CassavaBase

Upload an experimental field trial into the database that you have saved on your computer in Excel

Design a completely new experimental field trial in the database

Catalog your available seed inventory into the database

Upload phenotypic data into the database that you have saved on your computer in Excel

Plan tissue sampling

Upload crosses and crossing information into the database

Print barcode labels for my experiment (for your plots or plants or tissue samples in the field, or for your 96 well plate and tissue samples)

Analyze phenotypic performance across trials

Prepare a 96 or 384 well plate for a genotyping experiment

Upload VCF genotypic data

Intro
Sampling Level
Select a field trial
Plant Entries
Create Tissue Sample Entries

This workflow will guide you through tissue sampling an experiment

Tissue samples collected from the field are linked to a single plant, which is in turn linked to a single plot.

Many tissue samples can be created for each plant.

Each tissue sample has a globally unique name.

A unique tissue sample is present in each well of a genotyping plate (96 or 384 well plates).

The tissue sample in a 96 well plate can originate from another tissue sample name, plant name, plot name, or accession name.
At which level do you plan to keep track of your sampling?
   Accession Level: The sample is not from a field trial entity and only the accession name is known.
   Plot Level: Each plot in the field has a unique identifier, ideally with a barcode label.
   Plant Level: Each plant in the field has a unique identifier, ideally with a barcode label.
   Tissue Sample Level: Each tissue sample collected from the field has a unique identifier, ideally with a barcode label.

Select a field trial

Plant entries in your field trial

Plant entries not relevant for the type of tissue sampling you selected. Go to next step.

Plant entries exist for this trial. Go to next step.

Please create plant entries for this trial.

Number of plants per plot:

Inherits Management Factor(s) From Plots:
Create tissue sample entries for this trial

Field trial tissue sample entries not relevant for the type of tissue sampling you selected. Go to next step.

Tissue sample entries exist for this trial. Go to next step.

Number of tissue samples per plant:

Inherits Management Factor(s) From Plots:

Complete! You have all the entities you need to conduct your sampling.

All of the entities that you want to sample are saved in the database and available to use!
You can print barcodes for the entities you intend to sample on. These barcodes can be attached to your collection vials/containers to assist during sampling.

After you have finished sampling, you can use these entities as source material for a genotyping plate (96 or 384 well plate). Click the button below to create a genotyping plate now, if you will create a 96 or 384 well plate.
The Android Coordinate application can help you create 96 or 384 well plates. Alternatively you can create your plate layout in Excel and upload it.

Complete! You have all the entities you need to conduct your sampling.

All of the entities that you want to sample are saved in the database and available to use!
You can print barcodes for the entities you intend to sample on. These barcodes can be attached to your collection vials/containers to assist during sampling.

After you have finished sampling, you can use these entities as source material for a genotyping plate (96 or 384 well plate). Click the button below to create a genotyping plate now, if you will create a 96 or 384 well plate.
The Android Coordinate application can help you create 96 or 384 well plates. Alternatively you can create your plate layout in Excel and upload it.

Trials may be uploaded in an Excel file (.xls)
(.xlsx format not supported)

Header:
The first row (header) must contain the following:

plot_name	accession_name	plot_number	block_number	is_a_control	rep_number	range_number	row_number	col_number	seedlot_name	num_seed_per_plot	weight_gram_seed_per_plot

Header as a string:

plot_name,accession_name,plot_number,block_number,is_a_control,rep_number,range_number,row_number,col_number,seedlot_name,num_seed_per_plot,weight_gram_seed_per_plot

Required fields:

plot_name (must be unique across entire database. this is often a concatenation of the trial name, the accession name, and the plot number.)
accession_name (must exist in the database. this is the accession being tested in the plot.)
plot_number (a sequential number for the plot in the field (e.g. 1001, 1002, 2001, 2002). these numbers should be unique for the trial.)
block_number (a design parameter indicating which block the plot is in)

Optional fields:

is_a_control (type 1 in this field if the plot is a control, otherwise leave blank. generally you will have accessions that are controls, so you shuold indicate the plots that that accession is in as a control.)
rep_number (replicate number, numeric)
range_number (range number. often synonymous with col_number, numeric)
row_number (row number. if the field is a grid, this represents the y coordinate, numeric, required for field map generation. the top left plot shuold be row 1, column 1)
col_number (column number. if the field is a grid, this represents the x coordinate. sometimes called range_number, numeric, required for field map generation. the top left plot shuold be row 1, column 1)
seedlot_name (the seedlot from where the planted seed originated. must exist in the database)
num_seed_per_plot (number seeds per plot. seed is transferred from seedlot mentioned in seedlot_name. numeric)
weight_gram_seed_per_plot (weight in gram of seeds in plot. seed is transferred from seedlot mentioned in seedlot name. numeric)

Treatments:

treatment columns (additional column(s) that specify the name of a treatment (e.g. inoculated, drought, etc). the value for each plot should be 1 if the treatment was applied or empty.)

Background:

Partially replicated designs have some treatments that are unreplicated and rely on replicated treatments to make the trial analysable. The design were described in Cullis et al. (2006). It is recommended that at least 20% of the experimental units are occupied by replicated treatments. The aim of these experiments is usually to select promising treatments from a set of replicated and unreplicated test treatments, with check and quality standard treatments providing the necessary replication overall to give a valid experiment. DiGGer (Coombes, 2002) was used to implement this design. DiGGer is a flexible tool for creating experimental designs that are efficient for specified blocking and correlation patterns. DiGGer package (http://www.austatgen.org/files/software/downloads) is an add-on for the statistical computing language and environment R (R Development Core Team, 2009).

Design Parameters:

The parameters will consider a sample partially replicated design trial with 200 unreplicated accessions, 119 accessions replicated 4 times, 26 rows in design, 26 columns in design, bock sequence of 13 by 2 (13, 2) i.e 2 blocks with each having 13 rows; sub-block sequence of block of 13 by 1 (13, 1) i.e 1 sub-block with each having 13 rows in each block.

List of Unreplicated Accession: You're expected to provide the list of unreplicated accessions in this selectbox. E.g. is a list of 200 accessions.
List of Replicated Accession: List of replicated accessions should be provided in this selectbox. E.g. is a list of 119 accessions.
Number of rows in design: Provide the number of rows you want to have in the design. E.g. 26 number of rows.
Number of Columns in Design: Provide the number of columns you want to have in the design. E.g. 26 number of columns.
Number of Times Replicated Accessions are Replicated: Provide the number of times you want the replicated accessions to be replicated. E.g. 4
Block Sequence: The block sequence should reflect the blocking structure of your design. E.g. (13, 2), meaning the design has 2 blocks and each block has 13 rows.
Sub-block Sequence: The sub-block sequence should reflect the sub-blocking structure of your design. E.g. (13, 1), meaning the design has 1 sub-block (column) and each sub-block has 13 rows.

NOTE:

The product of the number of rows and columns in the design should equal the total number of plots. The sum of the unreplicated accessions and the replicated accessions (given the number of times it was replicated) should equal the total number of plots.: The product of the number of rows and columns in the design should equal the total number of plots.; The sum of the unreplicated accessions and the replicated accessions (given the number of times it was replicated) should equal the total number of plots.

Intro
Genotyping Project
Genotyping Protocol
Genotype Info
Confirm

This workflow will guide you through uploading genotypes into the database

Select a genotyping project on the next screen. This project can represent a series of genotyping plates sent to a genotyping facilty.

Ideally the sample names in your VCF file will match sample names in genotyping plates in the database; however, the sample names in your file can also match accession names in the database.

Curently we support the VCF format for upload.

Select the genotyping project or create a new one

Select	Genotyping Project Name	Description	Breeding program	Year	Location	Genotyping Facility

Provide info about the protocol used

Select	Protocol Name	Header Description	Number of Markers	Protocol Description	Reference Genome	Species	Sample Unit	Create Date

Genotyping Protocol Name:

Genotyping Protocol Reference Genome:

Species:

Description:

Choose Sample Unit:

Exported Tissue Sample Name: The sample names in your VCF are tissue_sample_names that already exist in genotyping plates (e.g. 96 well plates) in the database. The sample names in your VCF file can be the tissue_sample_name triple pipe joined to the accession_name (e.g. tissue_sample_name|||accession_name) or just simply the tissue_sample_name corresponding to the genotyping plate well.

Accession: The sample names are of accession names

Location of Data Generation:

Exported Tissue Sample Names Include Numbers Generated by Genotyping Facility (e.g. sample_name:IGD1001:09):
The generated number is separated from the tissue sample name in the database by a ':' separating character.

Provide genotype information

File format information
VCF format

Select VCF File:

Finalize and submit your genotyping data

Add these missing stocks as new accessions?:

Ignore warnings and upload genotypes?:

Complete! Your genotyping data was saved in the database.

The genotyping data was saved successfully

Complete! Your genotyping data was saved in the database.

The genotyping data was saved successfully

This is for uploading VCF genotype data.
VCF is a tab separated format
Header:
The first row (header) must contain the following fields, followed by all genotyped sample names:

#CHROM	POS	ID	REF	ALT	QUAL	FILTER	INFO	FORMAT	Sample names...

Required fields:

#CHROM (chromosome: An identifier from the reference genome pointing to a contig in the assembly file (cf. the ##assembly line in the header). All entries for a specific CHROM should form a contiguous block within the VCF file. The colon symbol (:) must be absent from all chromosome names to avoid parsing errors when dealing with breakends. (String, no white-space permitted, Required))
POS (position: The reference position, with the 1st base having position 1. Positions are sorted numerically, in increasing order, within each reference sequence CHROM. It is permitted to have multiple records with the same POS. Telomeres are indicated by using positions 0 or N+1, where N is the length of the corresponding chromosome or contig. (Integer, Required) )
ID ( identifier: Semi-colon separated list of unique identifiers where available. If this is a dbSNP variant it is encouraged to use the rs number(s). No identifier should be present in more than one data record. If there is no identifier available, then the missing value should be used. (String, no white-space or semi-colons permitted) )
REF (reference base(s): Each base must be one of A,C,G,T,N (case insensitive). Multiple bases are permitted. The value in the POS field refers to the position of the first base in the String. For simple insertions and deletions in which either the REF or one of the ALT alleles would otherwise be null/empty, the REF and ALT Strings must include the base before the event (which must be reflected in the POS field), unless the event occurs at position 1 on the contig in which case it must include the base after the event; this padding base is not required (although it is permitted) for e.g. complex substitutions or other events where all alleles have at least one base represented in their Strings. If any of the ALT alleles is a symbolic allele then the padding base is required and POS denotes the coordinate of the base preceding the polymorphism. Tools processing VCF files are not required to preserve case in the allele Strings. (String, Required) )
ALT (alternate base(s): Comma separated list of alternate non-reference alleles. These alleles do not have to be called in any of the samples. Options are base Strings made up of the bases A,C,G,T,N,*, (case insensitive) or a breakend replacement string as described in the section on breakends. The '*' allele is reserved to indicate that the allele is missing due to a upstream deletion. If there are no alternative alleles, then the missing value should be used. Tools processing VCF files are not required to preserve case in the allele String, except for IDs, which are case sensitive. (String; no whitespace, commas, or angle-brackets are permitted in the ID String itself) )
QUAL (quality: Phred-scaled quality score for the assertion made in ALT. i.e. -10log10 prob(call in ALT is wrong). If ALT is '.' (no variant) then this is -10log10 prob(variant), and if ALT is not '.' this is -10log10 prob(no variant). If unknown, the missing value should be specified. (Numeric) )
FILTER (filter status: PASS if this position has passed all filters, i.e. a call is made at this position. Otherwise, if the site has not passed all filters, a semicolon-separated list of codes for filters that fail. e.g. "q10;s50" might indicate that at this site the quality is below 10 and the number of samples with data is below 50% of the total number of samples. "0" is reserved and should not be used as a filter String. If filters have not been applied, then this field should be set to the missing value. (String, no white-space or semi-colons permitted) )
INFO (additional information: (String, no white-space, semi-colons, or equals-signs permitted; commas are permitted only as delimiters for lists of values) INFO fields are encoded as a semicolon-separated series of short keys with optional values in the format: key=data[,data]. Arbitrary keys are permitted, although the following sub-fields are reserved (albeit optional):

AA : ancestral allele
AC : allele count in genotypes, for each ALT allele, in the same order as listed
AF : allele frequency for each ALT allele in the same order as listed: use this when estimated from primary data, not called genotypes
AN : total number of alleles in called genotypes
BQ : RMS base quality at this position
CIGAR : cigar string describing how to align an alternate allele to the reference allele
DB : dbSNP membership
DP : combined depth across samples, e.g. DP=154
END : end position of the variant described in this record (for use with symbolic alleles)
H2 : membership in hapmap2
H3 : membership in hapmap3
MQ : RMS mapping quality, e.g. MQ=52
MQ0 : Number of MAPQ == 0 reads covering this record
NS : Number of samples with data
SB : strand bias at this position
SOMATIC : indicates that the record is a somatic mutation, for cancer genomics
VALIDATED : validated by follow-up experiment
1000G : membership in 1000 Genomes

FORMAT (A format field is given specifying the data types and order (colon-separated alphanumeric String). This is followed by one field per sample, with the colon-separated data in this field corresponding to the types specified in the format. The first sub-field must always be the genotype (GT) if it is present. There are no required sub-fields. As with the INFO field, there are several common, reserved keywords that are standards across the community:
- GT : genotype, encoded as allele values separated by either of / or |. The allele values are 0 for the reference allele (what is in the REF field), 1 for the first allele listed in ALT, 2 for the second allele list in ALT and so on. For diploid calls examples could be 0/1, 1 | 0, or 1/2, etc. For haploid calls, e.g. on Y, male nonpseudoautosomal X, or mitochondrion, only one allele value should be given; a triploid call might look like 0/0/1. If a call cannot be made for a sample at a given locus, '.' should be specified for each missing allele in the GT field (for example './.' for a diploid genotype and '.' for haploid genotype). The meanings of the separators are as follows (see the PS field below for more details on incorporating phasing information into the genotypes):
- DP : read depth at this position for this sample (Integer)
- FT : sample genotype filter indicating if this genotype was "called" (similar in concept to the FILTER field). Again, use PASS to indicate that all filters have been passed, a semi-colon separated list of codes for filters that fail, or '.' to indicate that filters have not been applied. These values should be described in the metainformation in the same way as FILTERs (String, no white-space or semi-colons permitted)
- GL : genotype likelihoods comprised of comma separated floating point log10-scaled likelihoods for all possible genotypes given the set of alleles defined in the REF and ALT fields. In presence of the GT field the same ploidy is expected and the canonical order is used; without GT field, diploidy is assumed. If A is the allele in REF and B,C,... are the alleles as ordered in ALT, the ordering of genotypes for the likelihoods is given by: F(j/k) = (k*(k+1)/2)+j. In other words, for biallelic sites the ordering is: AA,AB,BB; for triallelic sites the ordering is: AA,AB,BB,AC,BC,CC, etc. For example: GT:GL 0/1:-323.03,-99.29,-802.53 (Floats)
- GLE : genotype likelihoods of heterogeneous ploidy, used in presence of uncertain copy number. For example: GLE=0:-75.22,1:-223.42,0/0:-323.03,1/0:-99.29,1/1:-802.53 (String)
- PL : the phred-scaled genotype likelihoods rounded to the closest integer (and otherwise defined precisely as the GL field) (Integers)
- GP : the phred-scaled genotype posterior probabilities (and otherwise defined precisely as the GL field); intended to store imputed genotype probabilities (Floats)
- GQ : conditional genotype quality, encoded as a phred quality -10log10 p(genotype call is wrong, conditioned on the site's being variant) (Integer)
- HQ : haplotype qualities, two comma separated phred qualities (Integers)
- PS : phase set. A phase set is defined as a set of phased genotypes to which this genotype belongs. Phased genotypes for an individual that are on the same chromosome and have the same PS value are in the same phased set. A phase set specifies multi-marker haplotypes for the phased genotypes in the set. All phased genotypes that do not contain a PS subfield are assumed to belong to the same phased set. If the genotype in the GT field is unphased, the corresponding PS field is ignored. The recommended convention is to use the position of the first variant in the set as the PS identifier (although this is not required). (Non-negative 32-bit Integer)
- PQ : phasing quality, the phred-scaled probability that alleles are ordered incorrectly in a heterozygote (against all other members in the phase set). We note that we have not yet included the specific measure for precisely defining "phasing quality"; our intention for now is simply to reserve the PQ tag for future use as a measure of phasing quality. (Integer)
- EC : comma separated list of expected alternate allele counts for each alternate allele in the same order as listed in the ALT field (typically used in association analyses) (Integers)
- MQ : RMS mapping quality, similar to the version in the INFO field. (Integer)
If any of the fields is missing, it is replaced with the missing value. For example if the FORMAT is GT:GQ:DP:HQ then 0 | 0 : . : 23 : 23, 34 indicates that GQ is missing. Trailing fields can be dropped (with the exception of the GT field, which should always be present if specified in the FORMAT field). )

This is for uploading a pre-existing genotyping plate layout.
File must be Excel file (.xls)
(.xlsx format not supported)

Header:
The first row (header) must contain the following:

date	sample_id	well_A01	row	column	source_observation_unit_name	ncbi_taxonomy_id	dna_person	notes	tissue_type	extraction	concentration	volume	is_blank

Required fields:

date (should be YYYY-MM-DD)
sample_id (the unique identifier for the sample in the well)
well_A01 (the position of the sample in the plate)
row (the row position of the sample in the plate e.g. A)
column (the column position of the sample in the plate e.g. 10)
source_observation_unit_name (must exist in the database. the identifier of the origin material. in order of most desirable identifier to least desirable identifier that can be used here: tissue sample name, plant name, plot name, accession name)

Optional fields:

ncbi_taxonomy_id (NCBI taxonomy identifier)
dna_person (the name of the person who prepared the well)
notes (any additional notes on the well)
tissue_type (free-text for what type of tissue is present in the well)
extraction (free-text for the extraction method e.g. CTAB)
concentration (concentration in ng/ul)
volume (volume in ul)
is_blank (indicates if well is blank. write 1 if blank, otherwise leave empty.)

This is for uploading a Default Coordinate Android Application exported plate layout.
File must be a CSV file (.csv)
(Excel format not supported)

Header:
The first row (header) must contain the following:

date	plate_id	plate_name	sample_id	well_A01	well_01A	tissue_id	dna_person	notes	tissue_type	extraction

Required fields:

date (should be YYYY-MM-DD)
plate_id (an identifier for a grouping of plates. called "Genotyping Project Name" in genotyping plate submission form. e.g. NextGenCassava)
plate_name (the unique name for the individual plate. called "Plate ID" in genotyping plate submission form. e.g. 18DNA00001)
sample_id (the unique identifier for the sample in the well. e.g. 18DNA00001_A01)
well_A01 (the position of the sample in the plate in this format A01)
well_01A (the position of the sample in the plate in this format 01A)
tissue_id (the identifier of the origin material. in order of most desirable identifier to least desirable identifier that can be used here: tissue sample name, plant name, plot name, accession name. this can also say 'BLANK' to indicate a blank well.)
dna_person (the name of the person who plated the individual sample. can be any name.)

Optional fields:

notes (any additional notes on the well)
tissue_type (free-text for what type of tissue is present in the well)
extraction (free-text for the extraction method e.g. CTAB)

This is for uploading a Custom Coordinate Android Application exported plate layout.
File must be a CSV file (.csv)
(Excel format not supported)

Header:
The first row (header) must contain the following:

Value	Column	Row	Identification	Person	Date

Required fields:

Value (the identifier of the origin material. e.g. 2018MyPlant0001. in order of most desirable identifier to least desirable identifier that can be used here: tissue sample name, plant name, plot name, accession name. This can also say 'exclude' to indicate a BLANK)
Column (the column position of the sample e.g. 10)
Row (the row position of the sample e.g. A)
Identification (free text)
Person (the name of the person who plated the individual sample. can be any name.)
Date (should be YYYY-MM-DD)

Intro
File format
Upload inventory
Fix missing seedlots problem
Try submitting inventory again

What is a seedlot inventory?
- Seedlots represent physical seed in packets.
- This seed can be from crosses or for named accessions.
- Seedlots can have a specific location, box, weight(g), and count.
- Seedlots can belong to breeding programs and organizations.
- Seedlots can be used in trials (e.g. they were planted in a plot) and they can be harvested from a plot or plant (e.g. a cross was performed and seeds were collected.)
- A seedlot inventory consists of giving a location and current weight(g) to your seedlots. The seedlot name is the unique identifier for each seedlot and so should be encoded in a barcode on each seedlot packet.
- You can use the "Seed Inventory" Android Application to scan seedlot barcodes and record weight. If you prefer you can create your own CSV file and upload that, if you do not want to use the Seed Inventory Application. For info about the format of the file to upload, go to the next tab.
- For more info about the "Seed Inventory" Android Application go to Seed Inventory.
- It is also possible to manually enter a transaction by going to the seedlot detail page and clicking "Add New Transaction".
Make sure you are collecting seedlot inventory in the following format

The "Seed Inventory" Android Application will export this same exact format by default.
Select your file and upload seedlot inventory

Upload File (.csv):
Fixing the missing seedlot(s) problem
- Seedlots must exist in the database prior to updating or adding inventory. The reason for this is that the inventory does not give information about the content (a named accession or a cross name) and this information is required for a seedlot to exist in the database. We also want to be careful about adding new seedlots into the database because we do not want data to be incorrectly linked to duplicates.
- When adding seedlots into the database, you can upload an Excel file or you can add seedlots one at a time.
Seedlot Inventory Upload Error Messages
Submit your inventory again. You should have corrected all errors by now, but if not please take a look at the errors in the red box below. You can continue to modify your file and then click Upload until it works.

There exist these problems in your file:

Finished! Your seedlot inventory is in the database

The seedlot inventory file was uploaded successfully

You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just updated.
You can print barcodes for the seedlots.

Finished! Your seedlot inventory is in the database

The seedlot inventory file was uploaded successfully

You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just updated.
You can print barcodes for the seedlots.

Seedlots may be uploaded in a CSV file (.csv)
(Excel .xls and .xlsx format not supported)

Header:
The first row (header) should contain the following:

box_id	seed_id	inventory_date	inventory_person	weight_gram

Required fields:

box_id (the name of the box that the seedlot is in. also called box_name.)
seed_id (unique identifier for the seedlot. must exist in the database. also called seedlot_name)
inventory_date (a timestamp for when the seedlot was inventoried)
inventory_person (the name of the person doing the inventory. can be any name. also called operator_name)
weight_gram (the weight in grams of the seedlot)

Intro
What seedlots do you have?
File format
Upload seedlots
Fix errors in file
Try submitting seedlots again

What are seedlots?
- Seedlots represent physical seed in packets.
- This seed can be from crosses or for named accessions.
- Seedlots can have a specific location, box, weight(g), and count.
- Seedlots can belong to breeding programs and organizations.
- Seedlots can be used in trials (e.g. they were planted in a plot) and they can be harvested from a plot or plant (e.g. a cross was performed and seeds were collected.)
Seedlots fall into two categories

Select One:
Make sure your file matches the correct file format
Provide basic information about the seedlots and upload your file

Breeding Program:

Location of seedlot storage:

Organization Name:

Upload File (.xls):

Upload File (.xls):
Fix all errors in your file
- Accessions must exist in the database prior to adding seedlots of them. The reason for this is that an accession can be exist in many seedlots and therefore exists as a separate entity in the database. We also want to be careful about adding new accessions into the database because we do not want incorrectly duplicated data.
- When adding accessions into the database, you can use either a list of accessions or an Excel file.
- Crosses must exist in the database before adding your seed lots. The reason for this is that a cross can produce many seed lots and so the cross must exists as a separate entity in the database. We also want to be careful about adding new crosses into the database because we do not want data to be incorrectly linked to duplicates.
- When adding crosses into the database, you can upload an Excel file or you can add seedlots one at a time.
Seedlot Upload Error Messages
Submit your seedlots again. You should have corrected all errors by now, but if not please take a look at the errors in the red box below. You can continue to modify your file and then click Upload until it works.

There exist these problems in your file:

Finished! Your seedlots are now in the database

The seedlot file was uploaded successfully

You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just created.
You can print barcodes for the seedlots.

Finished! Your seedlots are now in the database

The seedlot file was uploaded successfully

You may want to proceed to the seedlot detail page(s) for the seedlot(s) you just created.
You can print barcodes for the seedlots.

Seedlots may be uploaded in an Excel file (.xls)
(.xlsx format not supported)

Header:
The first row (header) must contain the following:

seedlot_name	accession_name	operator_name	amount	weight(g)	description	box_name

Required fields:

seedlot_name (must be unique)
accession_name (must exist in the database. the accession_name is the unique identifier for the named genotype)
operator_name (the name of the person who oversaw the inventory process. can be any name.)
amount (number of seeds in seedlot. can be provided in conjunction with weight(g). must provide a value for amount or weight(g) or both.)
AND/OR
weight(g) (weight in grams of seedlot. can be provided in conjunction with amount. must provide a value for amount or weight(g) or both.)

Optional fields:

description (information about why this seedlot is being added)
box_name (the box name that the seed is located in. can be any name.)

Seedlots may be uploaded in an Excel file (.xls)
(.xlsx format not supported)

Header:
The first row (header) must contain the following:

seedlot_name	cross_name	operator_name	amount	weight(g)	description	box_name

Required fields:

seedlot_name (must be unique)
cross_name (must exist in the database. a cross_name can represent a cross between accessions e.g. AxB, but a cross can also represent a cross between specific plots in the field if you have this information)
operator_name (the name of the person who oversaw the inventory process. can be any name.)
amount (number of seeds in seedlot. can be provided in conjunction with weight(g). must provide a value for amount or weight(g) or both.)
AND/OR
weight(g) (weight in grams of seedlot. can be provided in conjunction with amount. must provide a value for amount or weight(g) or both.)

Optional fields:

description (information about why this seedlot is being added)
box_name (the box name that the seed is located in. can be any name.)

Accessions may be uploaded in an Excel file (.xls)
(.xlsx format not supported)

Header:
The first row (header) should contain the following:

accession_name	species_name	population_name	organization_name(s)	synonym(s)	location_code(s)	ploidy_level(s)	genome_structure(s)	variety(s)	donor(s)	donor_institute(s)	donor_PUI(s)	country_of_origin(s)	state(s)	institute_code(s)	institute_name(s)	biological_status_of_accession_code(s)	notes(s)	accession_number(s)	PUI(s)	seed_source(s)	type_of_germplasm_storage_code(s)	acquisition_date(s)	transgenic	introgression_parent	introgression_backcross_parent	introgression_map_version	introgression_chromosome	introgression_start_position_bp	introgression_end_position_bp

Required fields:

accession_name (must be unique)
species_name (must exist in the database)

Optional fields:

population_name (a population is a grouping of accessions. if the population already exists in the database, the accession will be added into it, otherwise, the new population will be created.)
organization_names (the name(s) of the organization(s) which use this accession. multiple organizations can be given with comma separation (e.g. NARO,IITA))
synonyms (an accession can be known by many names including local popular names. a synonym name can be used instead of the accession_name throughout the database; because of this, synonyms must themselves be unique. multiple synonyms can be given with comma separation (e.g. accession_synonym1,accession_synonym001))
location_code(s) (location code(s) for the accession. many can be uploaded at once in comma separated list)
ploidy_level(s) (a number indicating the ploidy (e.g. 2 for diploid, 3 for triploid), numeric. many values can be uploaded as comma separated list.)
genome_structure(s) (genome structure(s) for accession which take into account ploidy and ancestral genome info e.g. AAA, AB. many can be uploaded as comma separated list.)
variety(s) (variety can be defined as a group of individuals or plants having similar traits that can be reproduced "true to type" from generation to generation. may be uploaded as comma separated list.)
donor(s) (the accession_name of the donor accession. may be uploaded as comma separated list.)
donor_institute(s) (the institute of the donor accession. may be uploaded as comma separated list.)
donor_PUI(s) (the permanent unique identifier of the donor accession. may be uploaded as comma separated list.)
country_of_origin(s) (the country of origin. may be uploaded as comma separated list.)
state(s) (the state of origin. may be uploaded as comma separated list.)
institute_code(s) (the institute code of origin. may be uploaded as comma separated list.)
institute_name(s) (the institute name of origin. may be uploaded as comma separated list.)
biological_status_of_accession_code(s) (code indicating the state of accession. may be uploaded as comma separated list.)
notes(s) (free text for notes. may be uploaded as comma separated list.)
accession_number(s) (accession number for accession from germplasm bank. may be uploaded as comma separated list.)
PUI(s) (permanent unique identifier of the accession. may be uploaded as comma separated list.)
seed_source(s) (origin of seed source. may be uploaded as comma separated list.)
type_of_germplasm_storage_code(s) (code indicating the type of germplasm storage. may be uploaded as comma separated list.)
acquisition_date(s) (date(s) of acquisition YYYYMMDD for accession. may be uploaded as comma separated list.)
transgenic (indicates if accession is transgenic. Please indicate 1 if transgenic and empty if otherwise.)
introgression_parent (if the accession you are adding has an introgression that originated from one of the parents, you can specify the parent here)
introgression_backcross_parent (the backcross parent for introducing an introgression into the accession being added)
introgression_map_version (the map version for identifying the start and stop position of the introgression. e.g. AGPv2)
introgression_chromosome (the chromosome number that the introgression is on.)
introgression_start_position_bp (the start position of the introgression in base pairs)
introgression_start_position_bp (the end position of the introgression in base pairs)

Intro
Crossing experiment
Upload your crosses

What are crosses?
- Crosses represent any pollination that occurs.
- Crosses can be of different types (biparental, self, open, bulk, bulk_self, bulk_open, or doubled_haploid)
- Depending on the cross type, an individual cross can be defined as between two accessions (e.g. accession A is the female and accession B is the male in a biparental cross)
- For an open pollinated cross, the cross can be defined as between female accession A and male population P1 (populations in the database are only defined as groups of accessions)
- An individual cross can be linked to the specific female plot or plant, as well as the specific male plot or plant.
- A cross can have a number of properties associated to it, such as number of flowers, pollination date, etc.
- A cross can produce seed, which goes into a seedlot.
- A cross can ultimately produce progeny, which then become named accessions in the database.
Select a crossing experiment

Crossing experiments are for grouping crosses together. The grouping is most often done for crosses derived from the same field trial, the same year, or for crosses that have the same breeding objective.

Crossing Experiment:

Enter basic information about the crosses and upload your file

Crossing Experiment:

Location of Crosses:

File Format:

Finished! Your crosses are now in the database

The crosses file was uploaded successfully

You may want to proceed to the cross detail page(s) for the cross(es) you just created.
You can print barcodes for the crosses.
You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

Finished! Your crosses are now in the database

The crosses file was uploaded successfully

You may want to proceed to the cross detail page(s) for the cross(es) you just created.
You can print barcodes for the crosses.
You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

Intro
Add a crossing experiment

What are crossing experiments?

Crossing experiments group crosses. The grouping can reflect crosses done in the same field trial, crosses in a breeding program in a given year, or crosses that have the same breeding objective. This grouping can be used to encapsulate all the crosses done in a crossing block field trial that you have saved in the database (e.g. in Manage Trials your crossing block will appear as a field trial with plots)
Enter basic information about the crossing experiment

Crossing Experiment Name:

Breeding Program:

Location of crossing experiment

Year:

Description:

Finished! Your crossing experiment is now in the database

Crossing experiment was added successfully

You may want to proceed to the crossing experiment detail page you just created.
You can add or upload crosses into your crossing experiment as they become available.
You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

Finished! Your crossing experiment is now in the database

Crossing experiment was added successfully

You may want to proceed to the crossing experiment detail page you just created.
You can add or upload crosses into your crossing experiment as they become available.
You can add crossing information as it becomes available (e.g. number of seeds, progeny, etc).

Accessions	Seedlots
Accessions		Breeding Program	Seedlot Name	Contents	Seedlot Location	Count	Weight(g)

Attribute	Value
Project Name:
Start Date:
End Date:
Event Type:
Event Description:
Event Web URL:

Specify Pollination Date:	Pollination Date (YYYY/MM/DD):
Specify Number of Flowers: Specify Number of Fruits:	Number of Flowers: Number of Fruits:
Specify Number of Seeds:	Number of Seeds:
Add New Accessions for Progeny:	Number of progeny:
Use Prefix and/or Suffix:	Prefix: Suffix:

Cassava Genomes

Breeding programs

NextGenCassava Community

& Partners

SGN SlideShare

New to the database?

Which accessions will be in the field?

Number of Plants:

Number of Columns (required):

Number of columns between two check columns (Optional):

Which seedlots will you grow in the field? This is optional and can be decided later. If you do not know exactly which seedlot packets you will be planting at this time, you can add this information on the Trial Detail Page after the trial has been saved in the database.

Which seedlots will you grow in the field?
This is optional and can be decided later. If you do not know exactly which seedlot packets you will be planting at this time, you can add this information on the Trial Detail Page after the trial has been saved in the database.