Result for 3B9235954CBF2DAFEDF972BE54257EE54854EAEA

Query result

Key Value
FileName./usr/lib64/R/library/Rsolid/Meta/data.rds
FileSize73
MD53982BBC19F3A48704D41B7D42DC2B903
SHA-13B9235954CBF2DAFEDF972BE54257EE54854EAEA
SHA-2565CA16E7967D2C3E8341CC7361A4FBFF4C739D941778C61E5EC8CD84AFAC478D6
SSDEEP3:FttVFHl9jUcm7apn51znXjxKIrwo:XtVFwcm7aprzXjMIr3
TLSHT1C0A022CC820C02C0C00E803282C80F0380080CA2A8AC0883088303030000B03C28822C
hashlookup:parent-total4
hashlookup:trust70

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Parents (Total: 4)

The searched file hash is included in 4 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD504B136D1C401BF252EC01A13A464ABDA
PackageArchppc64
PackageDescription Rsolid is an R package for normalizing fluorescent intensity data from ABI/SOLiD second generation sequencing platform. It has been observed that the color-calls provided by factory software contain technical artifacts, where the proportions of colors called are extremely variable across sequencing cycles. Under the random DNA fragmentation assumption, these proportions should be equal across sequencing cycles and proportional to the dinucleotide frequencies of the sample. Rsolid implements a version of the quantile normalization algorithm that transforms the intensity values before calling colors. Results show that after normalization, the total number of mappable reads increases by around 5%, and number of perfectly mapped reads increases by 10%. Moreover a 2-5% reduction in overall error rates is observed, with a 2-6% reduction in the rate of valid adjacent color mis-matches. The latter is important, since it leads to a decrease in false-positive SNP calls. The normalization algorithm is computationally efficient. In a test we are able to process 300 million reads in 2 hours using 10 computer cluster nodes. The engine functions of the package are written in C for better performance.
PackageMaintainerFedora Project
PackageNameR-Rsolid
PackageRelease11.fc20
PackageVersion0.9.31
SHA-13C263388AA59865AFEAA074A414B2B91F74B3B80
SHA-256C3FD4B2151B7A71BBA25725A225EE08FB72D19438ACFD3AC4803B1F0C4C38AD2
Key Value
MD5A765912F72825921DD1C3393A8B3BEF7
PackageArchs390
PackageDescription Rsolid is an R package for normalizing fluorescent intensity data from ABI/SOLiD second generation sequencing platform. It has been observed that the color-calls provided by factory software contain technical artifacts, where the proportions of colors called are extremely variable across sequencing cycles. Under the random DNA fragmentation assumption, these proportions should be equal across sequencing cycles and proportional to the dinucleotide frequencies of the sample. Rsolid implements a version of the quantile normalization algorithm that transforms the intensity values before calling colors. Results show that after normalization, the total number of mappable reads increases by around 5%, and number of perfectly mapped reads increases by 10%. Moreover a 2-5% reduction in overall error rates is observed, with a 2-6% reduction in the rate of valid adjacent color mis-matches. The latter is important, since it leads to a decrease in false-positive SNP calls. The normalization algorithm is computationally efficient. In a test we are able to process 300 million reads in 2 hours using 10 computer cluster nodes. The engine functions of the package are written in C for better performance.
PackageMaintainerFedora Project
PackageNameR-Rsolid
PackageRelease11.fc20
PackageVersion0.9.31
SHA-1F4D63E9B6422FAC0B7C8EB264790AE15445C8CDE
SHA-25673FDD886549894676616C4C2CEBD8871BA1490357B9D5091EB9743E66DF91AF3
Key Value
MD5C3F54F83F49F3739337D4B7D462DB072
PackageArchppc
PackageDescription Rsolid is an R package for normalizing fluorescent intensity data from ABI/SOLiD second generation sequencing platform. It has been observed that the color-calls provided by factory software contain technical artifacts, where the proportions of colors called are extremely variable across sequencing cycles. Under the random DNA fragmentation assumption, these proportions should be equal across sequencing cycles and proportional to the dinucleotide frequencies of the sample. Rsolid implements a version of the quantile normalization algorithm that transforms the intensity values before calling colors. Results show that after normalization, the total number of mappable reads increases by around 5%, and number of perfectly mapped reads increases by 10%. Moreover a 2-5% reduction in overall error rates is observed, with a 2-6% reduction in the rate of valid adjacent color mis-matches. The latter is important, since it leads to a decrease in false-positive SNP calls. The normalization algorithm is computationally efficient. In a test we are able to process 300 million reads in 2 hours using 10 computer cluster nodes. The engine functions of the package are written in C for better performance.
PackageMaintainerFedora Project
PackageNameR-Rsolid
PackageRelease11.fc20
PackageVersion0.9.31
SHA-17F5D4F21FD074AF0C9A4505B4D2D3B091CD921EC
SHA-25641710918E32D9A98F846D4D3A30D346AAF0C868427DDCF63C670AAD113FDBAA9
Key Value
MD5EF4436252F452C75482A8196CA664F2B
PackageArchs390x
PackageDescription Rsolid is an R package for normalizing fluorescent intensity data from ABI/SOLiD second generation sequencing platform. It has been observed that the color-calls provided by factory software contain technical artifacts, where the proportions of colors called are extremely variable across sequencing cycles. Under the random DNA fragmentation assumption, these proportions should be equal across sequencing cycles and proportional to the dinucleotide frequencies of the sample. Rsolid implements a version of the quantile normalization algorithm that transforms the intensity values before calling colors. Results show that after normalization, the total number of mappable reads increases by around 5%, and number of perfectly mapped reads increases by 10%. Moreover a 2-5% reduction in overall error rates is observed, with a 2-6% reduction in the rate of valid adjacent color mis-matches. The latter is important, since it leads to a decrease in false-positive SNP calls. The normalization algorithm is computationally efficient. In a test we are able to process 300 million reads in 2 hours using 10 computer cluster nodes. The engine functions of the package are written in C for better performance.
PackageMaintainerFedora Project
PackageNameR-Rsolid
PackageRelease11.fc20
PackageVersion0.9.31
SHA-1C708DF44D0E07911820DDA202AC9C62405E55004
SHA-256E3F940A6BFB4B0A6603DFD9E95EFFA4312D569A981A71AEC5CCA102697081EAF