Consensuspredict: Consensuspredict

In brengong/ConservationtextmineR:

Description

Takes a data.table or mRNA sequences and returns mRNA's, miRNA's, or proteins containing a specified consensus sequence. Requires a three column data.table with columns labeled according to the type of specified search. If type = "mRNA", one column should be labeled "Sequence" containing the mRNA sequences to query, a column should be labeled "ensembl_transcript_id" containing the mRNA transcript id, and a column should be labeled "Species" designating the species of the mRNA. If type = "protein", one column should be labeled "Sequence" containing the protein sequences to query, a column should be labeled "ensembl_peptide_id" containing the protein peptide id, and a column should be labeled "Species" designating the species of the protein. If type = "miRNA", one column should be labeled "Sequence" containing the miRNA sequences to query, a column should be labeled "miRNA_Name" containing the miRNA name (ex: hsa-miRXXX), and a column should be labeled "miRNA_type" designating if the miRNA is an IMMATURE_HAIR_PIN or a MATURE miRNA.

Usage

Consensuspredict(DT, conse, type)

Arguments

DT	a data table with three columns. If type = "mRNA", the columns should be labeled "Sequence", "ensembl_transcript_id", "Species". If type = "miRNA", the columns should be labeled "Sequence", "miRNA_Name", "miRNA_type". If type = "protein", the columns should be labeled "Sequence", "ensembl_peptide_id", "Species".
conse	a character string containing a single consensus sequence to query.
type	a single character either "miRNA", "protein", or "mRNA" designating what type of sequences are being queried.

Value

A data table containing the following columns:

Author(s)

Brendan Gongol

Examples

ensembl_transcript_id <- c("ENSACAT00000000002","ENSACAT00000000003","ENSACAT00000000004","ENSACAT00000000006","ENSACAT00000000007","ENSACAT00000000008")
Sequence <- c("CTGTTTCGAGCCTGAATCTCGATCGCTCGCGCTAGACAGCTCGACGCACTTTTCAGCAGGAGCCTG",
              "AATTAATTTCAGCAGATAGCGCTCGATACAGCTCGACAGCTCTTGCTGTATTGTGTG",
              "TTGCTGTATTGTGTGATCCTCGATACAGGTATTTTCTGAGCCTGATAGCTAGCTTTGCTGTATTGTGTGAATTAATT",
              "AAAAAATTTTTTAATTAATTCCCCCCGGGGGG", "AATACAGCTCGCGCGCGGAACCAAT",
              "AATTAATTATCGCTACAGCTCGACACAATTAATTAGCTCGTGGGTTCCGGCCTTAACAATTAATT")
external_gene_name <- c("AKT", "PI3K", "SREBP", "FOXO", "PKA", "NRF")
Species <- c("Rat", "Mouse", "Human", "Pig", "Goat", "Fox")
mRNADT <- data.frame(cbind(ensembl_transcript_id, Sequence, external_gene_name, Species))
mRNADT$Sequence <- as.character(mRNADT$Sequence)
Consensuspredict(DT=mRNADT, conse= "AATTAATT", type = "mRNA")

ensembl_peptide_id <- c("ENSAMEP00000003151","ENSAMEP00000003176","ENSAMEP00000003150","ENSAMEP00000003213","ENSAMEP00000003164","ENSXMAP00000020464")
Sequence <- c("RKQHFIHQAVRNSDLVPKAKGRKSLQRLENTQYLLSLLETDGGTAGLDDGDLAPPAAPGIFAEACSNETYMEVWNDFMNRSGEEQERVLRYLEDEGKSK",
              "GADKSNRFPLPFPFPSKLYIMCMANLEELQSTDSLDCLERLIDLNNGEGQIFTIDGPLCLKNVQSMFGKLIDLAYTPFH",
              "IIALALEANNQLTWRDVQHLLVKTSRPAHLKANDWKVNGAGHKVSHLYGFGLVDAEALVMEAKKWTAVPAAEH",
              "VGSAAVSAPVLALHRLSPGPRTYCSEVFPSRALERAFALYNLLALYLLPLAATCA", "KFVNYMQQVSVQATCATLTAMSVDRWY",
              "VHEHVILDPLTKELNYPFIILALWGVIMTGSICGLERLRQTDLKALIAYSSVSHMGLVAAAILIQTPWALTGALILMIVHDK")
external_gene_name <- c("AKT", "PI3K", "SREBP", "FOXO", "PKA", "NRF")
Species <- c("Rat", "Mouse", "Human", "Pig", "Goat", "Fox")
PRODT <- data.frame(cbind(ensembl_peptide_id, Sequence, external_gene_name, Species))
PRODT$Sequence <- as.character(PRODT$Sequence)
conseq= "(G|A|V)(L|A|H)(D|E)(K|R|H)"
Consensuspredict(DT = PRODT, conse = conseq, type = "protein")

Sequence <- c("UAGCGAUUGGAUCCGGUGAGGUAGUAGGUUGUAUAGUUUGGAAUAUUACCACCGGUGAACUAUGCAAUUUUCUACCUUACCGGAGACAGAACUCUUCGA",
              "AUGCUUCCGGCCUGUUCCCUGAGACCUCAAGUGUGAGUGUACUAGCGAUGCUUCACACCUGGGCUCUCCGGGUACCAGGACGGUUUGAGCAGAU",
              "AAAGUGACCGUACCGAGCUGCAUACUUCCUUACAUGCCCAUACUAUAUCAUAAAUGGAUAUGGAAUGUAAAGAAGUAUGUAGAACGGGGUGGUAGU ",
              "UAAACAGUAUACAGAAAGCCAUCAAAGCGGUGGUUGAUGUGUUGCAAAUUAUGACUUUCAUAUCACAGCCAGCUUUGAUGUGCUGCCUGUUGCACUGU",
              "CGGACAAUGCUCGAGAGGCAGUGUGGUUAGCUGGUUGCAUAUUUCCUUGACAACGGCUACCUUCACUGCCACCCCGAACAUGUCGUCCAUCUUUGAA",
              "UAGCGAUUCAGAUCGAGCCAUUGCUGGUUUCUUCCACAGUAGCGAUUUCCAUUAGAACUAUCACCGGGUGGAAACUAGCAGUGGCUCGAUUAGCGAU",
              "UGAGGUAGUAGGUUGUAUAGUU", "CUAUGCAUAGCGAUACCUUACC", "UCCCUGAGACCUCAAGUGUGA", "ACACCUGGGCUCUCCGGGUACC",
              "UAGCGAUCCUUACAUGCCCAUA", "UCGUGUCCGUUUCUCGUUUCGA", "ACAAUAAUCGGACACUAGCGAU", "CACACCGGACGAGAUUUCAU",
              "UACCGGGCGUGGGGAGGGCAGG", "UAGCGAUUCCUUCUUAGCGAU")
miRNA_Name <- c("hsa-let-7","cel-lin-4","aae-mir-1","bol-mir-2","rno-mir-34","cel-mir-35",
                "cel-let-7-5p", "cel-let-7-3p", "cel-lin-4-5p", "cel-lin-4-3p", "cel-miR-1-5p", "ame-miR-9895",
                "hsa-miR-9896", "rno-miR-3478", "mmu-miR9897-5p", "cre-miR9897-3p")
miRNA_type <- c("IMMATURE_HAIR_PIN","IMMATURE_HAIR_PIN","IMMATURE_HAIR_PIN","IMMATURE_HAIR_PIN","IMMATURE_HAIR_PIN","IMMATURE_HAIR_PIN",
                "MATURE", "MATURE", "MATURE", "MATURE", "MATURE", "MATURE", "MATURE", "MATURE", "MATURE", "MATURE")
MiRNADT<- data.frame(cbind(Sequence, miRNA_Name, miRNA_type))
MiRNADT$Sequence <- as.character(MiRNADT$Sequence)

Consensuspredict(DT = MiRNADT, conse = "UAGCGAU", type = "miRNA")

brengong/ConservationtextmineR documentation built on July 29, 2019, 10:05 a.m.