varoquaux2019leaf: Time course transcriptomic data from leaf and root tissues...

In NelleV/timecoursedata: A data package for timecourse RNA-seq and microarray gene expression data sets

Description

Time-course RNA-seq leaf and root data from "Transcriptomic analysis of field-droughted sorghum from seedling to maturity reveals biotic and metabolic responses"

Usage

data(varoquaux2019leaf)
data(varoquaux2019root)

Format

A list with two related datasets: a gene expression data set (element data) and corresponding meta data (element meta). The column names of data correspond to the rownames of meta, linking the samples together in the two datasets. See examples for accessing these two data.frames.

Details

This are two datasets from a mRNA-Seq time-course experiment, measuring gene expression across time in the plant sorghum. One dataset corresponds to the leaf of the plant (varoquaux2019leaf), the other to the root from the same sets of plants (varoquaux2019leaf). Each sample sequenced is actually a pool of at least 10 plants. Note that leaf and root samples were processed and sequenced as two separate batches. Any comparison between the two datasets should be traded with care.

data is a data frame with 34,211 rows corresponding to sorghum genes with (Phytozome v3.0 gene ids). Root has 198 columns and leaf has 197 columns, corresponding to samples. The root and leaf samples are from the same plants, and have ids in the form of "0622162L05" or "0622162R05", with "L" corresponding to the leaf and "R" corresponding to the root sample. Some samples were removed for quality control reasons, resulting in slightly different numbers of samples between the leaf and root.

The data provided is the raw data. Note that leafs and roots were sequenced as two different batches.

meta is a data frame with rows corresponding to samples and and columns with meta data. These columns are the same across leaf and root, allowing for easy reuse of code across the datasets:

Barcode

Barcode of the sample, same as row name

libraryName

Internal Barcode given to the sample by the sequencing facility (JGI)

Block

Plot from which the sample was taken

Week

Numeric value corresponding to the week sample was taken

Replicate

Each condition combination was replicated three times, but not all replicates were sequenced. Each replicate came from a different plot. The replicate id tracks this plot for each condition. However, replicate 1 in one condition is a completely different plot from replicate 1 in another condition, though the replicates were physically close to each other in the field.

Genotype

Genotype (i.e. variety) of the sample, one of BT642 or RT430

Condition

The drought condition, one of "Control" (regular watering), "Postflowering" (drought applied post flowering of the plant), or "Preflowering" (drought applied pre-flowering of the plant, and then watering resumed after flowering)

Sample.type

Either "Leaves" or "Root", only relevant if merging the two datasets

Day

The day sample collected, in form of "Day14" (corresponding to Week 2)

Row

Row plant was sampled from within the block

isFloweringWeek

logical, indicating whether the week sampled corresponding to the plant flowering

Date.Harvested

The date sample was collected

Collection.Time

The time of day plant was collected

No.plants.pooled

The number of plants pooled for the sample

FloweringJulianDate

The Julian date of flowering for the block the sample was collected from

FloweringDate

The date of flowering for the block the sample was collected from

FloweringWeek

The week of flowering for the block the sample was collected from

FloweringDay

The day of flowering for the block the sample was collected from

Unreplicated

Identifies timepoints with no replicates

CompleteSampleTreatment

Full set of factors (Genotype x Treatment x Week)

The following variables are features measured at the end of planting when the remaining plants from the plot were harvested:

LbsGrainHarvestPerPlot

TonsOfGrain.ac

PctGrainMoisture

TonsOfGrain.acAt13PctMoisture

X1000SeedWt_g

ApproximateEndOfSeasonStandCount_aveOfGrainRows

TotalFreshForageWtPerPlot_kg

TotalFreshForageWtPerPlot_lbs

TonsOfForage.ac

PctMoistureForage

TonsOfForage.acAt65PctMoisture

ApproximateEndOfSeasonStandCount_aveOfForageRows

DryBiomass

FreshBiomass

AveHeight

The following variables are features regarding the quality of the mapping of the sequences from the sample:

rawReads

filteredReads

sequencerType

runType

totalFragments

mappedFragments

assignedFragments

unassignedAmbiguous

unassignedNoFeatures

unassignedSecondaryHits

ratioStrandedness

MappedRatio

AssignedRatio

Plate

Location

References

Varoquaux et al, 2019 (PNAS)

Examples

data(varoquaux2019leaf)
dataLeaf = attr(varoquaux2019leaf, "data")
metaLeaf = attr(varoquaux2019leaf, "meta")
data(varoquaux2019root)
dataRoot = attr(varoquaux2019root, "data")
metaRoot = attr(varoquaux2019root, "meta")

NelleV/timecoursedata documentation built on June 30, 2021, 11:07 p.m.