| Title: | Quantification of Mitochondrial DNA Heteroplasmy |
|---|---|
| Description: | R package that allows the estimation and downstream statistical analysis of the mitochondrial DNA Heteroplasmy calculated from single-cell datasets. |
| Authors: | Gabriele Lubatti |
| Maintainer: | Gabriele Lubatti <[email protected]> |
| License: | GPL-3 |
| Version: | 0.1.0 |
| Built: | 2024-11-05 05:26:38 UTC |
| Source: | https://github.com/gabrielelubatti/mitohear |
choose_features_clustering
choose_features_clustering( heteroplasmy_matrix, allele_matrix, cluster, top_pos, deepSplit_param, minClusterSize_param, min_value_vector, threshold = 0.2, index, max_frac = 0.7 )choose_features_clustering( heteroplasmy_matrix, allele_matrix, cluster, top_pos, deepSplit_param, minClusterSize_param, min_value_vector, threshold = 0.2, index, max_frac = 0.7 )
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
allele_matrix |
Fourth element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
top_pos |
Numeric value. Number of bases sorted with decreasing values of distance variance (see section Details below) among samples. If relevant_bases=NULL, then the bases for performing hierarchical clustering are the ones whose relative variance (variance of the base divided sum of variance among top_pos bases) is above min_value. |
deepSplit_param |
Integer value between 0 and 4 for the deepSplit parameter of the function cutreeHybrid. See section Details below. |
minClusterSize_param |
Integer value specifying the minClusterSize parameter of the function cutreeHybrid. See section Details below. |
min_value_vector |
Numeric vector. For each value in the vector, the function clustering_angular_distance is run with parameter min_value equal to one element of the vector min_value_vector. |
threshold |
Numeric value. If a base has heteroplasmy greater or equal to threshold in more than max_frac of cells, then the base is not considered for down stream analysis. |
index |
Fifth element returned by get_heteroplasmy. |
max_frac |
Numeric value.If a base has heteroplasmy greater or equal to threshold in more than max_frac of cells, then the base is not considered for down stream analysis. |
Clustree plot.
Gabriele Lubatti [email protected]
https://cran.r-project.org/package=clustree
For each pair of samples and for each base, an angular distance matrix is computed based on the four allele frequencies. Then only the angular distances corresponding to the relevant_bases are kept. If relevant bases is NULL, then only the angular distances corresponding to the bases with relative distance variance among samples above min_value are kept . Finally the distance between each pair of samples is defined as the euclidean distance of the angular distances corresponding to the bases that pass the previous filtering step. On this final distance matrix, a hierarchical clustering approach is performed using the function cutreeHybrid of the package dynamicTreeCut.
clustering_angular_distance( heteroplasmy_matrix, allele_matrix, cluster, top_pos, deepSplit_param, minClusterSize_param, threshold = 0.2, min_value, index, relevant_bases = NULL, max_frac = 0.7 )clustering_angular_distance( heteroplasmy_matrix, allele_matrix, cluster, top_pos, deepSplit_param, minClusterSize_param, threshold = 0.2, min_value, index, relevant_bases = NULL, max_frac = 0.7 )
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
allele_matrix |
Fourth element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
top_pos |
Numeric value. Number of bases sorted with decreasing values of distance variance (see section Details below) among samples. If relevant_bases=NULL, then the bases for performing hierarchical clustering are the ones whose relative variance (variance of the base divided sum of variance among top_pos bases) is above min_value. |
deepSplit_param |
Integer value between 0 and 4 for the deepSplit parameter of the function cutreeHybrid. See section Details below. |
minClusterSize_param |
Integer value specifying the minClusterSize parameter of the function cutreeHybrid. See section Details below. |
threshold |
Numeric value. If a base has heteroplasmy greater or equal to threshold in more than max_frac of cells, then the base is not considered for down stream analysis. |
min_value |
Numeric value. If relevant_bases=NULL, then the bases for performing hierarchical clustering are the ones whose relative variance (variance of the base divided sum of variance among top_pos bases) is above min_value. |
index |
Fifth element returned by get_heteroplasmy. |
relevant_bases |
Character vector of bases to consider as features for performing hierarchical clustering on samples.Default=NULL. |
max_frac |
Numeric value.If a base has heteroplasmy greater or equal to threshold in more than max_frac of cells, then the base is not considered for down stream analysis. |
It returns a list with 4 elements:
classification |
Dataframe with two columns and n_row equal to n_row in heteroplasmy_matrix. The first column is the old cluster annotation provided by cluster. The second columns is the new cluster annotation obtained with hierarchical clustering on distance matrix based on heteroplasmy values. |
dist_ang_matrix |
Distance matrix based on heteroplasmy values as defined in the section Details |
top_bases_dist |
Vector of bases used for hierarchical clustering. If relevant_bases is not NULL, then top_bases_dist=NULL |
common_idx |
Vector of indices of samples for which hierarchical clustering is performed. If index is NULL, then common_idx=NULL |
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/dynamicTreeCut/versions/1.63-1/topics/cutreeHybrid
detect_insertion
detect_insertion(ref_sequence, different_sequence, length_comparison = 10)detect_insertion(ref_sequence, different_sequence, length_comparison = 10)
ref_sequence |
Character vector whose elements are the bases of a DNA sequence to use as reference. |
different_sequence |
Character vector whose elements are the bases of a DNA sequence different from the reference. |
length_comparison |
Integer number. Number of bases to consider for the comparison between the two DNA sequences in order to detect and remove insertions in the non-reference sequence. |
Character vector of the different_sequence with length equal to ref_sequence, after having removed the insertions.
Gabriele Lubatti [email protected]
dpt_test
dpt_test(heteroplasmy_matrix, time, index = NULL, method = "GAM")dpt_test(heteroplasmy_matrix, time, index = NULL, method = "GAM")
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
time |
Vector of diffusion pseudo time. |
index |
index returned by get_heteroplasmy. |
method |
Character name denoting the method to choose for assigning an adjusted p value to each of the bases. Can be one of GAM, pearson and spearman. GAM: For each base, a GAM fit with formula z ~ lo(t) is performed between the heteroplasmy values (z) and the time (t). The p value from the table "Anova for Parametric Effects" is then assigned to the base. pearson,spearman:for each base, a pearson or spearman correlation test is performed between the heteroplasmy values and the time . The p value obtained from the test is then assigned to the base. In all the three possible methods, all the p values are then corrected with the method FDR. |
A data frame with 2 columns and number of rows equal to n_col in heteroplasmy_matrix. In the first column there are the names of the bases while in the second column there are the adjusted p value.
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/gam/versions/1.20/topics/gam
filter_bases
filter_bases(heteroplasmy_matrix, min_heteroplasmy, min_cells, index = NULL)filter_bases(heteroplasmy_matrix, min_heteroplasmy, min_cells, index = NULL)
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
min_heteroplasmy |
Numeric value. |
min_cells |
Numeric value. |
index |
Fifth element returned by get_heteroplasmy. |
Character vector of bases that have an heteroplasmy greater than min_heteroplasmy in more than min_cells.
Gabriele Lubatti [email protected]
get_distribution
get_distribution(heteroplasmy_matrix, FUNCTION, index = NULL)get_distribution(heteroplasmy_matrix, FUNCTION, index = NULL)
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
FUNCTION |
A character specifying the function to be applied on each column of matrix. The possible values are: mean,max,min,median and sum. |
index |
index returned by get_heteroplasmy. |
It returns a vector with length equal to n_col of matrix where each element contains the result of the operation defined by FUNCTION.
Gabriele Lubatti <[email protected]>
It is one of the two main functions of the MitoHEAR package (together with get_raw_counts_allele). It computes the allele frequencies and the heteroplasmy matrix starting from the counts matrix obtained with get_raw_counts_allele.
get_heteroplasmy( raw_counts_allele, name_position_allele, name_position, number_reads, number_positions, filtering = 1, my.clusters = NULL )get_heteroplasmy( raw_counts_allele, name_position_allele, name_position, number_reads, number_positions, filtering = 1, my.clusters = NULL )
raw_counts_allele |
A raw counts matrix obtained from get_raw_counts_allele. |
name_position_allele |
A character vector with elements specifying the genomic coordinate of the base and the allele (obtained from get_raw_counts_allele). |
name_position |
A character vector with elements specifying the genomic coordinate of the base (obtained from get_raw_counts_allele). |
number_reads |
Integer specifying the minimum number of counts above which we consider the base covered by the sample. |
number_positions |
Integer specifying the minimum number of bases that must be covered by the sample (with counts>number_reads), in order to keep the sample for down-stream analysis. |
filtering |
Numeric value equal to 1 or 2. If 1 then only the bases that are covered by all the samples are kept for the downstream analysis. If 2 then all the bases that are covered by more than 50% of the the samples in each cluster (specified by my.clusters) are kept for the down-stream analysis. Default is 1. |
my.clusters |
Character vector specifying a partition of the samples. It is only used when filtering is equal to 2. Default is NULL |
Starting from raw counts allele matrix, the function performed two consequentially filtering steps. The first one is on the samples, keeping only the ones that cover a number of bases above number_positions. The second one is on the bases, defined by the parameter filtering. The heteroplasmy for each sample-base pair is computed as 1-max(f), where f are the frequencies of the four alleles.
It returns a list with 5 elements:
sum_matrix |
A matrix (n_row=number of sample, n_col=number of bases) with the counts for each sample/base, for all the initial samples and bases included in the raw counts allele matrix. |
sum_matrix_qc |
A matrix (n_row=number of sample, n_col=number of bases) with the counts for each sample/base, for all the samples and bases that pass the two consequentially filtering steps. |
heteroplasmy_matrix |
A matrix with the same dimension of sum_matrix_qc where each entry (i,j) is the heteroplasmy for sample i in base j. |
allele_matrix |
A matrix (n_row=number of sample, n_col=4*number of bases) with allele frequencies, for all the samples and bases that pass the two consequentially filtering steps. |
index |
Indices of the samples that cover a base, for all bases and samples that pass the two consequentially filtering steps (if filtering = 2); if all the samples cover all the bases (that is the case for filtering = 1), then index is NULL |
Gabriele Lubatti [email protected]
It is one the two main function of the MitoHEAR package (together with get_heteroplasmy). The function allows to obtain a matrix of counts (n_row = number of sample, n_col= 4*number of bases) of the four alleles in each base, for every sample. It takes as input a vector of sorted bam files (one bam file for each sample) and a fasta file for the genomic region of interest. It is based on the pileup function of the package Rsamtools.
get_raw_counts_allele(bam_input, path_fasta, cell_names, cores_number = 1)get_raw_counts_allele(bam_input, path_fasta, cell_names, cores_number = 1)
bam_input |
Character vector of sorted bam files (full path). Each sample is defined by one bam file. For each bam file it is needed also the index bam file (.bai) at the same path. |
path_fasta |
Character string with full path to the fasta file of the genomic region of interest. |
cell_names |
Character vector of sample names. |
cores_number |
Number of cores to use. |
A list with three elements:
matrix_allele_counts |
Matrix of counts (n_row = number of sample, n_col= 4*number of bases) of the four alleles in each base, for every sample. The row names is equal to cell_names. |
name_position_allele |
Character vector with length equal to n_col of matrix_allele_counts. Each element specifies the coordinate of genomic position for a base and the allele. |
name_position |
Character vector with length equal to n_col of matrix_allele_counts. Each element specifies the coordinate of genomic position for a base. |
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/Rsamtools/versions/1.24.0/topics/pileup
get_wilcox_test
get_wilcox_test(heteroplasmy_matrix, cluster, label_1, label_2, index = NULL)get_wilcox_test(heteroplasmy_matrix, cluster, label_1, label_2, index = NULL)
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
label_1 |
Character name of a first label included in cluster. It denotes the first group used for the Wilcoxon test |
label_2 |
Character name of a second label included in cluster and different from label_1. it denotes the second group used for the Wilcoxon test. |
index |
Fifth element returned by get_heteroplasmy. |
It returns a vector of length equal to n_row in matrix. Each element stands for a base and it contains the adjusted p-value (FDR), obtained in unpaired two-samples Wilcoxon test from the comparison of the heteroplasmy between the label_1 and label_2 group.
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/stats/versions/3.6.2/topics/wilcox.test
plot_allele_frequency
plot_allele_frequency( position, heteroplasmy_matrix, allele_matrix, cluster, names_allele_qc, names_position_qc, size_text, index )plot_allele_frequency( position, heteroplasmy_matrix, allele_matrix, cluster, names_allele_qc, names_position_qc, size_text, index )
position |
Character name of the base to plot. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
allele_matrix |
Fourth element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
names_allele_qc |
Character vector with length equal to n_col of allele_matrix. Each element specifies the name of the base and the allele. |
names_position_qc |
Character vector with length equal to n_col of allele_matrix. Each element specifies the name of the base. |
size_text |
Character specifying the size of the text for gridExtra function grid.arrange) |
index |
Fifth element returned by get_heteroplasmy. |
grid.arrange plot of allele frequencies of a specific base across samples divided according to cluster.
Gabriele Lubatti [email protected]
https://cran.r-project.org/package=gridExtra
plot_base_coverage
plot_base_coverage( sum_matrix, sum_matrix_qc, selected_cells, interactive = FALSE, text_size = 10 )plot_base_coverage( sum_matrix, sum_matrix_qc, selected_cells, interactive = FALSE, text_size = 10 )
sum_matrix |
First element returned by the function get_heteroplasmy. |
sum_matrix_qc |
Second element returned by the function get_heteroplasmy. |
selected_cells |
Character vector with cells used fro plotting the coverage. |
interactive |
Logical. If TRUE an interactive plot is produced. |
text_size |
Character specifying the size of the text for ggplot2. |
ggplot2 object (if interactive=FALSE) or plotly object (if (if interactive=TRUE)
Gabriele Lubatti [email protected]
plot_batch
plot_batch(position, heteroplasmy_matrix, batch, cluster, text_size, index)plot_batch(position, heteroplasmy_matrix, batch, cluster, text_size, index)
position |
Character name of the base to plot. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
batch |
Vector of batch names,with length equal to n_row of heteroplasmy_matrix. |
cluster |
Vector specifying a partition of the samples. |
text_size |
Character specifying the size of the text for ggplot2. |
index |
Fifth element returned by get_heteroplasmy. |
ggplot2 object of the heteroplasmy level of a specific base across samples divided according to batch.
Gabriele Lubatti [email protected]
plot_cells_coverage
plot_cells_coverage(sum_matrix, cells_selected, cluster, interactive = FALSE)plot_cells_coverage(sum_matrix, cells_selected, cluster, interactive = FALSE)
sum_matrix |
First element returned by the function get_heteroplasmy. |
cells_selected |
Character vector of cells for which the coverage is computed. |
cluster |
Character vector with partition information for cells specified in cells_selected |
interactive |
Logical. If TRUE an interactive plot is produced. |
ggplot2 object (if interactive=FALSE) or plotly object (if interactive=TRUE)
Gabriele Lubatti [email protected]
plot_condition
plot_condition( distribution_1, distribution_2, label_1, label_2, name_x, name_y, name_title )plot_condition( distribution_1, distribution_2, label_1, label_2, name_x, name_y, name_title )
distribution_1, distribution_2
|
Numeric vector |
label_1 |
Character vector of length equal to distribution_1 |
label_2 |
Character vector of length equal to distribution_2 |
name_x |
Character name specifying the xlab argument in ggplot2. |
name_y |
Character name specifying the ylab argument in ggplot2. |
name_title |
Character name specifying the ggtitle argument in ggplot2. |
ggplot2 boxplot of the quantities specified by distribution_1 and distribution_2, separated by the conditions denoted by label_1 and label_2.
Gabriele Lubatti [email protected]
plot_coordinate_cluster
plot_coordinate_cluster(coordinate_dm, cluster)plot_coordinate_cluster(coordinate_dm, cluster)
coordinate_dm |
Dataframe whit samples on the rows and coordinates names on the columns. |
cluster |
Vector specifying a partition of the samples. |
ggplot2 object.
Gabriele Lubatti [email protected]
plot_coordinate_heteroplasmy
plot_coordinate_heteroplasmy( coordinate_dm, heteroplasmy_matrix, index, name_base )plot_coordinate_heteroplasmy( coordinate_dm, heteroplasmy_matrix, index, name_base )
coordinate_dm |
Dataframe whit samples on the rows and coordinates names on the columns. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
index |
Fifth element returned by get_heteroplasmy. |
name_base |
Character name specifying the base. |
ggplot2 object.
Gabriele Lubatti [email protected]
plot_correlation_bases
plot_correlation_bases(bases_vector, index, heteroplasmy_matrix)plot_correlation_bases(bases_vector, index, heteroplasmy_matrix)
bases_vector |
Character vector specifying the bases for which the spearman correlation across samples is computed. |
index |
Fifth element returned by get_heteroplasmy. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
Heatmap plot produced by function Heatmap
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/ComplexHeatmap/versions/1.10.2/topics/Heatmap
plot_distance_matrix
plot_distance_matrix(dist_ang_matrix, cluster)plot_distance_matrix(dist_ang_matrix, cluster)
dist_ang_matrix |
Distance matrix obtained from clustering_angular_distance (second element of the output). |
cluster |
Vector.Can be one of the two partitions returned by function clustering_angular_distance (first element of the output). |
Heatmap plot produced by function Heatmap
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/ComplexHeatmap/versions/1.10.2/topics/Heatmap
plot_distribution
plot_distribution(quantity_counts_cell, name_x, name_title)plot_distribution(quantity_counts_cell, name_x, name_title)
quantity_counts_cell |
Vector returned by get_distribution |
name_x |
Character name specifying the xlab argument in ggplot2. |
name_title |
Character name specifying the ggtitle argument in ggplot2. |
ggplot2 density plot of the Vector quantity_counts_cell.
Gabriele Lubatti [email protected]
plot_dpt
plot_dpt(position, heteroplasmy_matrix, cluster, time, gam_fit_result, index)plot_dpt(position, heteroplasmy_matrix, cluster, time, gam_fit_result, index)
position |
Character name of the base to plot. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
time |
Vector of diffusion pseudo time,with length equal to n_row of heteroplasmy_matrix. |
gam_fit_result |
Data frame returned by dpt_test. |
index |
Fifth element returned by get_heteroplasmy. |
ggplot object of the heteroplasmy level of a specific base across samples and the GAM fitted curve. The title shows the adjusted p value (FDR) for the position obtained from get_heteroplasmy.
Gabriele Lubatti [email protected]
https://cran.r-project.org/package=gam
plot_genome_coverage
plot_genome_coverage(biomart_file, path_fasta, chr_name, heteroplasmy_matrix)plot_genome_coverage(biomart_file, path_fasta, chr_name, heteroplasmy_matrix)
biomart_file |
Character string with full path to the txt file downloaded from BioMart https://m.ensembl.org/info/data/biomart/index.html . It must have the following five columns:Gene.stable.ID, Gene.name, Gene.start..bp., Gene.end..bp., Chromosome.scaffold.name |
path_fasta |
Character string with full path to the fasta file of the genomic region of interest. It should be the same file used in get_raw_counts_allele. |
chr_name |
Character specifying the name of the chromosome of interest. It must be one of the names in the Chromosome.scaffold.name column from the biomart_file. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
Plot as returned by karyoploteR package.
Gabriele Lubatti [email protected]
http://bioconductor.org/packages/release/bioc/html/karyoploteR.html
plot_heatmap
plot_heatmap( new_classification, old_classification, dist_ang_matrix, cluster_columns = F, cluster_rows = T, name_legend )plot_heatmap( new_classification, old_classification, dist_ang_matrix, cluster_columns = F, cluster_rows = T, name_legend )
new_classification |
Character vector.Second column of the dataframe returned by function clustering_angular_distance (first element of the output). |
old_classification |
Character vector. First column of the dataframe returned by function clustering_angular_distance (first element of the output). |
dist_ang_matrix |
Distance matrix obtained from clustering_angular_distance (second element of the output). |
cluster_columns |
Logical. Parameter for cluster_columns argument of the function Heatmap in the package ComplexHeatmap |
cluster_rows |
Logical. Parameter for cluster_rows argument of the function Heatmap |
name_legend |
Character value.Parameter for name argument of the function Heatmap |
Heatmap plot produced by function Heatmap
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/ComplexHeatmap/versions/1.10.2/topics/Heatmap
plot_heteroplasmy
plot_heteroplasmy(position, heteroplasmy_matrix, cluster, index)plot_heteroplasmy(position, heteroplasmy_matrix, cluster, index)
position |
Character name of the base to plot. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
index |
Fifth element returned by get_heteroplasmy. |
ggplot object of the heteroplasmy level of a specific base across samples divided according to cluster.
Gabriele Lubatti [email protected]
plot_heteroplasmy_variability
plot_heteroplasmy_variability( heteroplasmy_matrix, cluster, threshold = 0.1, frac = FALSE, index )plot_heteroplasmy_variability( heteroplasmy_matrix, cluster, threshold = 0.1, frac = FALSE, index )
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
cluster |
Vector specifying a partition of the samples. |
threshold |
Numeric value. |
frac |
Logical. If FALSE the absolute number of cells that have at least one base with heteroplasmy above threshold are shown separated by cluster. If TRUE, then the fraction of cells are shown. |
index |
Fifth element returned by get_heteroplasmy. |
ggplot2 object
Gabriele Lubatti [email protected]
plot_spider_chart
plot_spider_chart(name_base, cluster, heteroplasmy_matrix, index)plot_spider_chart(name_base, cluster, heteroplasmy_matrix, index)
name_base |
Character name specifying the base. |
cluster |
Vector specifying a partition of the samples. |
heteroplasmy_matrix |
Third element returned by get_heteroplasmy. |
index |
Fifth element returned by get_heteroplasmy. |
radarchart plot produced by function radarchart.
Gabriele Lubatti [email protected]
https://rdrr.io/cran/fmsb/man/radarchart.html
We compute the variation of information (VI) between the partition provided by new_classification and old_classification. The VI between a random partitions (obtained with re-shuffle from original labels in old_classification) and old_classification is also computed. A distribution of VI values from random partitions is built. Finally, from the comparison with this distribution, an empirical p value is given to the VI of the unsupervised cluster analysis.
vi_comparison(old_classification, new_classification, number_iter)vi_comparison(old_classification, new_classification, number_iter)
old_classification |
Character vector. First column of the dataframe returned by function clustering_angular_distance (first element of the output). |
new_classification |
Character vector.Second column of the dataframe returned by function clustering_angular_distance (first element of the output). |
number_iter |
Integer value. Specify how many random partition are generated (starting from re-shuffle of labels in old_classification). |
Empirical p value.
Gabriele Lubatti [email protected]
https://www.rdocumentation.org/packages/mcclust/versions/1.0/topics/vi.dist