NEWS.md
In jmw86069/platjam: Platform Jam, biological platform importers.

platjam 0.0.90.900

coverage_matrix2nmat()
Updated to accept ".matrix" and ".matrix.gz" files.
summit_from_vector() called during recentering, now uses jamba::call_fn_ellipsis() to ensure ... are recognized arguments.

platjam 0.0.89.900

import_proteomics_PD()
Fixed bug caused by presence of columns containing NA values, which then were incorrectly removed, causing a colnames-to-data mismatch in length.
Bumped jamba version to 0.0.103.900 to include a fix in readOpenxlsx() when using a vector of rows, which was causing colnames to be incorrectly populated with data from the wrong row.

platjam 0.0.88.900

Two new capabilities for coverage heatmaps, re-center and re-strand coverage matrix data. The driving use case is to re-center data using coverage under ATAC-seq peaks, then define strandedness using "+" and "-" strand RNA-seq or 4sU-seq (nascent RNA-seq) coverage data. Re-centered peaks should show some focusing of other coverage tracks, including visualization of +1 and +2 nucleosomes beside the ATAC-seq peaks.

recenter_nmatlist()
Intended workflow:
- create coverage matrix data with wider range than needed (e.g. 10kb)
- recenter data by the summit, which creates missing data at the edges
- create heatmaps with desired range (e.g. 2kb) to avoid missing data
Takes input nmatlist, one or more entries are used to define a new summit position. Then all nmatlist data is shifted to the summit.
The summit is defined using smooth.spline() to smooth out the noise spikes, making the estimate much more accurate than using the single-point maximum.
The option invert_coverage inverts coverage with (max - x) so it can also be used to find the "trough" (inverted peak, the low-point).
restrand_nmatlist()
Intended workflow:
- Create coverage files centered ATACseq or TF-ChIPseq peak. Expectation is that it may associate with enhancers or other transcription in strand-specific manner.
- Define "strandedness" using another coverage track, use the side with higher coverage: "use left", or "use right".
- Reverse the orientation of signal data for rows with "use left".
Takes input nmatlist, one or more entries are used to define strandedness.
The option invert_coverage inverts coverage with (max - x), which also reverses the strandedness. It allows providing "+" strand and "-" strand data as separate tracks, using invert_coverage=TRUE for the "-" strand data.
summit_from_vector() - to determine a summit position given a numeric vector, using smooth.spline().

nmatlist2heatmaps()
small change, the enrichment score is now calculated using transformed data when transform is defined. Previously it used un-transformed data, though in practice it makes little difference.
New arguments recenter and restrand enable the new functions recenter_nmatlist() and restrand_nmatlist(), passing all arguments to those functions.
Output includes adjust_df when recenter or restrand is enabled, which contains the output from that adjustment.
The heatmap caption includes "Adjustments" when recenter or restrand is enabled, with the heatmaps used.
New argument legend_fontsize to adjust all legend fonts. When two values are provided, they are applied to the title, and labels, respectively.

platjam 0.0.87.900

import_proteomics_PD(), import_lipotype_csv(), import_nanostring_rcc()
fixed missing package prefix SummarizedExperiment::rowData(), also for colData(), assays()
convert_PD_df_to_SE() used by import_proteomics_PD()
Added include_source=TRUE when ann_lib has multiple values, consistent with behavior in import_proteomics_mascot().
nmatlist2heatmaps()
The caption is now rendered using ComplexHeatmap::Legend() so it uses the same positioning and font size, instead of being tucked into the corner where it often overlapped other text. The Legend also includes the sort column(s) byCols and indicates whether rows are ordered by Enrichment Score, or with user-provided values.
Default change profile_linetype=c(1, 5, 3) so the default condition uses different linetypes, easier to distinguish visually. Previous was profile_linetype=1.
New argument legend_padding to adjust whitespace beside heatmaps before the color legend is drawn. It is applied to HEATMAP_LEGEND_PADDING and ANNOTATION_LEGEND_PADDING.
row_order is much more rigorously handled
- values must be unique integers, consistent with order() output.
- row_order is applied properly after byCols when both are provided.

platjam 0.0.86.900

Added cli as package dependency, mostly for messaging.

import_omics_data()
generic data import, convenient way to create SummarizedExperiment.
It recognized curation_txt consistent with other import functions, to add sample annotations, and possibly re-order or subset data to match the order and content of the curation_txt data.
This function may need some real world testing to confirm its feature set.

platjam 0.0.85.900

import_nanostring_rcc()
Fixed bug causing the order of internal Nanostring annotation to be mismatched with rows supplied by curation_txt. The bug is limited to Nanostring RCC annotations and does not affect the correct order of annotations supplied by curation_txt, however it could cause the Nanostring annotations to be out of order. These annotations are not typically used downstream, however it would impact things like "Lane_CartridgeID", "Lane_BindingDensity", "Lane_FovCounted".
nmatlist2heatmaps()
Added missing package prefix when anno_mark_rows is supplied, calling ComplexHeatmap::anno_mark().

platjam 0.0.84.900

nmatlist2heatmaps()
New arguments partition_counts=TRUE by default appends the number of rows in each row partition (and/or k-cluster). Format is controlled with partition_count_template using glue().
When duplicate heatmap names are supplied, they are resolved without error.
New arguments row_anno_padding and column_anno_padding add default 4 mm padding between heatmaps and annotation, to give clear separation between heatmap and annotations.

platjam 0.0.83.900

parse_ucsc_gokey()
Splits input track_lines by newline when detected.
Ignores comment lines beginning with optional whitespace then "#".
Argument overlay_grep no longer uses "R" and "L" (case-insensitive) to detect stranded tracks, problematic for tracks with any form of "L" or "R". Ouch, haha.

platjam 0.0.82.900

Added stringi to package dependencies, for word wrap without incurring heavy dependencies from stringr (which calls stringi anyway).
nmatlist2heatmaps()
Added option to hide the caption, but do_caption=TRUE is default.
New arg caption_fontsize=10 to control caption text size.
The caption includes byCols columns in the anno_df used to order the rows.
When data is transformed, the transform is no longer printed inside parentheses.
The color legend now uses adjust_annotation_extension=TRUE to ensure the legend does not overlap the annotation labels.
Color legend titles are word-wrapped at 15 characters, to handle very wide multi-word labels.
raster_by_magick by default checks that magick is available.

apply_word_wrap() - calls stringi::stri_wrap() and combines vectors by sep, default "\n" for multi-line word wrap by default. It improves base::strwrap() by also offering whitespace_only=TRUE so that strings can be split at "-" and other light punctuation, instead of requiring a space " ".

platjam 0.0.81.900

rmd_tab_iterator()
Fixed bug when base_fn contained argument test, the environment was not properly defined before testing whether the tab should be visible, even though the environment was properly defined before calling the subsequent function base_fn(..., test=FALSE).

platjam 0.0.80.900

import_nanostring_rcc()
added prefix to call jamba::pasteByRow()
changed detection of positive/negative control probes to use "^POS_" and "^NEG_" instead of previous "^POS", "^NEG". Previous approach would mark "POSTN" a positive control, when it is an endogenous gene.

import_nanostring_rcc()
New argument curation_txt to include sample curation during import.
import_nanostring_rlf()
changed default plot_type="none" so the default is not to create a color assignment plot.

platjam 0.0.79.900

rmd_tab_iterator() - major update
base_fn() can now contain optional argument test=TRUE to determine whether a particular tab should be displayed.
- When base_fn() is called with test=TRUE it is expected to return logical indicating whether the tab should be displayed, and should provide no other output. It will be called again with test=FALSE if the tab should be displayed, in which case the function should generate output.
- When base_fn() does not contain named argument test, the tab is always displayed, the function is called only once, and it should generate output as normal.
base_fn and fn_list functions are all wrapped inside tryCatch() which prints the error message and does not exit the iterator.
fn_list will likely be deprecated and retired in the near future, relying upon base_fn for all tasks.
import_salmon_quant()
Fixed rare error "duplicate 'row.names' are not allowed" caused by "gene_body" transcripts (unspliced transcripts) which also contained the strand "(+)" or "(-)" and were being removed by the default argument: trim_tx_from=c("[(][-+][)]"). This situation occurs when one gene locus (defined by "gene_name") is present on two strands (which probably should never happen, but in some Gencode files it does; perhaps by using gene_name and not gene_id). The argument default is now trim_tx_from=NULL which also makes sense that the default condition is not to change the rownames, nor the values in txColname="transcript_id".
Fixed argument help docs, which incorrectly used curate_tx_from, curate_tx_to instead of trim_tx_from, trim_tx_to.
print_color_list()
fixed error with function elements using the updated hex style from circlize::colorRamp2().
added examples.

platjam 0.0.78.900

import_nanostring_csv() two changes when supplying curation_txt:
The output se is subset to include only sample which were annotated in the curation_txt file.
The order of samples now matches that with the curation_txt file.

platjam 0.0.77.900

nmatlist2heatmaps()
new argument anno_row_gp with default fontsize 14 for row marks when anno_row_marks is provided.
anno_row_labels now accepts one or more columns in anno_df to define labels, when anno_row_marks is provided. Not super convenient, because row labels are most likely not shown as anno_df columns.
anno_row_labels now tolerates when names(anno_row_labels) is not defined, and uses anno_row_marks by default.
apply arg axis_name_gp to anno_enriched() axis labels, for consistent font size for x-axis labels, and profile y-axis labels.
axis_name_gp default fontsize 10, instead of 8 previously.
column_title_gp default font size is 14, instead of 12 previously.
legend_base_nrow=12 is default, mainly to provide two columns for human chromosomes, but one column for most other scenarios.
new argument title_gp with default fontsize 14 for the overall title.

platjam 0.0.76.950

zoom_nmat() now accepts "" or "none" to avoid transformation
nmatlist2heatmaps()
new default main_heatmap=NULL causes all heatmaps to be used for row ordering. The enriched score is calculated for each heatmap, summed by row, then used to produce decreasing order.
new argument transform_label to customize transformation labels included below each coverage heatmap title. By default it uses the character string from transform for anything except "none".
new argument padding to add whitespace padding around the heatmap set.
axis_name now accepts single character input to customize the center label.
A default caption is added to the bottom-right corner of the output, which describes basic information about the figure: number of heatmaps, number of rows, whether k-means was used and which method, the total number of row partitions, and which heatmaps were used for row ordering and k-means clustering.
returned data include fn_params with a list of important parameters associated with the heatmaps. Notably some values are calculated on the fly, like when panel_groups is defined: ylims, signal_ceiling, nmat_colors, etc.
default color ramp is "Reds"
main_heatmap can now accept multiple values, causing row_order by default to order using the sum EnrichedHeatmap::enriched_score() across each heatmap, before being ordered as usual.
row_order will by default substitute NA values with 0, in rare cases that NA values may exist, maybe caused during transformation.
argument k_method="correlation" is a new default, which falls back to "euclidean" if the amap package is not installed.
new argument min_rows_per_k=100 requires at least 100 rows per k-means cluster, to protect from clustering with a very small number of rows. The argument was motivated by using partition and k_clusters together, for which the number of rows in each partition is not (easily) known upfront. However, it is also useful to set k_clusters and be assured that at least min_rows_per_k on average are available during clustering.
Added new example demonstrating use of partition and k_clusters.
Added and updated function documentation for clarity.
silenced verbose output "Preparing ComplexHeatmap::draw()"
added more error-checking and specific error messages when matching across the optional inputs, all of which must match when provided:
- rows
- rownames(nmat)
- rownames(anno_df)
- names(partition)
partition is handled internally as a factor so the level order is maintained. If supplied as factor the levels are honored as given, even when combined with k_clusters as below.
kmeans() warnings are suppressed, otherwise they interfere with RMarkdown output.
k_clusters and partition work together
- each partition is individually k-means clustered
- k_clusters can be a vector, applied to each partition in order, or directed by names(k_clusters) if all partitions have an associated value in names(k_clusters). Otherwise k_clusters is recycled to the number of partitions, then applied in order.
- For each partition, k requires at least 10 rows per k rounded up. A partition with 10 rows can only have k=1, and partition with 11 rows can have k=2, etc. This step protects from k-means clustering small partitions.
- partition colors are assigned to partition first, then colors are split by jamba::color2gradient() across k-means clusters within each partition.
k_method now also offers "spearman" for rank-based correlation metrics, although this method has not been widely tested on genome coverage data.

platjam 0.0.75.900

rmd_tab_iterator()
Intended to help RMarkdown documents generate tabbed output, even allowing multiple layers of tabs, usually to configure the same visualization with a few different options.
Provide a list of vectors to use for tabs.
It iterates each layer of tabs, defines variables in the appropriate environment to be "seen" by subsequent layers of tabs.
The base layer calls a function, usually producing a figure or table.
The process clean up R code, preventing multiple layers of for loops or lapply() calls.
This function may be moved into jamba eventually, but for now is being tested and may be updated rapidly based upon real use cases.

platjam 0.0.74.900

design2colors()
simplified how class and group colors are assigned overall
simplified the call to colorjam::rainbowJam(), no longer assigning color hue (then applying color warping in colorjam), instead using colorjam::rainbowJam() since it has additional logic for low n color hue assignments. Pushes all aesthetic choices to rainbowJam().
Changed how phase is applied, so the ordered phase is applied only to non-padded colors. When class_pad or end_hue_pad insert blank colors to absorb the corresponding color hue, the phase is not consumed, since phase is intended to be applied across the final set of colors. Previously, the phase would be out of phase with the final colors, so to speak, making the output colors appear weird.
Fixed application of end_hue_pad and class_pad together, previously it only applied class_pad.
class_pad is applied partially at the start and end of the color wheel, splitting the padding before the first and after the last color hue.
color_sub can substitute for class or group colors without requiring all values in the column be matched. Useful for altering one color in a set.
Improved color saturation for class colors created when blending corresponding group colors. The process uses colorjam::vibrant_color_by_hue() to determine the most vibrant color for the same hue, then blends this color with the original class color.

platjam 0.0.73.900

dependency version bump for colorjam (>= 0.0.26.900)

quick_complement_color() was updated to match recent updates to colorjam version 0.0.26.900. This change also affected design2colors()
design2colors()
preset="dichromat2" new default, so colors begin with yellow, more conducive for applying to control groups than starting with red.

platjam 0.0.72.900

The functions related to coverage heatmaps are being migrated into "jmw86069/coverjam" Github-hosted R package, for cleaner maintenance of those functions.

platjam 0.0.71.900

import_metabolomics_niehs()
added optional step to import "compounds_pos.txt" and "compounds_neg.txt" files, which contains important annotations for which measurements are imputed by the upstream software, and using which impute method.
When the files above are not present, and the file "1_DataProcessed.zip" exists, it is used to extract the raw files as named above.
When no matching files are detected, this import step is skipped.

convert_imputed_assays_to_na()
utility function used to apply filtering based upon the impute flags, thereby converting imputed data matching the relevant flags to NA, and storing in a new assays() entry for downstream analysis.
process_metab_compounds_file()
Internal function used to import full compounds data supplied as a data.frame after loading from the "1_DataProcessed.zip" file.
The function will merge data into a se_list object if supplied, otherwise it will return the full se object including each assay name imported from the file.

platjam 0.0.70.900

Added missing package prefix for several calls to jamba::nameVector(), or jamba::printDebug(). Affected functions:
import_nanostring_rcc()
coverage_matrix2nmat()
frequency_matrix2nmat()
nmatlist2heatmaps()

platjam 0.0.69.900

design2colors()
input recognizes DataFrame which is commonly produced from SummarizedExperiment::colData().
input recognizes tbl_df (tibble) and matrix by coercing to data.frame.
column sort can be reversed with "-" prefix. For example "-Treatment" will reverse the sort order in column "Treatment".
allow empty group_colnames so colors are assigned in all columns
tolerate various combinations of group_colnames, class_colnames with non-ideal cardinality, by using different workarounds strategies
new arguments Crange,Lrange which are passed to colorjam::rainbowJam() to set a less saturated color palette by default.

platjam 0.0.68.900

import_metabolomics_niehs()
Fixed bug when importing files that may contain duplicated rows in metadata, and in each data matrix file. The issue appears to be pure duplication of rows, so the workaround is to print a warning, and retain non-duplicated records per SampleID value.

platjam 0.0.67.900

import_metabolomics_niehs()
imports metabolomics data specifically in file formats used by the NIEHS Metabolomics Core Facility. The output is a list of SummarizedExperiment objects, typically including positive and negative ionization data.
curate_se_colData()
wrapper function to curate_to_df_by_pattern() specifically for SummarizedExperiment::colData(), updating data in place.
optionally this step can subset columns for those that match curated patterns.

platjam 0.0.66.900

import_salmon_quant() was using the older version of curate_to_df_by_pattern() supplied by slicejam instead of the slightly updated version in platjam (this package). Not such a big issue except that slicejam is not yet public.

platjam 0.0.65.900

added genejam Github information to DESCRIPTION, previously this package was not properly referenced as part of Github and would cause the package dependency to fail.

platjam 0.0.64.900

import_nanostring_csv()
new argument curation_txt for optional sample annotations during import; behaves exactly as with import_proteomics_mascot().
TODO: will add this argument to import_nanostring_rcc()
TODO: will create generic function for curation into SE colData()
fixed bug not prefixing rowData()
import_proteomics_mascot()
updated to fix error when colnames are changed by curation_txt

platjam 0.0.63.900

added testthis unit tests for some functions

assign_numeric_colors()
new argument color_max to define a fixed upper numeric threshold for the maximum color in the color gradient.
design2colors()
Changes to enable color_sub to accept color ramp names in addition to accepting single colors.
Slightly cleaned up some logic during color assignment.
New argument color_sub_max intended to be passed to assign_numeric_colors() argument color_max for particular column names.

platjam 0.0.62.900

import_proteomics_mascot()
Added more robust detection of changes in column order between the input Excel file and the curation_txt data.
The output column order now matches the order of the curation_txt file, which should be helpful when defining the control group in statistical contrasts.
curate_to_df_by_pattern()
new argument order_priority="df" to indicate the order of rows in the data.frame returned will match the curation df.
option order_priority="x" will order rows in the data.frame returned by the order of entries in x.
import_lipotype_csv()
minor changes to ensure the order of curated rows and sample identifiers were matched when the curation data did not contain "Filename" column, by default uses the last column returned by curate_to_df_by_pattern().

platjam 0.0.61.900

Proteomics data is sometimes provided in separate results files, which can later be merged into one larger format for downstream analysis.

merge_proteomics_se()
This function provides a specific method of merging two SummarizedExperiment objects, with heuristics appropriate for proteomics expression data.

platjam 0.0.60.900

jamba dependency was bumped to 0.0.89.900
added SummarizedExperiment and XML to dependencies

import_nanostring_csv() and import_nanostring_rcc()
both functions now return data transformed with log2(1 + x)
CSV import will name the assay "norm" if the CSV file contains that substring, otherwise defaults to "raw", consistent with RCC import.
The assay_name can be defined upfront for both functions.

validate_heatmap_params()
This function begins a process of making the coverage heatmaps into a command-line tool. Work in progress.

platjam 0.0.59.900

import_salmon_quant()
new arguments curate_tx_from, curate_tx_to to allow custom curation of transcript identifiers, specifically for transcripts where the FASTA workflow introduces "(-)" and "(+)" to the identifiers. This situation occurred when adding gene body transcripts to the Thuman T2Tv2.0 genome GTF entries.
design2colors()
argument color_sub will convert color names to hex format, for compatibility with some downstream uses, for example knitr::kable() and jamba::kable_coloring() when used in an Rmarkdown document.

platjam 0.0.58.900

import_salmon_quant() was errantly checking the class of tx2gene, causing it to ignore user-supplied tx2gene. This issue affected import when gtf was not supplied, which was much more common.

import_salmon_quant()
the list of assays now use names directly from tximport(), specifically c("counts", "abundance", "length"), and not c("counts", "tpm").
TxSE now contains assayName "length", and metadata item "countsFromAbundance", so the output can be used with tximport::summarizeToGene() as a second step outside this import process.
new argument option import_types="gene_body" designed specifically when the GTF or tx2gene contain entries representing unspliced multi-exon genes, in addition to spliced proper transcripts. When present:
- import_types="gene" will summarize transcripts to gene level, excluding entries annotated "gene_body", returned as GeneSE.
- import_types="gene_body" will summarize transcripts to gene level, including entries annotated "gene_body", returned as GeneBodySE.
- import_types="gene_tx" will summarize transcripts to gene level, and separately represents "gene_body" entries, returned as GeneTxSE.

platjam 0.0.57.900

import_nanostring_csv() is a basic import function for the common CSV style export from Nanostring software. This version has minimal extra capabilities, and produces a simple SummarizedExperiment object.

platjam 0.0.56.900

import_proteomics_PD() was updated to fix an errant check of the protein colnames. This check occurs to verify that the accession colnames did not contain delimited values, which causes the colnames to be split into individual values by jamba::makeNames() with suffix. When that happens, the original colname is added before the split columns so the original data can be verified.

import_proteomics_mascot() is a version 1 importer for MASCOT and similar data, which expects protein-level data with totalIntensity and numSpectra columns for each sample.

platjam 0.0.55.900

import_proteomics_PD() was updated to remove dependency on slicejam R package which is currently private during internal development. The only dependent function curate_to_df_by_pattern() was moved into this package.

platjam 0.0.54.900

design2colors() caused an error when there were no leftover categorical colors to be assigned after the initial group/class/lightness, then user-defined colors by colname. This bug has been fixed.

platjam 0.0.53.900

import_nanostring_rlf() is an import function to load Nanostring codeset data provided in the form of an RLF file.

design2colors() now calls colorjam::blend_colors() to define colors for each class. The method is still in development, so the specific methods may change. The output is intended to represent the group colors contained in each class, we'll see how well it fares.

design2colors() was updated to convert columns with class "table" into "integer", otherwise weird things happened during coersion, causing an error.

platjam 0.0.52.900

mean_hue() is a simple function to return a mean hue in degrees.
print_color_list() is a convenience function to convert a color list that may contain color vectors, or color functions, into a list of named color vectors. It will print to the console using those colors.

design2colors() was updated to to handle an edge condition.

Refactoring the workflow:
define colors by design:
- define colors to group_colnames optionally partitioned by class_colname
- define gradient colors to lightness_colnames
- define class colors using the mean hue for groups contained in each class
Apply design colors to all matching columns:
- Test all columns for compatible cardinality with group, lightness.
- Note: column names in color_sub will be ignored at this step, instead those columns use color_sub to generate a gradient.
- Assign colors to each compatible column.
- Note this step will include extra annotation columns that have consistent cardinality.
- (This might be the coolest step tbh, since it figures out which columns match the design.)
Expand color_sub with newly defined colors.
- Intent is to assign consistent categorical colors to values present in other columns.
For columns without assigned colors:
- Apply color_sub to the column when it matches the column name.
- Numeric columns produce a color function.
- Character columns produce a named color vector.
Assemble all remaining unassigned values:
- Numeric columns use the column name as its "value", to define one color to the column header.
- Remaining character values defined in color_sub are assigned.
- Remaining unassigned character values, and character column names of numeric columns are assigned categorical colors.
Apply new categorical colors
- For numeric columns, generate color function using the categorical color assigned to that column name.
- For character columns, generate a color vector.
Note that the mechanism used may change, I am still testing how the assumptions work with real world data.
New behavior: When color_sub is assigned to a value in colnames(x), the cardinality is not checked for consistency with group color assignments, and instead will use the color assigned for that column.
New argument force_consistent_colors:
During color assignment, sometimes a column value is assigned one color in a column, and a different color in another column. It usually happens when color_sub defines a color for a column, where that column unintentionally shares a value with another column that gets colors assigned earlier in the chain.
New argument force_consistent_colors=TRUE forces values to be assigned only one color. It seems obvious to use this option, but why not always?
For purely text strings, like "Treated" and "Untreated" one would think any time "Treated" appears in a graphic, it should use the same color. Yes. However, sometimes the number "2" appears in a column, as character or integer, it doesn't matter for this purpose. I have seen something like "sample_num" with values "1", "2", "3", etc. Their cardinality matches 1:1 with class/group/lightness color assignments defined by this function, so these values are usually also assigned to the group colors. However, these values may appear in another column defined by color_sub, intended to apply a gradient of that color to values in the column. What if that column contained values c(2, 20, 500, 1000)? Only these values would be colorized: c(20, 50, 1000), while 2 would be assigned the color from group colors. It looks weird.
There are workarounds:
- pre-filter columns which might have this effect. In the case above, remove "sample_num" before calling design2colors() so that column is not assigned a color.
- associate all numeric columns with color_sub
The end result, which is intended, is to allow columns to have independent color assignments when values in those columns are not related. In the case above, the number "2" means something different in one column than another column.

platjam 0.0.51.900

design2colors() was updated to adjust the low end of color gradient.
specifically when the low-high numeric range is above zero, for example c(20, 50). The adjustment lowers the low end of color scale 5% the diff, so the low actual color will not be white.
Also the function was using pretty() to generate reasonable numeric steps across the numeric range, and was using those steps to define the color gradient. This method had weird effects, partly due to pretty() making choices about the best visible number for display, instead of the point range. Instead, the color gradient is applied to the calculated number range, then that function is used to generate a color function across the pretty() scale. I'm not sure it is ideal when pretty() does not color the numeric range, but it seems reasonable so far.

platjam 0.0.50.900

import_proteomics_pd() was updated to handle absence of curation_txt where sample names and labels may or may not be renamed for each abundance matrix.
Specifically label_colname is detected as "Label", any column containing "Label", then "^Input$". Note "Input" is the default first colname produced when there is no curation_txt file, and should represent a unique column identifier.
design2colors() was updated:
class_colnames is required to have 1-to-many cardinality with group_colnames, or throws an error. As a result, class is guaranteed to be associated only with one set of columns.
class is assigned a color hue using the mean color hue of the groups it contains.
color_sub will apply a gradient color to numeric column values.
TODO: add some ability to pre-define class color with color_sub
TODO: add some ability to define numeric colors or color function for columns that contain numeric data. They are currently handled as categorical values, which is not ideal.

platjam 0.0.49.900

save_salmon_qc_xlsx() new argument verbose=FALSE, thus changing the default which included some verbose output by default.
df_to_numcolors() new argument trimRamp passed to jamba::getColorRamp() to trim edge colors from linear color gradient, thus making the colors less dramatic.

platjam 0.0.48.900

design2layout() is experimental, and is intended to determine appropriate plot panel layout dimensions, given experimental groups and batch information. It should help align panels within batch, then within group, into columns, so plots can be visually compared.
cardinality() takes two vectors and determines the data cardinality, in terms of "one-to-one", "one-to-many", "many-to-many", "many-to-one". This function may help detect when experimental factors are compatible with color assignment by group or other factors.
df_to_numcolors() is an experimental function only used to create a color substitution vector for use with kable_coloring().

platjam 0.0.47.900

new function `import_lipotype()`

Intended to import CSV formats provided by LipoType lipidomics data
Returns SummarizedExperiment object, with rowData and colData assigned as appropriate.
Next iteration will parse optional curation_txt to assign sample annotation for experimental design, factors, etc.

new function `design2colors()` (in development)

See examples ? design2colors() for usage.

Intended as an extension to colorjam::group2colors() that also utilizes subgroup (smaller subsets of groups), and group class (which includes multiple groups together).
If this function works well through early testing, it likely moves into colorjam for broader re-use.
I find myself assigning categorical colors by group, then using jamba::color2gradient() to split colors into light-to-dark gradient:
time course, 0-hr, 2-hr, 4-hr, 8-hr (light-to-dark)
treatment: untreated, treated (light-to-dark)
for each group: batch A, batch B (light-to-dark)
I find myself assigning these categorical colors to each SampleID, or to subgroups, or other factors, so the colors are consistent when used in tables, and ComplexHeatmap output.
assign colors to all annotation columns with appropriate cardinality
Finally, other factors need colors, they should differ from group colors
for each individual factor, assign unique categorical colors
re-use colors when a factor level already has an assigned color
Default output:
colors assigned for every column, and every column value of the input data.frame argument x.
Plots a graphical table of sample annotations showing color assignments using jamba::imageByColors().
list of colors, named by colnames(x), suitable for use with ComplexHeatmap::HeatmapAnnotation().
optionally a color vector, named by factor level.
optionally returns a data.frame with colors, in same order as input x, suitable for use directly in jamba::imageByColors().
Relevant arguments
group_colnames: defines categorical colors, one per group
lightness_colnames: assigns light-to-dark gradient to categorical colors
class_colnames: arranges groups into classes, so groups with same class are assigned similar color hues, with spacing between classes.
preset: defines the color wheel used by colorjam::rainbowJam():
- dichromat: dichromat-friendly color wheel, largely removes green
- ryb1: red-yellow-blue (common painter's color wheel for color mixing)
- rgb: red-green-blue (default R, shows how much of the wheel is green)

platjam 0.0.46.900

import_salmon_quant()
does the job of tximport::tximport(), then associates sample annotations via curation_txt to produce SummarizedExperiment objects at transcript and/or gene level.

platjam 0.0.45.900

get_salmon_meta()
now parses the fragment length distribution if the file exists. It returns mean, median, mode, and 25/75 percentiles.
Also the names(metafile) are maintaines as rownames in the output.

parse_salmon_flenfile() parses the Salmon fragment length file usually named "flenDist.txt", and return summary values: mean, median, mode, 25/75 percentiles.

platjam 0.0.44.900

UCSC track hub function parse_ucsc_gokey() was updated because apparently glue::glue() added a new argument .trim to trim whitespace from every output line AND made .trim=TRUE the default value. Because why be consistent with past versions of glue. Thank you again to all the R package authors that have chosen not to change the output of the primary function in their package by default. :) Not shown: All the updates I did not have to do because other core functions keep working as normal.

platjam 0.0.43.900

nmatlist2heatmaps() was updated to handle transformation of data during k-means clustering. Previously this function was not correctly defined.

platjam 0.0.42.900

import_proteomics_PD() gained some options to handle PD data content, such as referring Protein gene annotations into the peptide data during import. Apparently sometimes they only annotate the protein level, so this step recovers some annotations otherwise lost. Also sometimes peptide data is split across multiple rows when the peptide may appear in multiple positions in the same protein.

platjam 0.0.41.900

import_proteomics_PD() will import proteomics abundance data from Proteomics Discoverer software, focused on the Excel format in use in 2022 that includes protein abundance data, with nested sub-tables of peptide abundance data with different columns. The function will parse each type of row and return two SummarizedExperiment objects, one for protein data, one for peptide data. This function calls an internal helper function convert_PD_df_to_SE() which performs the work of parsing gene annotations, peptides, post-translational modifications, sample annotations, and optionally reads "curation.txt" to define specific sample group annotations for downstream analysis.

platjam 0.0.40.900

parse_ucsc_gokey() was updated to allow additional parameters to be defined through ... dot list. These values will override all values defined in the track lines.
Examples have been added to demonstrate minimal use of the function, showing composite track views, and multiWig overlay tracks.
new experimental argument multiwig_concat_header=TRUE allows adjusting the format of multiWig superTrack names, being tested inside the UCSC genome browser.

platjam 0.0.39.900

changes to `nmatlist2heatmaps()`

The ComplexHeatmap::draw() function by default includes the argument adjust_annotation_extension=TRUE described here https://jokergoo.github.io/ComplexHeatmap-reference/book/a-list-of-heatmaps.html#adjust-blank-space-caused-by-annotations
The problem was that y-axis labels on the right side of profile plots overlapped the color legends on the right side.
Alternatively, profile axis labels may be positioned on the left side, which avoids having to adjust the legend on the right side.
New argument top_axis_side with values "right", "left", "both", "all", "none"
New argument k_heatmap which defines which heatmap or heatmaps are used for k-means clustering. Key new feature, k-means clustering can now involve multiple heatmaps, which may be useful to find patterns across multiple signals. This feature is being tested currently.
save_salmon_qc_xlsx() was updated to include jamba:: function prefixes as needed.

set_xlsx_colwidths() and set_xlsx_rowheights() were removed, since they have been moved into package "jamba".
twostep_gradient(), showDichromat(), and make_jam_divergent() were moved into package "colorjam".
jam_divergent and jam_linear were moved into package "colorjam".

platjam 0.0.38.900

changes to `nmatlist2heatmaps()`

A series of changes was made to nmatlist2heatmaps():

New argument top_annotation to customize the annotation appearing above each heatmap. It takes several forms:
TRUE uses the default ComplexHeatmap::HeatmapAnnotation(EnrichedHeatmap::anno_enriched()) with some platjam-specific customizations, mainly to match the profile line colors to the partition and k_colors arguments for consistency.
FALSE hides the annotation
HeatmapAnnotation uses the function as provided
list of any combination of the above, recycled to length(nmatlist). The list input can be used for specific plots above each matrix, which can also specify the data used for those plots. Note option 3 above uses the closed form EnrichedHeatmap::anno_enriched() in order to be applied to the appropriate data matrix for each heatmap.
New argument top_anno_height which is a grid::unit object specifying the height of the top_annotation - only used when top_annotation is not supplied in custom form.
Help text for argument signal_ceiling includes reference to the child function get_nmat_ceiling() which controls the logic:
signal_ceiling above 1 applies the strict numeric value
signal_ceiling between 0 and 1 applies a quantile(x, probs=signal_ceiling)
signal_ceiling=NULL uses the maximum absolute value
Argument row_order is intended to work alongside byCols, so the sort of anno_df will also inlude sort for row order within each subset of anno_df as applicable.
New arguments raster_quality and raster_by_magick passed to ComplexHeatmap::Heatmap().
New arguments upstream_length, downstream_length used for optional zoom of the coordinate range being displayed. These arguments are passed to zoom_nmatlist() if either is not NULL.
New behavior when panel_groups are supplied:
heatmap_annotation_param will automatically hide duplicate color legends, and will use the panel_groups value for the color legend title.
top_annotation default axis will be hidden except for the last in each set of adjacent duplicated panel_groups. For example, panel_groups=c("A", "A", "B", "B", "A", "A") will display y-axis for entries c(2, 4, 6).
In future, heatmap panels may have slightly wider gap between different panel_groups values.

zoom_nmatlist() and zoom_nmat() are intended to help zoom into a particular range of coverage matrix data, where the stored coverage is wider than desired for the heatmap figure. They filter the columns in each normalizedMatrix and adjust the attributes stored in:
attr(nmat, "upstream_index") - the column index positions upstream the target region
attr(nmat, "downstream_index") - the column index positions downstream the target region
attr(nmat, "target_index") - the column index positions representing the target region
attr(nmat, "extend") - the genomic distance upstream and downstream the target region

platjam 0.0.37.900

get_track_defaults() was updated to adjust the default bigBed track settings, so the default display is "pack" but can be adjusted as needed.

platjam 0.0.36.900

parse_ucsc_gokey() handles bigBed tracks with specific composite track templates and relevant default values.

platjam 0.0.35.900

parse_ucsc_gokey() was updated to improve the method of naming supergroup and group tracks, so the supergroup name will persist for every group it should contain.
nmatlist2heatmaps() new argument trim_legend_title will trim heatmap legend title to remove any text following a newline. For example, the heatmap label may contain multiple lines of text which are useful to the heatmap, but less useful to the color legend. In that case, only the first line of text is used as the heatmap legend title.

nmathm_row_order() returns the rowname order of the heatmap produced by nmatlist2heatmaps(). When rows are partitioned, the output is a list of rowname vectors.

platjam 0.0.34.900

jam_linear and jam_divergent are new color gradients intended to be visibly distinct, and color-blind-friendly. The divergent scales in particular are designed so that the two directions are visibly distinct even under three different color blindness simulations from dichromat::dichromat().

nmatlist2heatmaps() changes that forced heatmap legend direction to be "vertical" were reverted, since Dr. Gu updatedComplexHeatmapto fix the issue withgrid` on R version 3.6.*.
nmatlist2heatmaps():
new argument pos_line to control display of lines around the target region
return values include HM_drawn which is the object returned after ComplexHeatmap::draw(), and which contains all the column and row orders for each heatmap.

platjam 0.0.33.900

nmatlist2heatmaps() encountered an error when displaying heatmap legend with direction="horizontal" which appears to be specific to R version R-3.6.1, and is not present in R-4.0.0 and above. Specifically I believe this error is from grid package version 3.6.1 and how the function unit.arithmetic() is called by ComplexHeatmap. Nonetheless, the workaround is to force direction="vertical" when grid package version is below 4.0.0.

platjam 0.0.32.900

nmatlist2heatmaps() new argument show_heatmap_legend is recycled to the length(nmatlist) to allow hiding legends for certain heatmaps. This update is intended when heatmaps are grouped by panel_groups which allows multiple heatmaps to have the same shared numeric color mapping.

platjam 0.0.31.900

nmatlist2heatmaps() updated so ylims will take priority over panel_groups=TRUE which defines its own ylims ranges.

platjam 0.0.28.900

nmatlist2heatmaps() bug with no k_clusters, no partition, and no k_colors would fail during profile plot because it had NULL color.

platjam 0.0.28.900

nmatlist2heatmaps() does more work to validate rows with respect to rownames of nmatlist, rownames(anno_df), and names(partition) to ensure everything is properly synchronized. The smallest common set of rows will be used.

nmatlist2heatmaps() now allows partition and k_clusters to be combined, so rows can be both partitioned, and kmeans clustered. Labels are created "partition - cluster_number" and are ordered by partition then kmeans cluster number. So if partition is a factor with ordered levels, that level will be preserved in the output.
nmatlist2heatmaps() new argument color_sub which allows defined categorical colors by sending a named vector. Any column in anno_df all of whose values are in names(color_sub) will be colored accordingly.
nmatlist2heatmaps() will use k_subset to re-order partitions, in addition to plotting only the subset of row partitions. The code was change to handle the sequence of operations: kmeans, partitioning, k_subset, then anno_df, marked rows.
nmatlist2heatmaps() changed the default ht_gap down to 3 mm.

platjam 0.0.27.900

Numerous small bug fixes in nmatlist2heatmaps(), mostly in handling annotation categorical color legends.

platjam 0.0.26.900

nmatlist2heatmaps() new default transform="none", previously was jamba::log2signed() which enforced log2 transformation. Frankly not sure which is best, might depend upon the range of data, which depends upon the type of coverage signal being used.
nmatlist2heatmaps() now treats annotation columns in anno_df as bi-directional when the max value is <= 50, which helps in cases that have values c(-1, 0, 1) and sometimes only c(0, 1). The end result is more numeric columns will have the same color gradient (blue-white-red).
nmatlist2heatmaps() displays legend with distinct color steps for anno_df columns with 10 or fewer distinct values, which is mostly helpful with a small number of integer values.
nmatlist2heatmaps() uses nrow for discrete annotation color layout instead of ncol -- jokergoo::ComplexHeatmap kindly updated the package to handle both, but nrow is more definitive in this use case.

platjam 0.0.25.900

applyXlsxConditionalFormatByColumn() fixed bug in verbose output that referred to nonexistent object. Also removed verbose=TRUE from calling function save_salmon_qc_xlsx().

platjam 0.0.24.900

save_salmon_qc_xlsx() saves output from get_salmon_meta() in a convenient Excel .xlsx format, with four worksheets showing different aspects of data quality. It returns a list of data.frame summaries invisibly, for further review.
applyXlsxConditionalFormatByColumn() applies conditional formatting using values in each column, rather than using a fixed range for all columns. This function will become part of jamba::writeOpenxlsx() and jamba::applyXlsxConditionalFormat() in the near future.
set_xlsx_colwidths() and set_xlsx_rowheights() define fixed column width and row height, respectively, for .xlsx files.

platjam 0.0.23.900

color_complement() takes input color, rotates the color hue 180 degrees to make a complement color. It is unique in that it uses warped hue (see colorjam::h2hw()) which therefore uses red-yellow-blue color wheel instead of red-green-blue, which is much better for color operations like these. This function will almost certainly be moved into the colorjam package. The examples show how to make a divergent color gradient from a single color.

nmatlist2heatmaps() new argument nmat_names used to supply custom names for each heatmap, otherwise the attribute "signal_name" values are used.
nmatlist2heatmaps() fixed error caused by use_raster=TRUE and any operation that expects to create a grid graphical object, such as multienrichjam::grid_with_title(), or multi-row output specified with hm_nrow=2.
nmatlist2heatmaps() new arguments heatmap_legend_param and annotation_legend_param allow customizing the legends in detail, passed to ComplexHeatmap::Heatmap(). However, default settings show color gradients horizontally, which may save some screen space.
nmatlist2heatmaps() new arguments title and caption invoke a prototype method that calls multienrichjam::grid_with_title() to position an overall title and caption above and below the heatmaps, respectively. When supplied, these sections are displayed and the heatmaps are resized accordingly.
nmatlist2heatmaps() now properly handles k_subset to plot a subset of clusters provided by partition or after k_clusters is used to create clusters. Mostly useful for follow-up plots to drill down into one or more specific clusters.
nmatlist2heatmaps() now properly handles row_order for edge cases like k_subset, or when row_order=NULL; also row_order=TRUE will enable the default EnrichedHeatmap::enriched_score() for the main_heatmap using only the rows being displayed.
nmatlist2heatmaps() new argument border whether to draw a border around the heatmap. It can be supplied as a vector, to control the border around each heatmap if needed.

platjam 0.0.22.900

nmatlist2heatmaps() accepts input nmat_colors with color functions, for example sending output from circlize::colorRamp2().
nmatlist2heatmaps() when given a single color per matrix, when data is determined to have positive and negative values, it generates a divergent color ramp using the supplied color, and complementary color. To define a specific set of colors, supply a three color vector, the middle color will be fixed at zero.

nmatlist2heatmaps() no longer requires ylims and uses ylim=NULL properly.

platjam 0.0.21.900

parse_ucsc_gokey() was updated to recognize bigBed/bb files can not become overlay tracks.

platjam 0.0.20.900

get_track_defaults() was modified to include shortLabel,longLabel in the template for multiWig tracks. Apparently a label is displayed and it uses the internal hub number as a prefix by default.

platjam 0.0.19.900

get_salmon_meta() is intended to load Salmon transcript quantification metadata from several output JSON files, returning results in a data.frame with one row per Salmon run. It combines various measured statistics from "meta_info.json", "cmd_info.json", and "lib_format_counts.json" so that multiple Salmon runs can be directly compared in a table format.
get_salmon_root() is a wrapper to rprojroot::find_root(), intended to find the root directory of a Salmon run given any Salmon output file. It searches for the root directory that contains the file "cmd_info.json".

platjam 0.0.18.900

get_numeric_transform() was updated to clean up the help docs, to accept "linear" as a valid name (which does not change the input data), and to parse the input transform values in order to assign reasonable names where possible.

platjam 0.0.17.900

Fixed various bugs in nmatlist2heatmaps(). No doubt there will be more, covering the host of assumptions made for the panel_groups, signal_ceiling, and ylims arguments.

platjam 0.0.16.900

Changes to `nmatlist2heatmaps()`

Cool new feature: nmatlist2heatmaps() argument panel_group, when it is defined, it calculates a shared ylims for each group of panels, and a shared signal_ceiling for each group of panels. The signal ceiling uses the supplied signal_ceiling for each panel (if supplied) then takes the maximum value for each group of panels. So if signal_ceiling=0.8 it is treated as quantile 0.8, the 0.8 quantile is calculate for all non-zero values for each panel, then each group of panels uses the max for that group.
nmatlist2heatmaps() the ht_gap gap between heatmaps is not applied between annotation heatmaps, instead "1mm" gap is used between annotation heatmaps. The purpose of ht_gap is to have enough gap between heatmaps so the y-axis profile plot labels can be displayed, but there are no y-axis labels for annotations.
The default lens for anno_df numeric columns is now lens=1, reverting previous change lens=2 which was causing gradients to be darker than expected.
The verbose output is now more concise, and TRUE by default. For even more detail use verbose=2.

get_nmat_ceiling() is a simple wrapper function called by nmatlist2heatmaps() and not intended to be called directly. It takes a numeric matrix, and ceiling, and returns what I determines to be the appropriate ceiling to use.

platjam 0.0.15.900

nmatlist2heatmaps() modified signal_name to clean up leading/trailing whitespace and return \n, and repeated return \n characters.
nmatlist2heatmaps() new argument ht_gap used to define the gap between heatmap panels. This argument is intended to help reduce the overlap of the top y-axis profile labels in adjacent profile panels.
nmatlist2heatmaps() new argument axis_name, as either a vector, or a list of vectors, used for x-axis labels across each panel.
nmatlist2heatmaps() new argument column_title_gp, as either a grid::gpar object, or list of gpar objects.
nmatlist2heatmaps() new argument profile_value, passed to EnrichedHeatmap::anno_enriched() to define the type of numeric summary to use for the profile plots.
nmatlist2heatmaps() new argument panel_groups, character vector of groups used to apply consistent y-axis ylims values per group. By default if nmat_colors is not supplied, then colorjam::group2colors(panel_groups) is used to define group colors.

platjam 0.0.14.900

nmatlist2heatmaps() fixed bug in handling argument signal_ceiling, which when the value is between 0 and 1 is treated as a quantile. The method now removes zero before the quantile() calculation.
nmatlist2heatmaps() fixed bug that wrongly expanded argument axis_names_gp as a list without realizing class "gpar" is also a list. Now "gpar" is wrapped in list() before expanding to the number of coverage matrices.
nmatlist2heatmaps() fixed bug where argument axis_name_rot was not defined in the function itself.

platjam 0.0.13.900

nmatlist2heatmaps() altered the logic used to define color ranges in numeric columns of anno_df, opting to use quantile ranges c(0.005, 0.995) to help trim extreme values. Also changed "purple" to "Purples" to use the RColorBrewer purple color gradient.

platjam 0.0.12.900

get_numeric_transform() bug fixed wrong argument name used inside the function. Should also resolve issues with nmatlist2heatmaps().

platjam 0.0.11.900

import_nanostring_rcc() reads Nanostring RCC files, and produces a SummarizedExperiment object suitable for use in omics-style analyses.

platjam 0.0.10.900

nmatlist2heatmaps() new argument signal_ceiling defines a numerical ceiling for each input matrix, used to apply the color ramp to a defined numeric range. When signal_ceiling is between 0 and 1, it is assumed to be a quantile, so the appropriate quantile value is used as the ceiling. These values can be seen when verbose=TRUE.
nmatlist2heatmaps() argument transform now accepts text string for transformation functions, such as "log2signed", "sqrt", "cubert", etc. Any other string will try to match a function name in the R search path.

get_numeric_transform() is used to apply name-based transformations, called from nmatlist2heatmaps().

Some new functions were added to help create UCSC genome browser track hubs, which are fairly tedious to build manually.

get_track_defaults() returns default values for tracks, including some track snippet templates for composite and overlay track types.
parse_ucsc_gokey() is a parser for a specific track type, based upon prominent scientist Dr. Gokey, who defines a straightforward format for a series of grouped tracks.
make_ucsc_trackname() creates a valid UCSC track name, removing invalid characters.
assign_track_defaults() assigns track values to an environment which may already contain default values. New values override previous values, after which the environment can be used with the glue package to update a track snippet template for each track in a set.

platjam 0.0.9.900

coverage_matrix2nmat() now accepts a vector of files as input, and will process them and return a list of normalizedMatrix objects, ready to go directly into nmatlist2heatmaps().

platjam 0.0.8.900

nmatlist2heatmaps() fixed bug in placement of argument show_error, now properly placed inside EnrichedHeatmap::anno_enriched().

platjam 0.0.7.900

nmatlist2heatmaps() new argument show_error is passed to EnrichedHeatmap::anno_enriched() which enables shaded error bars using standard error around the profile at the top of each heatmap.

frequency_matrix2nmat() converts a frequency matrix whose colnames represent numeric frequency values, and converts to class "normalizedMatrix" for use in EnrichedHeatmap. It optionally scales each row using rowNormScale().
rowNormScale() applies jamba::normScale() to each row of a matrix.

platjam 0.0.6.900

nmatlist2heatmaps() argument k_subset now works when partition is supplied and k-means clustering is not performed inside this function. Therefore, one can supply their own clusters, and choose a subset for subsequent drilldown. The colors are assigned by total cluster, so the subset should retain consistent colors per cluster.
nmatlist2heatmaps() argument k_method allows defining different k-means clustering methods, including c("pearson","correlation") if the "amap" package is installed.

platjam 0.0.5.900

Version bump while debugging logistics with nmatlist2heatmaps() argument transform.

platjam 0.0.4.900

nmatlist2heatmaps() argument transform is now applied to each heatmap, with transform values recycled to the length(nmatlist), to allow control over mathematical transformation of each numeric matric.

platjam 0.0.3.900

nmatlist2heatmaps() argument anno_df is a data.frame with annotations that can be used to order rows in the data.
nmatlist2heatmaps() updated its method to handle proper order of user-supplied partition information.
nmatlist2heatmaps() new arguments to handle row labeling, still testing the combination of partitions and row labels which appear misaligned.

platjam 0.0.2.900

The package itself allows installation on R-3.0.0 and higher, resolving an issue with installing on R-3.5.0 when the package said it required R-3.5.1 (and did not).

platjam 0.0.2.900

nmatlist2heatmaps() creates multiple coverage heatmaps as the result of importing data with coverage_matrix2nmat().

platjam 0.0.1.900

Initial release.

coverage_matrix2nmat() imports genome coverage matrix file and converts to class normalizedMatrix for use in the amazing "EnrichedHeatmap" package.

jmw86069/platjam documentation built on Sept. 26, 2024, 3:31 p.m.

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Note that we can't provide technical support on individual packages. You should contact the package authors for that.

jmw86069/platjam Platform Jam, biological platform importers.

NEWS.md In jmw86069/platjam: Platform Jam, biological platform importers.

platjam 0.0.90.900

updates to existing functions

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bug fixed

platjam 0.0.88.900

new functions

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changes to existing functions

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platjam 0.0.84.900

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changes to existing functions

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migration of coverage heatmap functions to coverjam

platjam 0.0.71.900

changes to existing functions

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jmw86069/platjam
Platform Jam, biological platform importers.

NEWS.md
In jmw86069/platjam: Platform Jam, biological platform importers.

new function `import_lipotype()`

new function `design2colors()` (in development)

changes to `nmatlist2heatmaps()`

changes to `nmatlist2heatmaps()`