| Title: | Non-Additive Expression Analysis of Hybrid Offspring |
|---|---|
| Description: | Three functional modules, including genetic features, differential expression analysis and non-additive expression analysis were integrated into the package. And the package is suitable for RNA-seq and small RNA sequencing data. Besides, two methods of non-additive expression analysis were provided. One is the calculation of the additive (a) and dominant (d), the other is the evaluation of expression level dominance by comparing the total expression of the gene in hybrid offspring with the expression level in parents. For non-additive expression analysis of RNA-seq data, it is only applicable to hybrid offspring (including two sub-genomes) species for the time being. |
| Authors: | Yuqing Wu [aut, cre] |
| Maintainer: | Yuqing Wu <[email protected]> |
| License: | AGPL (>= 3) |
| Version: | 0.1.0 |
| Built: | 2025-02-03 04:40:34 UTC |
| Source: | https://github.com/w123yu/expgenetic |
Plot the base frequency distribution diagram for small RNA (sRNA)
basepreplot(sRNAdata, width = 0.6, font_size = 10, title_size = 12)basepreplot(sRNAdata, width = 0.6, font_size = 10, title_size = 12)
sRNAdata |
A data frame. Base frequency distribution of sRNAs. |
width |
A numeric. Bar width, and default is 0.6. |
font_size |
A numeric. Size of axis ticks and legend item labels, and default is 10. |
title_size |
A numeric. Size of axis titles and legend titles, and default is 12. |
Base frequency distribution plot of sRNAs.
#F1 F1_miRNA <- F1_miRNA_count[,1] F1_bf <- mirnapredata(sRNAseq = F1_miRNA) basepreplot(sRNAdata = F1_bf)#F1 F1_miRNA <- F1_miRNA_count[,1] F1_bf <- mirnapredata(sRNAseq = F1_miRNA) basepreplot(sRNAdata = F1_bf)
Regarding the criteria for filtering out lowly expressed genes, no less than the count threshold in all replicates.
Countfilter( P1_count, P2_count, F1_count, type, homoeologs, count_threshold = 5 )Countfilter( P1_count, P2_count, F1_count, type, homoeologs, count_threshold = 5 )
P1_count |
A data frame. The count table of genes in P1 species. For the count table, the first column is the gene identifier, and other columns are read counts of the gene in each biological replicate. |
P2_count |
A data frame. The count table of genes in P2 species. |
F1_count |
A data frame. The count table of genes in F1 species. |
type |
A character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes within the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
count_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 5 (the count values in all replicates). |
The 'homoeologs' table contains the orthologs pairs. In detail, the first column is the group name (unique) of homoeologs among three species (Parents: P1; P2, Progeny: F1), the second column is the Gene ID of P1, the third column is the Gene ID of P2. And the fourth column and fifth columns are the identifier of F1 orthologs derived from P1 and P2 ancestors, respectively (e.g. "Homoeolog1 BraA01t00004Z BolC01g000040.2J BnA01g0000030.1 BnC01g0424620.1").
A data frame.
Count5result <- Countfilter(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count, type = "sRNA", count_threshold = 5)Count5result <- Countfilter(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count, type = "sRNA", count_threshold = 5)
Count table of miRNAs in F1 species. The "F1" represents the polyploid progeny.
head(F1_miRNA_count) # sequence BF1.1 BF1.2 BF1.3 #1 TTTGGATTGAAGGGAGCTCTA 20233 6388 16732 #2 TTTCCAAATGTAGACAAAGCA 19909 5157 16076 #3 TCCCAAATGTAGACAAAGC 82 33 103 #4 CTTTGTCTATCGTTTGGAAAAG 2367 1040 3203 #5 TTGGACTGAAGGGAGCTCCTT 34 9 21 #6 TCGGACCAGGCTTCATTCCCC 3281 607 1289head(F1_miRNA_count) # sequence BF1.1 BF1.2 BF1.3 #1 TTTGGATTGAAGGGAGCTCTA 20233 6388 16732 #2 TTTCCAAATGTAGACAAAGCA 19909 5157 16076 #3 TCCCAAATGTAGACAAAGC 82 33 103 #4 CTTTGTCTATCGTTTGGAAAAG 2367 1040 3203 #5 TTGGACTGAAGGGAGCTCCTT 34 9 21 #6 TCGGACCAGGCTTCATTCCCC 3281 607 1289
RPM table of miRNAs in F1 species. The "F1" represents the polyploid progeny.
head(F1_miRNA_rpm) # sequence BF1.1 BF1.2 BF1.3 #1 TTTGGATTGAAGGGAGCTCTA 1512.16 1086.35 2032.97 #2 TTTCCAAATGTAGACAAAGCA 1487.94 877.01 1953.27 #3 TCCCAAATGTAGACAAAGC 6.13 5.61 12.51 #4 CTTTGTCTATCGTTTGGAAAAG 176.90 176.86 389.17 #5 TTGGACTGAAGGGAGCTCCTT 2.54 1.53 2.55 #6 TCGGACCAGGCTTCATTCCCC 245.21 103.23 156.62head(F1_miRNA_rpm) # sequence BF1.1 BF1.2 BF1.3 #1 TTTGGATTGAAGGGAGCTCTA 1512.16 1086.35 2032.97 #2 TTTCCAAATGTAGACAAAGCA 1487.94 877.01 1953.27 #3 TCCCAAATGTAGACAAAGC 6.13 5.61 12.51 #4 CTTTGTCTATCGTTTGGAAAAG 176.90 176.86 389.17 #5 TTGGACTGAAGGGAGCTCCTT 2.54 1.53 2.55 #6 TCGGACCAGGCTTCATTCCCC 245.21 103.23 156.62
All sRNA sequences in F1 (F1: the polyploid progeny).
Rapp et al. proposed the classification of 12 expression patterns in allopolyploids, including additivity (I, XII), ELD (II, XI, IV, IX), transgressive down-regulation (III, VII, X) and transgressive up-regulation (V, VI, VIII).
Get12Bins( P1_count, P2_count, F1_count, type, homoeologs, count_threshold = 5, Pvalue = 0.05, log2FC = 1 )Get12Bins( P1_count, P2_count, F1_count, type, homoeologs, count_threshold = 5, Pvalue = 0.05, log2FC = 1 )
P1_count |
A data frame. The count table of genes in P1 species. For the count table, the first column is the gene identifier, and other columns are the corresponding expression levels of the genes in each biological replicate. |
P2_count |
A data frame. The count table of genes in P2 species. |
F1_count |
A data frame. The count table of genes in F1 species. |
type |
A character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes in the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
count_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 5 (the count values in all replicates). |
Pvalue |
A numeric. The P value of differential expression analysis using DESeq2. Default is 0.05. |
log2FC |
A numeric. The log2-transformed expression fold of differential expression analysis using DESeq2. Default is 1. |
pv11: P value of differential expression analysis using DESeq2. Parental P1 was used as the control group and F1 was used as the treatment group. pv12: P value of differential expression analysis using DESeq2. Parental P2 was used as the control group and F1 was used as the treatment group. pv21: P value of differential expression analysis using DESeq2. Parental P1 was used as the control group and P2 was used as the treatment group. Besides, "fc" represents the log2FoldChange of differential expression analysis.
A data frame. Classification results of non-additive analysis based on the ELD method.
Rapp RA, Udall JA, Wendel JF. Genomic expression dominance in allopolyploids. BMC Biol. 2009 May 1;7:18.
miRNA_12bin <- Get12Bins(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count,type = "sRNA")miRNA_12bin <- Get12Bins(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count,type = "sRNA")
About the classification method based on |d/a|, the additive (a) and dominant (d) values were calculated by the expression level of each miRNA. Edwards et al. proposed that the "|d/a|" can be used as the criterion to estimate the expression patterns of miRNAs. Specific classification criteria are as follows, |d/a| <= 0.2, additivity; |d/a| > 0.2 and |d/a| <= 0.8, partial dominance; |d/a| > 0.8 and |d/a| <= 1.2, dominance; |d/a| > 1.2, overdominance.
GetDAtable(P1_RPM, P2_RPM, F1_RPM, type, homoeologs, rpm_threshold = 1)GetDAtable(P1_RPM, P2_RPM, F1_RPM, type, homoeologs, rpm_threshold = 1)
P1_RPM |
A data frame. The RPM table of genes in P1 species. For the RPM table, the first column is the gene identifier, and other columns are the RPM values of the genes in each biological replicate. |
P2_RPM |
A data frame. The RPM table of genes in P2 species. |
F1_RPM |
A data frame. The RPM table of genes in F1 species. |
type |
A character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes in the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
rpm_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 1 (the average RPM of all replicates). |
The 'homoeologs' table contains the orthologs pairs. In detail, the first column is the group name (unique) of homoeologs among three species (Parents: P1; P2, Progeny: F1), the second column is the Gene ID of P1, the third column is the Gene ID of P2. And the fourth column and fifth columns are the identifier of F1 orthologs derived from P1 and P2 ancestors, respectively (e.g. "Homoeolog1 BraA01t00004Z BolC01g000040.2J BnA01g0000030.1 BnC01g0424620.1").
A data frame. Classification results of non-additive expression analysis based on |d/a|.
Edwards MD, Stuber CW, Wendel JF. Molecular-marker-facilitated investigations of quantitative-trait loci in maize. I. Numbers, genomic distribution and types of gene action. Genetics. 1987 May;116(1):113-25.
DAresult <- GetDAtable(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type = "sRNA", rpm_threshold = 1)DAresult <- GetDAtable(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type = "sRNA", rpm_threshold = 1)
Extract the results of differential expression analysis.
GetDEdata( P1_count, P2_count, F1_count, output_type, type, homoeologs, count_threshold = 5 )GetDEdata( P1_count, P2_count, F1_count, output_type, type, homoeologs, count_threshold = 5 )
P1_count |
A data frame. The count table of genes in P1 species. For the count table, the first column is the gene identifier, and other columns are the corresponding expression levels of the genes in each biological replicate. |
P2_count |
A data frame. The count table of genes in P2 species. |
F1_count |
A data frame. The count table of genes in F1 species. |
output_type |
A character. "F1_vs_P1", "F1_vs_P2" or "P2_vs_P1". |
type |
A character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes in the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
count_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 5 (the count values in all replicates). |
F1_vs_P1: Results of differential expression analysis using DESeq2. Parental P1 was used as the control group and F1 was used as the treatment group. If the log2FoldChange of a gene is positive, it means that the expression level of the gene in F1 is higher than that in P1. F1_vs_P2: Results of differential expression analysis using DESeq2. Parental P2 was used as the control group and F1 was used as the treatment group. P2_vs_P1: Results of differential expression analysis using DESeq2. Parental P1 was used as the control group and P2 was used as the treatment group.
A data frame. Differential expression analysis results.
P2_vs_P1 <- GetDEdata(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count, output_type = "P2_vs_P1", type="sRNA")P2_vs_P1 <- GetDEdata(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count, output_type = "P2_vs_P1", type="sRNA")
There are two types of pictures: bar plot (type = "bar") and line plot (type = "line"). For the bar plot, the Y-axis displays the proportion of sRNAs in a certain length, the X-axis represents sRNAs in different length. And for line plot, the Y-axis displays the abundance of sRNAs in a certain length, the X-axis represents sRNAs in different length.
lenplot(sRNAdata, type, width = 0.6, font_size = 10, title_size = 12)lenplot(sRNAdata, type, width = 0.6, font_size = 10, title_size = 12)
sRNAdata |
A data frame. Frequency distribution of sRNAs in different length. |
type |
A character. "bar" or "line". |
width |
A numeric. Bar width, and default is 0.6. if the type is "line", the parameter does not need to be given. |
font_size |
A numeric. Size of axis ticks and legend item labels, and default is 10. |
title_size |
A numeric. Size of axis titles and legend titles, and default is 12. |
Length distribution plot of sRNAs.
#P1(B.napus) B.napu_sRNA <- srnapredata(sRNAseq = P1_sRNA_seq,Group = "B.napus(AACC)") #P2(B.rapa) B.rapa_sRNA <- srnapredata(sRNAseq = P2_sRNA_seq,Group = "B.rapa(AA)") #F1(B.napus X B.rapa) B.nr_sRNA <- srnapredata(sRNAseq = F1_sRNA_seq,Group = "B.napus x B.rapa(AAAACC)") #intergrate these data for length distribution plot sRNA_data <- rbind(B.napu_sRNA,B.rapa_sRNA,B.nr_sRNA) #plot lenplot(sRNAdata = sRNA_data,type = "line") lenplot(sRNAdata = sRNA_data,type = "bar")#P1(B.napus) B.napu_sRNA <- srnapredata(sRNAseq = P1_sRNA_seq,Group = "B.napus(AACC)") #P2(B.rapa) B.rapa_sRNA <- srnapredata(sRNAseq = P2_sRNA_seq,Group = "B.rapa(AA)") #F1(B.napus X B.rapa) B.nr_sRNA <- srnapredata(sRNAseq = F1_sRNA_seq,Group = "B.napus x B.rapa(AAAACC)") #intergrate these data for length distribution plot sRNA_data <- rbind(B.napu_sRNA,B.rapa_sRNA,B.nr_sRNA) #plot lenplot(sRNAdata = sRNA_data,type = "line") lenplot(sRNAdata = sRNA_data,type = "bar")
Get the base frequency distribution table.
mirnapredata(sRNAseq)mirnapredata(sRNAseq)
sRNAseq |
Character. All sRNA sequences in vector format. |
A data frame. The output consists of three columns, i.e., base, base frequency and position.
#F1 F1_miRNA <- F1_miRNA_count[,1] F1_bf <- mirnapredata(sRNAseq = F1_miRNA) #output result head(F1_bf) # Base Frequency Position #1 A 32 1 #2 C 27 1 #3 G 31 1 #4 T 115 1 #5 A 27 2 #6 C 50 2#F1 F1_miRNA <- F1_miRNA_count[,1] F1_bf <- mirnapredata(sRNAseq = F1_miRNA) #output result head(F1_bf) # Base Frequency Position #1 A 32 1 #2 C 27 1 #3 G 31 1 #4 T 115 1 #5 A 27 2 #6 C 50 2
Count table of miRNAs in P1 species. The "P1" represents one of parents.
head(P1_miRNA_count) # sequence Bnapus.1 Bnapus.2 Bnapus.3 #1 TTTGGATTGAAGGGAGCTCTA 29848 12094 10685 #2 TTAGATTCACGCACAAACTCG 986 571 456 #3 TGAAGCTGCCAGCATGATCTA 3152 1436 1091 #4 CTTTGTCTATCGTTTGGAAAAG 2449 1307 1116 #5 GATCATGTTCGCAGTTTCACC 1364 650 656 #6 TTTCCAAATGTAGACAAAGCA 11658 3914 4123head(P1_miRNA_count) # sequence Bnapus.1 Bnapus.2 Bnapus.3 #1 TTTGGATTGAAGGGAGCTCTA 29848 12094 10685 #2 TTAGATTCACGCACAAACTCG 986 571 456 #3 TGAAGCTGCCAGCATGATCTA 3152 1436 1091 #4 CTTTGTCTATCGTTTGGAAAAG 2449 1307 1116 #5 GATCATGTTCGCAGTTTCACC 1364 650 656 #6 TTTCCAAATGTAGACAAAGCA 11658 3914 4123
RPM table of miRNAs in P1 species. The "P1" represents one of parents.
head(P1_miRNA_rpm) # sequence Brapa.1 Brapa.2 Brapa.3 #1 TTTGGATTGAAGGGAGCTCTA 1641.18 1116.03 1014.37 #2 TGAAGCTGCCAGCATGATCTA 129.33 103.23 103.68 #3 TTTCCAAATGTAGACAAAGCA 905.23 920.57 1180.51 #4 TCGGACCAGGCTTCATCCCCC 24.71 14.38 15.03 #5 AGAATCTTGATGATGCTGCAG 48.64 41.09 41.60 #6 TTGACAGAAGAAAGAGAGCAC 86.96 81.23 67.41head(P1_miRNA_rpm) # sequence Brapa.1 Brapa.2 Brapa.3 #1 TTTGGATTGAAGGGAGCTCTA 1641.18 1116.03 1014.37 #2 TGAAGCTGCCAGCATGATCTA 129.33 103.23 103.68 #3 TTTCCAAATGTAGACAAAGCA 905.23 920.57 1180.51 #4 TCGGACCAGGCTTCATCCCCC 24.71 14.38 15.03 #5 AGAATCTTGATGATGCTGCAG 48.64 41.09 41.60 #6 TTGACAGAAGAAAGAGAGCAC 86.96 81.23 67.41
All sRNA sequences in P1 (P1: one of the parents).
Count table of miRNAs in P2 species. The "P2" represents one of parents.
head(P2_miRNA_count) # sequence Bnapus.1 Bnapus.2 Bnapus.3 #1 TTTGGATTGAAGGGAGCTCTA 29848 12094 10685 #2 TTAGATTCACGCACAAACTCG 986 571 456 #3 TGAAGCTGCCAGCATGATCTA 3152 1436 1091 #4 CTTTGTCTATCGTTTGGAAAAG 2449 1307 1116 #5 GATCATGTTCGCAGTTTCACC 1364 650 656 #6 TTTCCAAATGTAGACAAAGCA 11658 3914 4123head(P2_miRNA_count) # sequence Bnapus.1 Bnapus.2 Bnapus.3 #1 TTTGGATTGAAGGGAGCTCTA 29848 12094 10685 #2 TTAGATTCACGCACAAACTCG 986 571 456 #3 TGAAGCTGCCAGCATGATCTA 3152 1436 1091 #4 CTTTGTCTATCGTTTGGAAAAG 2449 1307 1116 #5 GATCATGTTCGCAGTTTCACC 1364 650 656 #6 TTTCCAAATGTAGACAAAGCA 11658 3914 4123
RPM table of miRNAs in P2 species. The "P2" represents one of parents.
head(P2_miRNA_rpm) # sequence Bnapus.1 Bnapus.2 Bnapus.3 #1 TTTGGATTGAAGGGAGCTCTA 1804.35 1362.88 1439.22 #2 TTAGATTCACGCACAAACTCG 59.60 64.35 61.42 #3 TGAAGCTGCCAGCATGATCTA 190.54 161.82 146.95 #4 CTTTGTCTATCGTTTGGAAAAG 148.04 147.29 150.32 #5 GATCATGTTCGCAGTTTCACC 82.46 73.25 88.36 #6 TTTCCAAATGTAGACAAAGCA 704.74 441.07 555.35head(P2_miRNA_rpm) # sequence Bnapus.1 Bnapus.2 Bnapus.3 #1 TTTGGATTGAAGGGAGCTCTA 1804.35 1362.88 1439.22 #2 TTAGATTCACGCACAAACTCG 59.60 64.35 61.42 #3 TGAAGCTGCCAGCATGATCTA 190.54 161.82 146.95 #4 CTTTGTCTATCGTTTGGAAAAG 148.04 147.29 150.32 #5 GATCATGTTCGCAGTTTCACC 82.46 73.25 88.36 #6 TTTCCAAATGTAGACAAAGCA 704.74 441.07 555.35
All sRNA sequences in P2 (P2: one of the parents).
The count matrix of different species as the input data to perform differential expression analysis using DESeq2. And the number of differentially expressed genes between any two species is marked on the triangle diagram.
polyDESeq( P1_count, P2_count, F1_count, P1_name, P2_name, F1_name, type, homoeologs, count_threshold = 5, Pvalue = 0.05 )polyDESeq( P1_count, P2_count, F1_count, P1_name, P2_name, F1_name, type, homoeologs, count_threshold = 5, Pvalue = 0.05 )
P1_count |
A data frame. The count table of genes in P1 species. For the count table, the first column is the gene identifier, and other columns are the read counts of the genes in each biological replicate. |
P2_count |
A data frame. The count table of genes in P2 species. |
F1_count |
A data frame. The count table of genes in F1 species. |
P1_name |
A character. Category names of P1 species. |
P2_name |
A character. Category names of P2 species. |
F1_name |
A character. Category names of F1 species. |
type |
A character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes in the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
count_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 5 (the count values in all replicates). |
Pvalue |
A numeric. Threshold for significance test in differential expression analysis. Default is 0.05. |
The 'homoeologs' table contains the orthologs pairs. In detail, the first column is the group name (unique) of homoeologs among three species (Parents: P1;P2, Progeny: F1), the second column is the Gene ID of P1, the third column is the Gene ID of P2. And the fourth column and fifth columns are the identifier of F1 orthologs derived from P1 and P2 ancestors, respectively (e.g. "Homoeolog1 BraA01t00004Z BolC01g000040.2J BnA01g0000030.1 BnC01g0424620.1").
Triangle Diagram
polyDESeq(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count, P1_name = "B.napus(AACC)", P2_name = "B.rapa(AA)", F1_name = "B.napus x B.rapa (AAAACC)",type="sRNA")polyDESeq(P1_count = P1_miRNA_count, P2_count = P2_miRNA_count, F1_count = F1_miRNA_count, P1_name = "B.napus(AACC)", P2_name = "B.rapa(AA)", F1_name = "B.napus x B.rapa (AAAACC)",type="sRNA")
Regarding the criteria for filtering out lowly expressed genes, no less than the RPM threshold in all replicates.
Rpmfilter(P1_RPM, P2_RPM, F1_RPM, type, homoeologs, rpm_threshold = 1)Rpmfilter(P1_RPM, P2_RPM, F1_RPM, type, homoeologs, rpm_threshold = 1)
P1_RPM |
A data frame. The RPM table of genes in P1 species. For the RPM table, the first column is the gene identifier (e.g. sequences of sRNA, Gene ID), and other columns are the RPM values of the gene in each biological replicate. |
P2_RPM |
A data frame. The RPM table of genes in P2 species. |
F1_RPM |
A data frame. The RPM table of genes in F1 species. |
type |
A character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes within the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
rpm_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 1 (the average RPM of all replicates). |
The 'homoeologs' table contains the orthologs pairs. In detail, the first column is the group name (unique) of homoeologs among three species (Parents: P1; P2, Progeny: F1), the second column is the Gene ID of P1, the third column is the Gene ID of P2. And the fourth column and fifth columns are the identifier of F1 orthologs derived from P1 and P2 ancestors, respectively (e.g. "Homoeolog1 BraA01t00004Z BolC01g000040.2J BnA01g0000030.1 BnC01g0424620.1").
A data frame.
Rpm1result <- Rpmfilter(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type = "sRNA", rpm_threshold = 1)Rpm1result <- Rpmfilter(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type = "sRNA", rpm_threshold = 1)
Get the length distribution of sRNAs.
srnapredata(sRNAseq, Group)srnapredata(sRNAseq, Group)
sRNAseq |
Character. All sRNA sequences in vector format. |
Group |
Character. Group name. |
A data frame. The output consists of three columns, i.e., length, frequency and group name.
#P1(B.napus) B.napu_sRNA <- srnapredata(sRNAseq = P1_sRNA_seq, Group = "B.napus(AACC)") #P2(B.rapa) B.rapa_sRNA <- srnapredata(sRNAseq = P2_sRNA_seq, Group = "B.rapa(AA)") #F1(B.napus X B.rapa) B.nr_sRNA <- srnapredata(sRNAseq = F1_sRNA_seq, Group = "B.napus x B.rapa(AAAACC)") #intergrate these data for length distribution plot sRNA_data <- rbind(B.napu_sRNA, B.rapa_sRNA, B.nr_sRNA) #output result head(sRNA_data) # Length Frequency Group #1 15 8 B.napus(AACC) #2 16 7 B.napus(AACC) #3 17 13 B.napus(AACC) #4 18 16 B.napus(AACC) #5 19 25 B.napus(AACC) #6 20 33 B.napus(AACC)#P1(B.napus) B.napu_sRNA <- srnapredata(sRNAseq = P1_sRNA_seq, Group = "B.napus(AACC)") #P2(B.rapa) B.rapa_sRNA <- srnapredata(sRNAseq = P2_sRNA_seq, Group = "B.rapa(AA)") #F1(B.napus X B.rapa) B.nr_sRNA <- srnapredata(sRNAseq = F1_sRNA_seq, Group = "B.napus x B.rapa(AAAACC)") #intergrate these data for length distribution plot sRNA_data <- rbind(B.napu_sRNA, B.rapa_sRNA, B.nr_sRNA) #output result head(sRNA_data) # Length Frequency Group #1 15 8 B.napus(AACC) #2 16 7 B.napus(AACC) #3 17 13 B.napus(AACC) #4 18 16 B.napus(AACC) #5 19 25 B.napus(AACC) #6 20 33 B.napus(AACC)
Get the information for each region of the venn diagram.
VennData( P1_RPM, P2_RPM, F1_RPM, type, homoeologs, rpm_threshold = 1, output_file = "venn_list" )VennData( P1_RPM, P2_RPM, F1_RPM, type, homoeologs, rpm_threshold = 1, output_file = "venn_list" )
P1_RPM |
A data frame. The RPM table of genes in P1 species. For the RPM table, the first column is the gene identifier, and other columns are the RPM values of the genes in each biological replicate. |
P2_RPM |
A data frame. The RPM table of genes in P2 species. |
F1_RPM |
A data frame. The RPM table of genes in P2 species. |
type |
Character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes in the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
rpm_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 1 (the average RPM of all replicates). |
output_file |
"venn_list", "P1_specific", "P2_specific", "F1_specific", or "all_common". |
The 'homoeologs' table contains the orthologs pairs. In detail, the first column is the group name (unique) of homoeologs among three species (Parents: P1; P2, Progeny: F1), the second column is the Gene ID of P1, the third column is the Gene ID of P2. And the fourth column and fifth columns are the identifier of F1 orthologs derived from P1 and P2 ancestors, respectively (e.g. "Homoeolog1 BraA01t00004Z BolC01g000040.2J BnA01g0000030.1 BnC01g0424620.1").
A data frame.
#output_file = "venn_list" venn_list <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "venn_list") ##output_file = "P1_specific" P1_specific <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "P1_specific") ##output_file = "P2_specific" P2_specific <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "P2_specific") ##output_file = "F1_specific" F1_specific <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "F1_specific") ##output_file = "all_common" all_common <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "all_common")#output_file = "venn_list" venn_list <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "venn_list") ##output_file = "P1_specific" P1_specific <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "P1_specific") ##output_file = "P2_specific" P2_specific <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "P2_specific") ##output_file = "F1_specific" F1_specific <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "F1_specific") ##output_file = "all_common" all_common <- VennData(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, type="sRNA",rpm_threshold = 1, output_file = "all_common")
This function creates a Venn Diagram to display the overlap of expressed genes between three sets (parents and progeny).
VennPlot( P1_RPM, P2_RPM, F1_RPM, P1_name, P2_name, F1_name, type, homoeologs, rpm_threshold = 1 )VennPlot( P1_RPM, P2_RPM, F1_RPM, P1_name, P2_name, F1_name, type, homoeologs, rpm_threshold = 1 )
P1_RPM |
A data frame. The RPM table of genes in P1 species. For the RPM table, the first column is the gene identifier, and other columns are the RPM values of the genes in each biological replicate. |
P2_RPM |
A data frame. The RPM table of genes in P2 species. |
F1_RPM |
A data frame. The RPM table of genes in F1 species. |
P1_name |
Character. Category names of P1 species. |
P2_name |
Character. Category names of P2 species. |
F1_name |
Character. Category names of F1 species. |
type |
Character. "sRNA" or "mRNA". |
homoeologs |
A data frame. Orthologous relationships of genes in the parental species and their progeny. Only required when the 'type' is 'mRNA'. |
rpm_threshold |
A numeric. Threshold for filtering out the lowly expressed genes. The default is 1 (the average RPM of all replicates). |
The 'homoeologs' table contains the orthologs pairs. In detail, the first column is the group name (unique) of homoeologs among three species (Parents: P1; P2, Progeny: F1), the second column is the Gene ID of P1, the third column is the Gene ID of P2. And the fourth column and fifth columns are the identifier of F1 orthologs derived from P1 and P2 ancestors, respectively (e.g. "Homoeolog1 BraA01t00004Z BolC01g000040.2J BnA01g0000030.1 BnC01g0424620.1").
Venn diagram.
#miRNA VennPlot(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, P1_name = "B.napus(AACC)", P2_name = "B.rapa(AA)", F1_name = "B.napus x B.rapa(AAAACC)",type="sRNA")#miRNA VennPlot(P1_RPM = P1_miRNA_rpm, P2_RPM = P2_miRNA_rpm, F1_RPM = F1_miRNA_rpm, P1_name = "B.napus(AACC)", P2_name = "B.rapa(AA)", F1_name = "B.napus x B.rapa(AAAACC)",type="sRNA")