range you may need 64-128 Gb of memory and for plants you a looking at $ 1 TB $. Also, you have to plan on how are you going to store your data and the always essential backups and consider that this type of machines run better in temperature-controlled rooms, they like it cold
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Nils
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Memory, memory, memory....
Originally posted by nilshomer View PostLinux, 32GB RAM, dual-quad AMD, 2TB of disk, and a low powered GPU.. Also, you have to plan on how are you going to store your data and the always essential backups and consider that this type of machines run better in temperature-controlled rooms, they like it cold
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Originally posted by polsum View PostThank you very much for the reply.Is there a significant advantage in having dual-Quad AMD over dual-quad Xeon processor?
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Originally posted by nilshomer View PostLinux, 32GB RAM, dual-quad AMD, 2TB of disk, and a low powered GPU.
The reasoning for Linux is that academic bioinformatic programs use Linux, where you can always run vmware (or in some cases wine) to run windows program.
Some NGS applications need >16Gb of RAM, with a lot of CPU. Also the data coming off Illumina/SOLiD data requires a lot of storage, so 2TB is a must.Is there a significant advantage in having dual-Quad AMD over dual-quad Xeon processor?
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Originally posted by polsum View PostHi, Our lab is planning to buy a computer that would be dedicated primarily to the bioinformatic analysis. We will be doing lots of deep-sequencing data analysis including Blasting, reference genome mapping etc.
I would like to request the experts here to please suggest a basic configuration for the computer, particularly the processor, OS, RAM, graphics card. We would prefer to use Windows OS but if someone really prefers Linux, no problems.
Thanks a lot in advance
The reasoning for Linux is that academic bioinformatic programs use Linux, where you can always run vmware (or in some cases wine) to run windows program.
Some NGS applications need >16Gb of RAM, with a lot of CPU. Also the data coming off Illumina/SOLiD data requires a lot of storage, so 2TB is a must.
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Which Computer to Buy?
Hi, Our lab is planning to buy a computer that would be dedicated primarily to the bioinformatic analysis. We will be doing lots of deep-sequencing data analysis including Blasting, reference genome mapping etc.
I would like to request the experts here to please suggest a basic configuration for the computer, particularly the processor, OS, RAM, graphics card. We would prefer to use Windows OS but if someone really prefers Linux, no problems.
Thanks a lot in advanceTags: None
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The complexity of cancer is clearly demonstrated in the diverse ecosystem of the tumor microenvironment (TME). The TME is made up of numerous cell types and its development begins with the changes that happen during oncogenesis. “Genomic mutations, copy number changes, epigenetic alterations, and alternative gene expression occur to varying degrees within the affected tumor cells,” explained Andrea O’Hara, Ph.D., Strategic Technical Specialist at Azenta. “As...-
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